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<button class="button is-small is-link">Go</button> </div> </div> </form> </div> </div> <nav class="pagination is-small is-centered breathe-horizontal" role="navigation" aria-label="pagination"> <a href="" class="pagination-previous is-invisible">Previous </a> <a href="/search/?searchtype=author&query=Dobre%2C+O+A&start=50" class="pagination-next" >Next </a> <ul class="pagination-list"> <li> <a href="/search/?searchtype=author&query=Dobre%2C+O+A&start=0" class="pagination-link is-current" aria-label="Goto page 1">1 </a> </li> <li> <a href="/search/?searchtype=author&query=Dobre%2C+O+A&start=50" class="pagination-link " aria-label="Page 2" aria-current="page">2 </a> </li> <li> <a href="/search/?searchtype=author&query=Dobre%2C+O+A&start=100" class="pagination-link " aria-label="Page 3" aria-current="page">3 </a> </li> </ul> </nav> <ol class="breathe-horizontal" start="1"> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2502.17128">arXiv:2502.17128</a> <span> [<a href="https://arxiv.org/pdf/2502.17128">pdf</a>, <a href="https://arxiv.org/ps/2502.17128">ps</a>, <a href="https://arxiv.org/format/2502.17128">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1109/TCOMM.2025.3541047">10.1109/TCOMM.2025.3541047 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Conditional Generative Adversarial Networks for Channel Estimation in RIS-Assisted ISAC Systems </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Faisal%2C+A">Alice Faisal</a>, <a href="/search/eess?searchtype=author&query=Al-Nahhal%2C+I">Ibrahim Al-Nahhal</a>, <a href="/search/eess?searchtype=author&query=Lee%2C+K">Kyesan Lee</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a>, <a href="/search/eess?searchtype=author&query=Shin%2C+H">Hyundong Shin</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2502.17128v1-abstract-short" style="display: inline;"> Integrated sensing and communication (ISAC) technology has been explored as a potential advancement for future wireless networks, striving to effectively use spectral resources for both communication and sensing. The integration of reconfigurable intelligent surfaces (RIS) with ISAC further enhances this capability by optimizing the propagation environment, thereby improving both the sensing accur… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2502.17128v1-abstract-full').style.display = 'inline'; document.getElementById('2502.17128v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2502.17128v1-abstract-full" style="display: none;"> Integrated sensing and communication (ISAC) technology has been explored as a potential advancement for future wireless networks, striving to effectively use spectral resources for both communication and sensing. The integration of reconfigurable intelligent surfaces (RIS) with ISAC further enhances this capability by optimizing the propagation environment, thereby improving both the sensing accuracy and communication quality. Within this domain, accurate channel estimation is crucial to ensure a reliable deployment. Traditional deep learning (DL) approaches, while effective, can impose performance limitations in modeling the complex dynamics of wireless channels. This paper proposes a novel application of conditional generative adversarial networks (CGANs) to solve the channel estimation problem of an RIS-assisted ISAC system. The CGAN framework adversarially trains two DL networks, enabling the generator network to not only learn the mapping relationship from observed data to real channel conditions but also to improve its output based on the discriminator network feedback, thus effectively optimizing the training process and estimation accuracy. The numerical simulations demonstrate that the proposed CGAN-based method improves the estimation performance effectively compared to conventional DL techniques. The results highlight the CGAN's potential to revolutionize channel estimation, paving the way for more accurate and reliable ISAC deployments. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2502.17128v1-abstract-full').style.display = 'none'; document.getElementById('2502.17128v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 24 February, 2025; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> February 2025. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">Accepted for publication in IEEE Transactions on Communications</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2502.03936">arXiv:2502.03936</a> <span> [<a href="https://arxiv.org/pdf/2502.03936">pdf</a>, <a href="https://arxiv.org/format/2502.03936">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> </div> <p class="title is-5 mathjax"> ICGNN: Graph Neural Network Enabled Scalable Beamforming for MISO Interference Channels </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=He%2C+C">Changpeng He</a>, <a href="/search/eess?searchtype=author&query=Lu%2C+Y">Yang Lu</a>, <a href="/search/eess?searchtype=author&query=Ai%2C+B">Bo Ai</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a>, <a href="/search/eess?searchtype=author&query=Ding%2C+Z">Zhiguo Ding</a>, <a href="/search/eess?searchtype=author&query=Niyato%2C+D">Dusit Niyato</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2502.03936v1-abstract-short" style="display: inline;"> This paper investigates the graph neural network (GNN)-enabled beamforming design for interference channels. We propose a model termed interference channel GNN (ICGNN) to solve a quality-of-service constrained energy efficiency maximization problem. The ICGNN is two-stage, where the direction and power parts of beamforming vectors are learned separately but trained jointly via unsupervised learnin… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2502.03936v1-abstract-full').style.display = 'inline'; document.getElementById('2502.03936v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2502.03936v1-abstract-full" style="display: none;"> This paper investigates the graph neural network (GNN)-enabled beamforming design for interference channels. We propose a model termed interference channel GNN (ICGNN) to solve a quality-of-service constrained energy efficiency maximization problem. The ICGNN is two-stage, where the direction and power parts of beamforming vectors are learned separately but trained jointly via unsupervised learning. By formulating the dimensionality of features independent of the transceiver pairs, the ICGNN is scalable with the number of transceiver pairs. Besides, to improve the performance of the ICGNN, the hybrid maximum ratio transmission and zero-forcing scheme reduces the output ports, the feature enhancement module unifies the two types of links into one type, the subgraph representation enhances the message passing efficiency, and the multi-head attention and residual connection facilitate the feature extracting. Furthermore, we present the over-the-air distributed implementation of the ICGNN. Ablation studies validate the effectiveness of key components in the ICGNN. Numerical results also demonstrate the capability of ICGNN in achieving near-optimal performance with an average inference time less than 0.1 ms. The scalability of ICGNN for unseen problem sizes is evaluated and enhanced by transfer learning with limited fine-tuning cost. The results of the centralized and distributed implementations of ICGNN are illustrated. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2502.03936v1-abstract-full').style.display = 'none'; document.getElementById('2502.03936v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 6 February, 2025; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> February 2025. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2501.10753">arXiv:2501.10753</a> <span> [<a href="https://arxiv.org/pdf/2501.10753">pdf</a>, <a href="https://arxiv.org/ps/2501.10753">ps</a>, <a href="https://arxiv.org/format/2501.10753">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Information Theory">cs.IT</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> </div> <p class="title is-5 mathjax"> Pinching Antennas: Principles, Applications and Challenges </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Yang%2C+Z">Zheng Yang</a>, <a href="/search/eess?searchtype=author&query=Wang%2C+N">Ning Wang</a>, <a href="/search/eess?searchtype=author&query=Sun%2C+Y">Yanshi Sun</a>, <a href="/search/eess?searchtype=author&query=Ding%2C+Z">Zhiguo Ding</a>, <a href="/search/eess?searchtype=author&query=Schober%2C+R">Robert Schober</a>, <a href="/search/eess?searchtype=author&query=Karagiannidis%2C+G+K">George K. Karagiannidis</a>, <a href="/search/eess?searchtype=author&query=Wong%2C+V+W+S">Vincent W. S. Wong</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2501.10753v1-abstract-short" style="display: inline;"> Flexible-antenna systems, such as fluid antennas and movable antennas, have been recognized as key enabling technologies for sixth-generation (6G) wireless networks, as they can intelligently reconfigure the effective channel gains of the users and hence significantly improve their data transmission capabilities. However, existing flexible-antenna systems have been designed to combat small-scale f… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2501.10753v1-abstract-full').style.display = 'inline'; document.getElementById('2501.10753v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2501.10753v1-abstract-full" style="display: none;"> Flexible-antenna systems, such as fluid antennas and movable antennas, have been recognized as key enabling technologies for sixth-generation (6G) wireless networks, as they can intelligently reconfigure the effective channel gains of the users and hence significantly improve their data transmission capabilities. However, existing flexible-antenna systems have been designed to combat small-scale fading in non-line-of-sight (NLoS) conditions. As a result, they lack the ability to establish line-of-sight links, which are typically 100 times stronger than NLoS links. In addition, existing flexible-antenna systems have limited flexibility, where adding/removing an antenna is not straightforward. This article introduces an innovative flexible-antenna system called pinching antennas, which are realized by applying small dielectric particles to waveguides. We first describe the basics of pinching-antenna systems and their ability to provide strong LoS links by deploying pinching antennas close to the users as well as their capability to scale up/down the antenna system. We then focus on communication scenarios with different numbers of waveguides and pinching antennas, where innovative approaches to implement multiple-input multiple-output and non-orthogonal multiple access are discussed. In addition, promising 6G-related applications of pinching antennas, including integrated sensing and communication and next-generation multiple access, are presented. Finally, important directions for future research, such as waveguide deployment and channel estimation, are highlighted. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2501.10753v1-abstract-full').style.display = 'none'; document.getElementById('2501.10753v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 18 January, 2025; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> January 2025. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.17990">arXiv:2411.17990</a> <span> [<a href="https://arxiv.org/pdf/2411.17990">pdf</a>, <a href="https://arxiv.org/format/2411.17990">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Information Theory">cs.IT</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> </div> <p class="title is-5 mathjax"> Beam Switching Based Beam Design for High-Speed Train mmWave Communications </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Huang%2C+J">Jingjia Huang</a>, <a href="/search/eess?searchtype=author&query=Qi%2C+C">Chenhao Qi</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a>, <a href="/search/eess?searchtype=author&query=Li%2C+G+Y">Geoffrey Ye Li</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.17990v1-abstract-short" style="display: inline;"> For high-speed train (HST) millimeter wave (mmWave) communications, the use of narrow beams with small beam coverage needs frequent beam switching, while wider beams with small beam gain leads to weaker mmWave signal strength. In this paper, we consider beam switching based beam design, which is formulated as an optimization problem aiming to minimize the number of switched beams within a predeter… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.17990v1-abstract-full').style.display = 'inline'; document.getElementById('2411.17990v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.17990v1-abstract-full" style="display: none;"> For high-speed train (HST) millimeter wave (mmWave) communications, the use of narrow beams with small beam coverage needs frequent beam switching, while wider beams with small beam gain leads to weaker mmWave signal strength. In this paper, we consider beam switching based beam design, which is formulated as an optimization problem aiming to minimize the number of switched beams within a predetermined railway range subject to that the receiving signal-to-noise ratio (RSNR) at the HST is no lower than a predetermined threshold. To solve this problem, we propose two sequential beam design schemes, both including two alternately-performed stages. In the first stage, given an updated beam coverage according to the railway range, we transform the problem into a feasibility problem and further convert it into a min-max optimization problem by relaxing the RSNR constraints into a penalty of the objective function. In the second stage, we evaluate the feasibility of the beamformer obtained from solving the min-max problem and determine the beam coverage accordingly. Simulation results show that compared to the first scheme, the second scheme can achieve 96.20\% reduction in computational complexity at the cost of only 0.0657\% performance degradation. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.17990v1-abstract-full').style.display = 'none'; document.getElementById('2411.17990v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 26 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.02911">arXiv:2411.02911</a> <span> [<a href="https://arxiv.org/pdf/2411.02911">pdf</a>, <a href="https://arxiv.org/format/2411.02911">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Systems and Control">eess.SY</span> </div> </div> <p class="title is-5 mathjax"> Synergizing Hyper-accelerated Power Optimization and Wavelength-Dependent QoT-Aware Cross-Layer Design in Next-Generation Multi-Band EONs </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Arpanaei%2C+F">Farhad Arpanaei</a>, <a href="/search/eess?searchtype=author&query=Zefreh%2C+M+R">Mahdi Ranjbar Zefreh</a>, <a href="/search/eess?searchtype=author&query=Jiang%2C+Y">Yanchao Jiang</a>, <a href="/search/eess?searchtype=author&query=Poggiolini%2C+P">Pierluigi Poggiolini</a>, <a href="/search/eess?searchtype=author&query=Ghodsifar%2C+K">Kimia Ghodsifar</a>, <a href="/search/eess?searchtype=author&query=Beyranvand%2C+H">Hamzeh Beyranvand</a>, <a href="/search/eess?searchtype=author&query=Natalino%2C+C">Carlos Natalino</a>, <a href="/search/eess?searchtype=author&query=Monti%2C+P">Paolo Monti</a>, <a href="/search/eess?searchtype=author&query=Napoli%2C+A">Antonio Napoli</a>, <a href="/search/eess?searchtype=author&query=Rivas-Moscoso%2C+J+M">Jose M. Rivas-Moscoso</a>, <a href="/search/eess?searchtype=author&query=de+Dios%2C+O+G">Oscar Gonzalez de Dios</a>, <a href="/search/eess?searchtype=author&query=Fernandez-Palacios%2C+J+P">Juan P. Fernandez-Palacios</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a>, <a href="/search/eess?searchtype=author&query=Hernandez%2C+J+A">Jose Alberto Hernandez</a>, <a href="/search/eess?searchtype=author&query=Larrabeiti%2C+D">David Larrabeiti</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.02911v1-abstract-short" style="display: inline;"> The extension of elastic optical networks (EON) to multi-band transmission (MB-EON) shows promise in enhancing spectral efficiency, throughput, and long-term cost-effectiveness for telecom operators. However, designing MB-EON networks introduces complex challenges, notably the optimization of physical parameters like optical power and quality of transmission (QoT). Frequency-dependent characterist… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.02911v1-abstract-full').style.display = 'inline'; document.getElementById('2411.02911v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.02911v1-abstract-full" style="display: none;"> The extension of elastic optical networks (EON) to multi-band transmission (MB-EON) shows promise in enhancing spectral efficiency, throughput, and long-term cost-effectiveness for telecom operators. However, designing MB-EON networks introduces complex challenges, notably the optimization of physical parameters like optical power and quality of transmission (QoT). Frequency-dependent characteristics of fiber, such as loss, dispersion, and nonlinear effects, alongside inter-channel stimulated Raman scattering, pose significant hurdles when extending beyond the L+C (LC) band to a continuous spectrum over 100 nm. In this study, we propose a span-by-span methodology for optimal power allocation, introducing two hyper-accelerated power optimization (HPO) strategies: flat launch power (FLP) and flat received power (FRP). These approaches significantly expedite network power optimization while preserving the stability of running services. Our comparative analysis of FLP and FRP models reveals that while FRP has a minimal effect on capacity (increasing less than 10 Tbps for an L+C+S (LCS) system over 100 km), it improves flatness and GSNR/OSNR metrics in the S-band by approximately 2/0 dB and 2.5/6 dB, respectively. A network-wide analysis across various topologies shows that the FRP technique enhances minimum GSNR, contributing to a throughput increase of 12% to 75%, depending on network scale, at a 1% bandwidth blocking rate. Lastly, our application of HPO in MB-EON for both local and global power optimization demonstrates that while both approaches offer comparable performance, global optimization is simpler and more cost-effective for large-scale networks. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.02911v1-abstract-full').style.display = 'none'; document.getElementById('2411.02911v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 5 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2410.13718">arXiv:2410.13718</a> <span> [<a href="https://arxiv.org/pdf/2410.13718">pdf</a>, <a href="https://arxiv.org/ps/2410.13718">ps</a>, <a href="https://arxiv.org/format/2410.13718">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> </div> <p class="title is-5 mathjax"> Maximal Transmission Rate in Omni-DRIS-Assisted Indoor Visible Light Communication Systems </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Ndjiongue%2C+A+R">Alain R. Ndjiongue</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a>, <a href="/search/eess?searchtype=author&query=Shin%2C+H">Hyundong Shin</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2410.13718v1-abstract-short" style="display: inline;"> Given the importance of reconfigurable intelligent surfaces (RISs) in next-generation mobile systems, several RIS variants have been proposed in recent years. Omni-digital-RIS (omni-DRIS) is one of the newly introduced variants of optical RIS that can successfully be driven by bit sequences to control lights emerging from simultaneous reflection and refraction processes, impacting both the achieva… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2410.13718v1-abstract-full').style.display = 'inline'; document.getElementById('2410.13718v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2410.13718v1-abstract-full" style="display: none;"> Given the importance of reconfigurable intelligent surfaces (RISs) in next-generation mobile systems, several RIS variants have been proposed in recent years. Omni-digital-RIS (omni-DRIS) is one of the newly introduced variants of optical RIS that can successfully be driven by bit sequences to control lights emerging from simultaneous reflection and refraction processes, impacting both the achievable rate and the required number of omni-DRIS elements. In this paper, we analyze the effects of omni-DRIS-assisted transmission environment parameters to maximize the achievable rate and highlight the corresponding number of omni-DRIS elements. Furthermore, we show that the number of omni-DRIS elements that yields the highest achievable rate largely depends on the number of bits per omni-DRIS control sequence. On the other hand, this rate is determined by the remaining parameters of the transmission system and environmental factors, which include the total transmit power, transmission bandwidth, number of transmitters and users, and the channel DC gain. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2410.13718v1-abstract-full').style.display = 'none'; document.getElementById('2410.13718v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 17 October, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> October 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2410.11736">arXiv:2410.11736</a> <span> [<a href="https://arxiv.org/pdf/2410.11736">pdf</a>, <a href="https://arxiv.org/format/2410.11736">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Information Theory">cs.IT</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> </div> <p class="title is-5 mathjax"> Near-Field Communications for Extremely Large-Scale MIMO: A Beamspace Perspective </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Chen%2C+K">Kangjian Chen</a>, <a href="/search/eess?searchtype=author&query=Qi%2C+C">Chenhao Qi</a>, <a href="/search/eess?searchtype=author&query=Huang%2C+J">Jingjia Huang</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a>, <a href="/search/eess?searchtype=author&query=Li%2C+G+Y">Geoffrey Ye Li</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2410.11736v1-abstract-short" style="display: inline;"> Extremely large-scale multiple-input multiple-output (XL-MIMO) is regarded as one of the key techniques to enhance the performance of future wireless communications. Different from regular MIMO, the XL-MIMO shifts part of the communication region from the far field to the near field, where the spherical-wave channel model cannot be accurately approximated by the commonly-adopted planar-wave channe… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2410.11736v1-abstract-full').style.display = 'inline'; document.getElementById('2410.11736v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2410.11736v1-abstract-full" style="display: none;"> Extremely large-scale multiple-input multiple-output (XL-MIMO) is regarded as one of the key techniques to enhance the performance of future wireless communications. Different from regular MIMO, the XL-MIMO shifts part of the communication region from the far field to the near field, where the spherical-wave channel model cannot be accurately approximated by the commonly-adopted planar-wave channel model. As a result, the well-explored far-field beamspace is unsuitable for near-field communications, thereby requiring the exploration of specialized near-field beamspace. In this article, we investigate the near-field communications for XL-MIMO from the perspective of beamspace. Given the spherical wavefront characteristics of the near-field channels, we first map the antenna space to the near-field beamspace with the fractional Fourier transform. Then, we divide the near-field beamspace into three parts, including high mainlobe, low mainlobe, and sidelobe, and provide a comprehensive analysis of these components. Based on the analysis, we demonstrate the advantages of the near-field beamspace over the existing methods. Finally, we point out several applications of the near-field beamspace and highlight some potential directions for future study in the near-field beamspace. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2410.11736v1-abstract-full').style.display = 'none'; document.getElementById('2410.11736v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 15 October, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> October 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2409.14702">arXiv:2409.14702</a> <span> [<a href="https://arxiv.org/pdf/2409.14702">pdf</a>, <a href="https://arxiv.org/ps/2409.14702">ps</a>, <a href="https://arxiv.org/format/2409.14702">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Information Theory">cs.IT</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> </div> <p class="title is-5 mathjax"> Rate-Splitting for Cell-Free Massive MIMO: Performance Analysis and Generative AI Approach </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Zheng%2C+J">Jiakang Zheng</a>, <a href="/search/eess?searchtype=author&query=Zhang%2C+J">Jiayi Zhang</a>, <a href="/search/eess?searchtype=author&query=Du%2C+H">Hongyang Du</a>, <a href="/search/eess?searchtype=author&query=Zhang%2C+R">Ruichen Zhang</a>, <a href="/search/eess?searchtype=author&query=Niyato%2C+D">Dusit Niyato</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a>, <a href="/search/eess?searchtype=author&query=Ai%2C+B">Bo Ai</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2409.14702v2-abstract-short" style="display: inline;"> Cell-free (CF) massive multiple-input multipleoutput (MIMO) provides a ubiquitous coverage to user equipments (UEs) but it is also susceptible to interference. Ratesplitting (RS) effectively extracts data by decoding interference, yet its effectiveness is limited by the weakest UE. In this paper, we investigate an RS-based CF massive MIMO system, which combines strengths and mitigates weaknesses o… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2409.14702v2-abstract-full').style.display = 'inline'; document.getElementById('2409.14702v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2409.14702v2-abstract-full" style="display: none;"> Cell-free (CF) massive multiple-input multipleoutput (MIMO) provides a ubiquitous coverage to user equipments (UEs) but it is also susceptible to interference. Ratesplitting (RS) effectively extracts data by decoding interference, yet its effectiveness is limited by the weakest UE. In this paper, we investigate an RS-based CF massive MIMO system, which combines strengths and mitigates weaknesses of both approaches. Considering imperfect channel state information (CSI) resulting from both pilot contamination and noise, we derive a closed-form expression for the sum spectral efficiency (SE) of the RS-based CF massive MIMO system under a spatially correlated Rician channel. Moreover, we propose low-complexity heuristic algorithms based on statistical CSI for power-splitting of common messages and power-control of private messages, and genetic algorithm is adopted as a solution for upper bound performance. Furthermore, we formulate a joint optimization problem, aiming to maximize the sum SE of the RS-based CF massive MIMO system by optimizing the power-splitting factor and power-control coefficient. Importantly, we improve a generative AI (GAI) algorithm to address this complex and nonconvexity problem by using a diffusion model to obtain solutions. Simulation results demonstrate its effectiveness and practicality in mitigating interference, especially in dynamic environments. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2409.14702v2-abstract-full').style.display = 'none'; document.getElementById('2409.14702v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 24 September, 2024; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 23 September, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> September 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">15 pages, 9 figures, Accepted in IEEE Transactions on Communications</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2408.08496">arXiv:2408.08496</a> <span> [<a href="https://arxiv.org/pdf/2408.08496">pdf</a>, <a href="https://arxiv.org/format/2408.08496">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Networking and Internet Architecture">cs.NI</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> </div> <p class="title is-5 mathjax"> Generative AI for Energy Harvesting Internet of Things Network: Fundamental, Applications, and Opportunities </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Xie%2C+W">Wenwen Xie</a>, <a href="/search/eess?searchtype=author&query=Sun%2C+G">Geng Sun</a>, <a href="/search/eess?searchtype=author&query=Li%2C+J">Jiahui Li</a>, <a href="/search/eess?searchtype=author&query=Wang%2C+J">Jiacheng Wang</a>, <a href="/search/eess?searchtype=author&query=Du%2C+H">Hongyang Du</a>, <a href="/search/eess?searchtype=author&query=Niyato%2C+D">Dusit Niyato</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2408.08496v1-abstract-short" style="display: inline;"> Internet of Things (IoT) devices are typically powered by small-sized batteries with limited energy storage capacity, requiring regular replacement or recharging. To reduce costs and maintain connectivity in IoT networks, energy harvesting technologies are regarded as a promising solution. Notably, due to its robust analytical and generative capabilities, generative artificial intelligence (GenAI)… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2408.08496v1-abstract-full').style.display = 'inline'; document.getElementById('2408.08496v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2408.08496v1-abstract-full" style="display: none;"> Internet of Things (IoT) devices are typically powered by small-sized batteries with limited energy storage capacity, requiring regular replacement or recharging. To reduce costs and maintain connectivity in IoT networks, energy harvesting technologies are regarded as a promising solution. Notably, due to its robust analytical and generative capabilities, generative artificial intelligence (GenAI) has demonstrated significant potential in optimizing energy harvesting networks. Therefore, we discuss key applications of GenAI in improving energy harvesting wireless networks for IoT in this article. Specifically, we first review the key technologies of GenAI and the architecture of energy harvesting wireless networks. Then, we show how GenAI can address different problems to improve the performance of the energy harvesting wireless networks. Subsequently, we present a case study of unmanned aerial vehicle (UAV)-enabled data collection and energy transfer. The case study shows distinctively the necessity of energy harvesting technology and verify the effectiveness of GenAI-based methods. Finally, we discuss some important open directions. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2408.08496v1-abstract-full').style.display = 'none'; document.getElementById('2408.08496v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 15 August, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> August 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2407.02184">arXiv:2407.02184</a> <span> [<a href="https://arxiv.org/pdf/2407.02184">pdf</a>, <a href="https://arxiv.org/format/2407.02184">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Networking and Internet Architecture">cs.NI</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> </div> <p class="title is-5 mathjax"> Non-Terrestrial Networks for 6G: Integrated, Intelligent and Ubiquitous Connectivity </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Jamshed%2C+M+A">Muhammad Ali Jamshed</a>, <a href="/search/eess?searchtype=author&query=Kaushik%2C+A">Aryan Kaushik</a>, <a href="/search/eess?searchtype=author&query=Dajer%2C+M">Miguel Dajer</a>, <a href="/search/eess?searchtype=author&query=Guidotti%2C+A">Alessandro Guidotti</a>, <a href="/search/eess?searchtype=author&query=Parzysz%2C+F">Fanny Parzysz</a>, <a href="/search/eess?searchtype=author&query=Lagunas%2C+E">Eva Lagunas</a>, <a href="/search/eess?searchtype=author&query=Di+Renzo%2C+M">Marco Di Renzo</a>, <a href="/search/eess?searchtype=author&query=Chatzinotas%2C+S">Symeon Chatzinotas</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2407.02184v1-abstract-short" style="display: inline;"> Universal connectivity has been part of past and current generations of wireless systems, but as we approach 6G, the subject of social responsibility is being built as a core component. Given the advent of Non-Terrestrial Networks (NTN), reaching these goals will be much closer to realization than ever before. Owing to the benefits of NTN, the integration NTN and Terrestrial Networks (TN) is still… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2407.02184v1-abstract-full').style.display = 'inline'; document.getElementById('2407.02184v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2407.02184v1-abstract-full" style="display: none;"> Universal connectivity has been part of past and current generations of wireless systems, but as we approach 6G, the subject of social responsibility is being built as a core component. Given the advent of Non-Terrestrial Networks (NTN), reaching these goals will be much closer to realization than ever before. Owing to the benefits of NTN, the integration NTN and Terrestrial Networks (TN) is still infancy, where the past, the current and the future releases in the 3$^{\text{rd}}$ Generation Partnership Project (3GPP) provide guidelines to adopt a successfully co-existence/integration of TN and NTN. Therefore, in this article, we have illustrated through 3GPP guidelines, on how NTN and TN can effectively be integrated. Moreover, the role of beamforming and Artificial Intelligence (AI) algorithms is highlighted to achieve this integration. Finally the usefulness of integrating NTN and TN is validated through experimental analysis. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2407.02184v1-abstract-full').style.display = 'none'; document.getElementById('2407.02184v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 2 July, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> July 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">submitted to IEEE Vehicular Technology Magazine</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2406.18391">arXiv:2406.18391</a> <span> [<a href="https://arxiv.org/pdf/2406.18391">pdf</a>, <a href="https://arxiv.org/format/2406.18391">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> </div> <p class="title is-5 mathjax"> CmWave and Sub-THz: Key Radio Enablers and Complementary Spectrum for 6G </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Katwe%2C+M+V">Mayur V. Katwe</a>, <a href="/search/eess?searchtype=author&query=Kaushik%2C+A">Aryan Kaushik</a>, <a href="/search/eess?searchtype=author&query=Singh%2C+K">Keshav Singh</a>, <a href="/search/eess?searchtype=author&query=Di+Renzo%2C+M">Marco Di Renzo</a>, <a href="/search/eess?searchtype=author&query=Sun%2C+S">Shu Sun</a>, <a href="/search/eess?searchtype=author&query=Lee%2C+D">Doohwan Lee</a>, <a href="/search/eess?searchtype=author&query=Armada%2C+A+G">Ana G. Armada</a>, <a href="/search/eess?searchtype=author&query=Eldar%2C+Y+C">Yonina C. Eldar</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a>, <a href="/search/eess?searchtype=author&query=Rappaport%2C+T+S">Theodore S. Rappaport</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2406.18391v1-abstract-short" style="display: inline;"> Sixth-generation (6G) networks are poised to revolutionize communication by exploring alternative spectrum options, aiming to capitalize on strengths while mitigating limitations in current fifth-generation (5G) spectrum. This paper explores the potential opportunities and emerging trends for cmWave and sub-THz spectra as key radio enablers. This paper poses and answers three key questions regardi… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2406.18391v1-abstract-full').style.display = 'inline'; document.getElementById('2406.18391v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2406.18391v1-abstract-full" style="display: none;"> Sixth-generation (6G) networks are poised to revolutionize communication by exploring alternative spectrum options, aiming to capitalize on strengths while mitigating limitations in current fifth-generation (5G) spectrum. This paper explores the potential opportunities and emerging trends for cmWave and sub-THz spectra as key radio enablers. This paper poses and answers three key questions regarding motivation of additional spectrum to explore the strategic implementation and benefits of cmWave and sub-THz spectra. Also, we show using case studies how these complementary spectrum bands will enable new applications in 6G, such as integrated sensing and communication (ISAC), re-configurable intelligent surfaces (RIS) and non-terrestrial networks (NTN). Numerical simulations reveal that the ISAC performance of cmWave and sub-THz spectra outperforms that of existing 5G spectrum, including sub-6 GHz and mmWave. Additionally, we illustrate the effective interplay between RIS and NTN to counteract the effects of high attenuation at sub-THz frequencies. Finally, ongoing standardization endeavors, challenges and promising directions are elucidated for these complementary spectrum bands. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2406.18391v1-abstract-full').style.display = 'none'; document.getElementById('2406.18391v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 26 June, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> June 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2406.09238">arXiv:2406.09238</a> <span> [<a href="https://arxiv.org/pdf/2406.09238">pdf</a>, <a href="https://arxiv.org/format/2406.09238">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Information Theory">cs.IT</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> </div> <p class="title is-5 mathjax"> Near-Field Multiuser Communications based on Sparse Arrays </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Chen%2C+K">Kangjian Chen</a>, <a href="/search/eess?searchtype=author&query=Qi%2C+C">Chenhao Qi</a>, <a href="/search/eess?searchtype=author&query=Li%2C+G+Y">Geoffrey Ye Li</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2406.09238v1-abstract-short" style="display: inline;"> This paper considers near-field multiuser communications based on sparse arrays (SAs). First, for the uniform SAs (USAs), we analyze the beam gains of channel steering vectors, which shows that increasing the antenna spacings can effectively improve the spatial resolution of the antenna arrays to enhance the sum rate of multiuser communications. Then, we investigate nonuniform SAs (NSAs) to mitiga… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2406.09238v1-abstract-full').style.display = 'inline'; document.getElementById('2406.09238v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2406.09238v1-abstract-full" style="display: none;"> This paper considers near-field multiuser communications based on sparse arrays (SAs). First, for the uniform SAs (USAs), we analyze the beam gains of channel steering vectors, which shows that increasing the antenna spacings can effectively improve the spatial resolution of the antenna arrays to enhance the sum rate of multiuser communications. Then, we investigate nonuniform SAs (NSAs) to mitigate the high multiuser interference from the grating lobes of the USAs. To maximize the sum rate of near-field multiuser communications, we optimize the antenna positions of the NSAs, where a successive convex approximation-based antenna position optimization algorithm is proposed. Moreover, we find that the channels of both the USAs and the NSAs show uniform sparsity in the defined surrogate distance-angle (SD-A) domain. Based on the channel sparsity, an on-grid SD-A-domain orthogonal matching pursuit (SDA-OMP) algorithm is developed to estimate multiuser channels. To further improve the resolution of the SDA-OMP, we also design an off-grid SD-A-domain iterative super-resolution channel estimation algorithm. Simulation results demonstrate the superior performance of the proposed methods. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2406.09238v1-abstract-full').style.display = 'none'; document.getElementById('2406.09238v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 13 June, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> June 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2405.03356">arXiv:2405.03356</a> <span> [<a href="https://arxiv.org/pdf/2405.03356">pdf</a>, <a href="https://arxiv.org/format/2405.03356">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Networking and Internet Architecture">cs.NI</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> </div> <p class="title is-5 mathjax"> An Overview of Intelligent Meta-surfaces for 6G and Beyond: Opportunities, Trends, and Challenges </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Katwe%2C+M">Mayur Katwe</a>, <a href="/search/eess?searchtype=author&query=Kaushik%2C+A">Aryan Kaushik</a>, <a href="/search/eess?searchtype=author&query=Mohjazi%2C+L">Lina Mohjazi</a>, <a href="/search/eess?searchtype=author&query=Abualhayja%27a%2C+M">Mohammad Abualhayja'a</a>, <a href="/search/eess?searchtype=author&query=Dardari%2C+D">Davide Dardari</a>, <a href="/search/eess?searchtype=author&query=Singh%2C+K">Keshav Singh</a>, <a href="/search/eess?searchtype=author&query=Imran%2C+M+A">Muhammad Ali Imran</a>, <a href="/search/eess?searchtype=author&query=Butt%2C+M+M">M. Majid Butt</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2405.03356v1-abstract-short" style="display: inline;"> With the impending arrival of the sixth generation (6G) of wireless communication technology, the telecommunications landscape is poised for another revolutionary transformation. At the forefront of this evolution are intelligent meta-surfaces (IS), emerging as a disruptive physical layer technology with the potential to redefine the capabilities and performance metrics of future wireless networks… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2405.03356v1-abstract-full').style.display = 'inline'; document.getElementById('2405.03356v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2405.03356v1-abstract-full" style="display: none;"> With the impending arrival of the sixth generation (6G) of wireless communication technology, the telecommunications landscape is poised for another revolutionary transformation. At the forefront of this evolution are intelligent meta-surfaces (IS), emerging as a disruptive physical layer technology with the potential to redefine the capabilities and performance metrics of future wireless networks. As 6G evolves from concept to reality, industry stakeholders, standards organizations, and regulatory bodies are collaborating to define the specifications, protocols, and interoperability standards governing IS deployment. Against this background, this article delves into the ongoing standardization efforts, emerging trends, potential opportunities, and prevailing challenges surrounding the integration of IS into the framework of 6G and beyond networks. Specifically, it provides a tutorial-style overview of recent advancements in IS and explores their potential applications within future networks beyond 6G. Additionally, the article identifies key challenges in the design and implementation of various types of intelligent surfaces, along with considerations for their practical standardization. Finally, it highlights potential future prospects in this evolving field. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2405.03356v1-abstract-full').style.display = 'none'; document.getElementById('2405.03356v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 6 May, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> May 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2404.16376">arXiv:2404.16376</a> <span> [<a href="https://arxiv.org/pdf/2404.16376">pdf</a>, <a href="https://arxiv.org/ps/2404.16376">ps</a>, <a href="https://arxiv.org/format/2404.16376">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Information Theory">cs.IT</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Multiagent Systems">cs.MA</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Systems and Control">eess.SY</span> </div> </div> <p class="title is-5 mathjax"> A Hypergraph Approach to Distributed Broadcast </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Cao%2C+Q">Qi Cao</a>, <a href="/search/eess?searchtype=author&query=Shao%2C+Y">Yulin Shao</a>, <a href="/search/eess?searchtype=author&query=Yang%2C+F">Fan Yang</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2404.16376v2-abstract-short" style="display: inline;"> This paper explores the distributed broadcast problem within the context of network communications, a critical challenge in decentralized information dissemination. We put forth a novel hypergraph-based approach to address this issue, focusing on minimizing the number of broadcasts to ensure comprehensive data sharing among all network users. The key contributions of this work include the establis… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2404.16376v2-abstract-full').style.display = 'inline'; document.getElementById('2404.16376v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2404.16376v2-abstract-full" style="display: none;"> This paper explores the distributed broadcast problem within the context of network communications, a critical challenge in decentralized information dissemination. We put forth a novel hypergraph-based approach to address this issue, focusing on minimizing the number of broadcasts to ensure comprehensive data sharing among all network users. The key contributions of this work include the establishment of a general lower bound for the problem using the min-cut capacity of hypergraphs, and a distributed broadcast for quasi-trees (DBQT) algorithm tailored for the unique structure of quasi-trees, which is proven to be optimal. This paper advances both network communication strategies and hypergraph theory, with implications for a wide range of real-world applications, from vehicular and sensor networks to distributed storage systems. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2404.16376v2-abstract-full').style.display = 'none'; document.getElementById('2404.16376v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 30 September, 2024; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 25 April, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> April 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2402.10687">arXiv:2402.10687</a> <span> [<a href="https://arxiv.org/pdf/2402.10687">pdf</a>, <a href="https://arxiv.org/format/2402.10687">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Information Theory">cs.IT</span> </div> </div> <p class="title is-5 mathjax"> Beamforming Optimization for Active RIS-Aided Multiuser Communications With Hardware Impairments </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Peng%2C+Z">Zhangjie Peng</a>, <a href="/search/eess?searchtype=author&query=Zhang%2C+Z">Zhibo Zhang</a>, <a href="/search/eess?searchtype=author&query=Pan%2C+C">Cunhua Pan</a>, <a href="/search/eess?searchtype=author&query=Di+Renzo%2C+M">Marco Di Renzo</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a>, <a href="/search/eess?searchtype=author&query=Wang%2C+J">Jiangzhou Wang</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2402.10687v1-abstract-short" style="display: inline;"> In this paper, we consider an active reconfigurable intelligent surface (RIS) to assist the multiuser downlink transmission in the presence of practical hardware impairments (HWIs), including the HWIs at the transceivers and the phase noise at the active RIS. The active RIS is deployed to amplify the incident signals to alleviate the multiplicative fading effect, which is a limitation in the conve… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2402.10687v1-abstract-full').style.display = 'inline'; document.getElementById('2402.10687v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2402.10687v1-abstract-full" style="display: none;"> In this paper, we consider an active reconfigurable intelligent surface (RIS) to assist the multiuser downlink transmission in the presence of practical hardware impairments (HWIs), including the HWIs at the transceivers and the phase noise at the active RIS. The active RIS is deployed to amplify the incident signals to alleviate the multiplicative fading effect, which is a limitation in the conventional passive RIS-aided wireless systems. We aim to maximize the sum rate through jointly designing the transmit beamforming at the base station (BS), the amplification factors and the phase shifts at the active RIS. To tackle this challenging optimization problem effectively, we decouple it into two tractable subproblems. Subsequently, each subproblem is transformed into a second order cone programming problem. The block coordinate descent framework is applied to tackle them, where the transmit beamforming and the reflection coefficients are alternately designed. In addition, another efficient algorithm is presented to reduce the computational complexity. Specifically, by exploiting the majorization-minimization approach, each subproblem is reformulated into a tractable surrogate problem, whose closed-form solutions are obtained by Lagrange dual decomposition approach and element-wise alternating sequential optimization method. Simulation results validate the effectiveness of our developed algorithms, and reveal that the HWIs significantly limit the system performance of active RIS-empowered wireless communications. Furthermore, the active RIS noticeably boosts the sum rate under the same total power budget, compared with the passive RIS. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2402.10687v1-abstract-full').style.display = 'none'; document.getElementById('2402.10687v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 16 February, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> February 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">16 pages, 8 figures, accepted by IEEE Transactions on Wireless Communications</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2402.09441">arXiv:2402.09441</a> <span> [<a href="https://arxiv.org/pdf/2402.09441">pdf</a>, <a href="https://arxiv.org/ps/2402.09441">ps</a>, <a href="https://arxiv.org/format/2402.09441">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1109/TVT.2022.3231727">10.1109/TVT.2022.3231727 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Deep-Learning Channel Estimation for IRS-Assisted Integrated Sensing and Communication System </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Liu%2C+Y">Yu Liu</a>, <a href="/search/eess?searchtype=author&query=Al-Nahhal%2C+I">Ibrahim Al-Nahhal</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a>, <a href="/search/eess?searchtype=author&query=Wang%2C+F">Fanggang Wang</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2402.09441v2-abstract-short" style="display: inline;"> Integrated sensing and communication (ISAC), and intelligent reflecting surface (IRS) are envisioned as revolutionary technologies to enhance spectral and energy efficiencies for next wireless system generations. For the first time, this paper focuses on the channel estimation problem in an IRS-assisted ISAC system. This problem is challenging due to the lack of signal processing capacity in passi… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2402.09441v2-abstract-full').style.display = 'inline'; document.getElementById('2402.09441v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2402.09441v2-abstract-full" style="display: none;"> Integrated sensing and communication (ISAC), and intelligent reflecting surface (IRS) are envisioned as revolutionary technologies to enhance spectral and energy efficiencies for next wireless system generations. For the first time, this paper focuses on the channel estimation problem in an IRS-assisted ISAC system. This problem is challenging due to the lack of signal processing capacity in passive IRS, as well as the presence of mutual interference between sensing and communication (SAC) signals in ISAC systems. A three-stage approach is proposed to decouple the estimation problem into sub-ones, including the estimation of the direct SAC channels in the first stage, reflected communication channel in the second stage, and reflected sensing channel in the third stage. The proposed three-stage approach is based on a deep-learning framework, which involves two different convolutional neural network (CNN) architectures to estimate the channels at the full-duplex ISAC base station. Furthermore, two types of input-output pairs to train the CNNs are carefully designed, which affect the estimation performance under various signal-to-noise ratio conditions and system parameters. Simulation results validate the superiority of the proposed estimation approach compared to the least-squares baseline scheme, and its computational complexity is also analyzed. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2402.09441v2-abstract-full').style.display = 'none'; document.getElementById('2402.09441v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 7 April, 2024; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 29 January, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> February 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> Published in IEEE Transactions on Vehicular Technology, vol. 72, no. 5, pp. 6181-6193, May 2023 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2402.09440">arXiv:2402.09440</a> <span> [<a href="https://arxiv.org/pdf/2402.09440">pdf</a>, <a href="https://arxiv.org/ps/2402.09440">ps</a>, <a href="https://arxiv.org/format/2402.09440">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1109/TCOMM.2023.3308150">10.1109/TCOMM.2023.3308150 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Extreme Learning Machine-based Channel Estimation in IRS-Assisted Multi-User ISAC System </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Liu%2C+Y">Yu Liu</a>, <a href="/search/eess?searchtype=author&query=Al-Nahhal%2C+I">Ibrahim Al-Nahhal</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a>, <a href="/search/eess?searchtype=author&query=Wang%2C+F">Fanggang Wang</a>, <a href="/search/eess?searchtype=author&query=Shin%2C+H">Hyundong Shin</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2402.09440v2-abstract-short" style="display: inline;"> Multi-user integrated sensing and communication (ISAC) assisted by intelligent reflecting surface (IRS) has been recently investigated to provide a high spectral and energy efficiency transmission. This paper proposes a practical channel estimation approach for the first time to an IRS-assisted multiuser ISAC system. The estimation problem in such a system is challenging since the sensing and comm… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2402.09440v2-abstract-full').style.display = 'inline'; document.getElementById('2402.09440v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2402.09440v2-abstract-full" style="display: none;"> Multi-user integrated sensing and communication (ISAC) assisted by intelligent reflecting surface (IRS) has been recently investigated to provide a high spectral and energy efficiency transmission. This paper proposes a practical channel estimation approach for the first time to an IRS-assisted multiuser ISAC system. The estimation problem in such a system is challenging since the sensing and communication (SAC) signals interfere with each other, and the passive IRS lacks signal processing ability. A two-stage approach is proposed to transfer the overall estimation problem into sub-ones, successively including the direct and reflected channels estimation. Based on this scheme, the ISAC base station (BS) estimates all the SAC channels associated with the target and uplink users, while each downlink user estimates the downlink communication channels individually. Considering a low-cost demand of the ISAC BS and downlink users, the proposed two-stage approach is realized by an efficient neural network (NN) framework that contains two different extreme learning machine (ELM) structures to estimate the above SAC channels. Moreover, two types of input-output pairs to train the ELMs are carefully devised, which impact the estimation accuracy and computational complexity under different system parameters. Simulation results reveal a substantial performance improvement achieved by the proposed ELM-based approach over the least-squares and NN-based benchmarks, with reduced training complexity and faster training speed. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2402.09440v2-abstract-full').style.display = 'none'; document.getElementById('2402.09440v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 7 April, 2024; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 29 January, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> February 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> Published in IEEE Transactions on Communications, vol. 71, no. 12, pp. 6993-7007, Dec. 2023 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2402.09439">arXiv:2402.09439</a> <span> [<a href="https://arxiv.org/pdf/2402.09439">pdf</a>, <a href="https://arxiv.org/ps/2402.09439">ps</a>, <a href="https://arxiv.org/format/2402.09439">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1109/GLOBECOM48099.2022.10001672">10.1109/GLOBECOM48099.2022.10001672 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Deep-Learning-Based Channel Estimation for IRS-Assisted ISAC System </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Liu%2C+Y">Yu Liu</a>, <a href="/search/eess?searchtype=author&query=Al-Nahhal%2C+I">Ibrahim Al-Nahhal</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a>, <a href="/search/eess?searchtype=author&query=Wang%2C+F">Fanggang Wang</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2402.09439v2-abstract-short" style="display: inline;"> Integrated sensing and communication (ISAC) and intelligent reflecting surface (IRS) are viewed as promising technologies for future generations of wireless networks. This paper investigates the channel estimation problem in an IRS-assisted ISAC system. A deep-learning framework is proposed to estimate the sensing and communication (S&C) channels in such a system. Considering different propagation… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2402.09439v2-abstract-full').style.display = 'inline'; document.getElementById('2402.09439v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2402.09439v2-abstract-full" style="display: none;"> Integrated sensing and communication (ISAC) and intelligent reflecting surface (IRS) are viewed as promising technologies for future generations of wireless networks. This paper investigates the channel estimation problem in an IRS-assisted ISAC system. A deep-learning framework is proposed to estimate the sensing and communication (S&C) channels in such a system. Considering different propagation environments of the S&C channels, two deep neural network (DNN) architectures are designed to realize this framework. The first DNN is devised at the ISAC base station for estimating the sensing channel, while the second DNN architecture is assigned to each downlink user equipment to estimate its communication channel. Moreover, the input-output pairs to train the DNNs are carefully designed. Simulation results show the superiority of the proposed estimation approach compared to the benchmark scheme under various signal-to-noise ratio conditions and system parameters. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2402.09439v2-abstract-full').style.display = 'none'; document.getElementById('2402.09439v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 7 April, 2024; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 29 January, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> February 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> Published in IEEE Global Communications Conference, Rio de Janeiro, Brazil, Dec. 2022, pp. 4220-4225 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2402.03042">arXiv:2402.03042</a> <span> [<a href="https://arxiv.org/pdf/2402.03042">pdf</a>, <a href="https://arxiv.org/format/2402.03042">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> </div> <p class="title is-5 mathjax"> Semi-Passive Intelligent Reflecting Surface Enabled Sensing Systems </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Peng%2C+Q">Qiaoyan Peng</a>, <a href="/search/eess?searchtype=author&query=Wu%2C+Q">Qingqing Wu</a>, <a href="/search/eess?searchtype=author&query=Chen%2C+W">Wen Chen</a>, <a href="/search/eess?searchtype=author&query=Ma%2C+S">Shaodan Ma</a>, <a href="/search/eess?searchtype=author&query=Zhao%2C+M">Ming-Min Zhao</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2402.03042v1-abstract-short" style="display: inline;"> Intelligent reflecting surface (IRS) has garnered growing interest and attention due to its potential for facilitating and supporting wireless communications and sensing. This paper studies a semi-passive IRS-enabled sensing system, where an IRS consists of both passive reflecting elements and active sensors. Our goal is to minimize the Cram茅r-Rao bound (CRB) for parameter estimation under both po… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2402.03042v1-abstract-full').style.display = 'inline'; document.getElementById('2402.03042v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2402.03042v1-abstract-full" style="display: none;"> Intelligent reflecting surface (IRS) has garnered growing interest and attention due to its potential for facilitating and supporting wireless communications and sensing. This paper studies a semi-passive IRS-enabled sensing system, where an IRS consists of both passive reflecting elements and active sensors. Our goal is to minimize the Cram茅r-Rao bound (CRB) for parameter estimation under both point and extended target cases. Towards this goal, we begin by deriving the CRB for the direction-of-arrival (DoA) estimation in closed-form and then theoretically analyze the IRS reflecting elements and sensors allocation design based on the CRB under the point target case with a single-antenna base station (BS). To efficiently solve the corresponding optimization problem for the case with a multi-antenna BS, we propose an efficient algorithm by jointly optimizing the IRS phase shifts and the BS beamformers. Under the extended target case, the CRB for the target response matrix (TRM) estimation is minimized via the optimization of the BS transmit beamformers. Moreover, we explore the influence of various system parameters on the CRB and compare these effects to those observed under the point target case. Simulation results show the effectiveness of the semi-passive IRS and our proposed beamforming design for improving the performance of the sensing system. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2402.03042v1-abstract-full').style.display = 'none'; document.getElementById('2402.03042v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 5 February, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> February 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2401.11195">arXiv:2401.11195</a> <span> [<a href="https://arxiv.org/pdf/2401.11195">pdf</a>, <a href="https://arxiv.org/format/2401.11195">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Information Theory">cs.IT</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1109/TWC.2024.3351712">10.1109/TWC.2024.3351712 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Triple-Refined Hybrid-Field Beam Training for mmWave Extremely Large-Scale MIMO </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Chen%2C+K">Kangjian Chen</a>, <a href="/search/eess?searchtype=author&query=Qi%2C+C">Chenhao Qi</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a>, <a href="/search/eess?searchtype=author&query=Li%2C+G+Y">Geoffrey Ye Li</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2401.11195v1-abstract-short" style="display: inline;"> This paper investigates beam training for extremely large-scale multiple-input multiple-output systems. By considering both the near field and far field, a triple-refined hybrid-field beam training scheme is proposed, where high-accuracy estimates of channel parameters are obtained through three steps of progressive beam refinement. First, the hybrid-field beam gain (HFBG)-based first refinement m… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2401.11195v1-abstract-full').style.display = 'inline'; document.getElementById('2401.11195v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2401.11195v1-abstract-full" style="display: none;"> This paper investigates beam training for extremely large-scale multiple-input multiple-output systems. By considering both the near field and far field, a triple-refined hybrid-field beam training scheme is proposed, where high-accuracy estimates of channel parameters are obtained through three steps of progressive beam refinement. First, the hybrid-field beam gain (HFBG)-based first refinement method is developed. Based on the analysis of the HFBG, the first-refinement codebook is designed and the beam training is performed accordingly to narrow down the potential region of the channel path. Then, the maximum likelihood (ML)-based and principle of stationary phase (PSP)-based second refinement methods are developed. By exploiting the measurements of the beam training, the ML is used to estimate the channel parameters. To avoid the high computational complexity of ML, closed-form estimates of the channel parameters are derived according to the PSP. Moreover, the Gaussian approximation (GA)-based third refinement method is developed. The hybrid-field neighboring search is first performed to identify the potential region of the main lobe of the channel steering vector. Afterwards, by applying the GA, a least-squares estimator is developed to obtain the high-accuracy channel parameter estimation. Simulation results verify the effectiveness of the proposed scheme. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2401.11195v1-abstract-full').style.display = 'none'; document.getElementById('2401.11195v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 20 January, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> January 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> IEEE Transactions on Wireless Communications, 2024 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2312.16874">arXiv:2312.16874</a> <span> [<a href="https://arxiv.org/pdf/2312.16874">pdf</a>, <a href="https://arxiv.org/format/2312.16874">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Information Theory">cs.IT</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1109/MVT.2024.3415570">10.1109/MVT.2024.3415570 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Reconfigurable Intelligent Surfaces for 6G: Emerging Hardware Architectures, Applications, and Open Challenges </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Basar%2C+E">Ertugrul Basar</a>, <a href="/search/eess?searchtype=author&query=Alexandropoulos%2C+G+C">George C. Alexandropoulos</a>, <a href="/search/eess?searchtype=author&query=Liu%2C+Y">Yuanwei Liu</a>, <a href="/search/eess?searchtype=author&query=Wu%2C+Q">Qingqing Wu</a>, <a href="/search/eess?searchtype=author&query=Jin%2C+S">Shi Jin</a>, <a href="/search/eess?searchtype=author&query=Yuen%2C+C">Chau Yuen</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a>, <a href="/search/eess?searchtype=author&query=Schober%2C+R">Robert Schober</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2312.16874v2-abstract-short" style="display: inline;"> Reconfigurable intelligent surfaces (RISs) are rapidly gaining prominence in the realm of fifth generation (5G)-Advanced, and predominantly, sixth generation (6G) mobile networks, offering a revolutionary approach to optimizing wireless communications. This article delves into the intricate world of the RIS technology, exploring its diverse hardware architectures and the resulting versatile operat… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2312.16874v2-abstract-full').style.display = 'inline'; document.getElementById('2312.16874v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2312.16874v2-abstract-full" style="display: none;"> Reconfigurable intelligent surfaces (RISs) are rapidly gaining prominence in the realm of fifth generation (5G)-Advanced, and predominantly, sixth generation (6G) mobile networks, offering a revolutionary approach to optimizing wireless communications. This article delves into the intricate world of the RIS technology, exploring its diverse hardware architectures and the resulting versatile operating modes. These include RISs with signal reception and processing units, sensors, amplification units, transmissive capability, multiple stacked components, and dynamic metasurface antennas. Furthermore, we shed light on emerging RIS applications, such as index and reflection modulation, non-coherent modulation, next generation multiple access, integrated sensing and communications (ISAC), energy harvesting, as well as aerial and vehicular networks. These exciting applications are set to transform the way we will wirelessly connect in the upcoming era of 6G. Finally, we review recent experimental RIS setups and present various open problems of the overviewed RIS hardware architectures and their applications. From enhancing network coverage to enabling new communication paradigms, RIS-empowered connectivity is poised to play a pivotal role in shaping the future of wireless networking. This article unveils the underlying principles and potential impacts of RISs, focusing on cutting-edge developments of this physical-layer smart connectivity technology. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2312.16874v2-abstract-full').style.display = 'none'; document.getElementById('2312.16874v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 14 June, 2024; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 28 December, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> December 2023. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">18 pages, 15 figures, 54 references, and an extended archival version of an invited and accepted article from IEEE Vehicular Technology Magazine</span> </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> IEEE Vehicular Technology Magazine, 2024 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2312.05884">arXiv:2312.05884</a> <span> [<a href="https://arxiv.org/pdf/2312.05884">pdf</a>, <a href="https://arxiv.org/ps/2312.05884">ps</a>, <a href="https://arxiv.org/format/2312.05884">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Information Theory">cs.IT</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> </div> <p class="title is-5 mathjax"> A General Analytical Framework for the Resolution of Near-Field Beamforming </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Rao%2C+C">Chenguang Rao</a>, <a href="/search/eess?searchtype=author&query=Ding%2C+Z">Zhiguo Ding</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a>, <a href="/search/eess?searchtype=author&query=Dai%2C+X">Xuchu Dai</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2312.05884v1-abstract-short" style="display: inline;"> The resolution is an important performance metric of near-field communication networks. In particular, the resolution of near field beamforming measures how effectively users can be distinguished in the distance-angle domain, which is one of the most significant features of near-field communications. In a comparison, conventional far-field beamforming can distinguish users in the angle domain only… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2312.05884v1-abstract-full').style.display = 'inline'; document.getElementById('2312.05884v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2312.05884v1-abstract-full" style="display: none;"> The resolution is an important performance metric of near-field communication networks. In particular, the resolution of near field beamforming measures how effectively users can be distinguished in the distance-angle domain, which is one of the most significant features of near-field communications. In a comparison, conventional far-field beamforming can distinguish users in the angle domain only, which means that near-field communication yields the full utilization of user spatial resources to improve spectrum efficiency. In the literature of near-field communications, there have been a few studies on whether the resolution of near-field beamforming is perfect. However, each of the existing results suffers its own limitations, e.g., each is accurate for special cases only, and cannot precisely and comprehensively characterize the resolution. In this letter, a general analytical framework is developed to evaluate the resolution of near-field beamforming. Based on this derived expression, the impacts of parameters on the resolution are investigated, which can shed light on the design of the near-field communications, including the designs of beamforming and multiple access tequniques. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2312.05884v1-abstract-full').style.display = 'none'; document.getElementById('2312.05884v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 10 December, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> December 2023. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">This work has been submitted to the IEEE for possible publication</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2312.01071">arXiv:2312.01071</a> <span> [<a href="https://arxiv.org/pdf/2312.01071">pdf</a>, <a href="https://arxiv.org/format/2312.01071">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Information Theory">cs.IT</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> </div> <p class="title is-5 mathjax"> Hybrid Hierarchical DRL Enabled Resource Allocation for Secure Transmission in Multi-IRS-Assisted Sensing-Enhanced Spectrum Sharing Networks </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Wang%2C+L">Lingyi Wang</a>, <a href="/search/eess?searchtype=author&query=Wu%2C+W">Wei Wu</a>, <a href="/search/eess?searchtype=author&query=Zhou%2C+F">Fuhui Zhou</a>, <a href="/search/eess?searchtype=author&query=Wu%2C+Q">Qihui Wu</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a>, <a href="/search/eess?searchtype=author&query=Quek%2C+T+Q+S">Tony Q. S. Quek</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2312.01071v1-abstract-short" style="display: inline;"> Secure communications are of paramount importance in spectrum sharing networks due to the allocation and sharing characteristics of spectrum resources. To further explore the potential of intelligent reflective surfaces (IRSs) in enhancing spectrum sharing and secure transmission performance, a multiple intelligent reflection surface (multi-IRS)-assisted sensing-enhanced wideband spectrum sharing… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2312.01071v1-abstract-full').style.display = 'inline'; document.getElementById('2312.01071v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2312.01071v1-abstract-full" style="display: none;"> Secure communications are of paramount importance in spectrum sharing networks due to the allocation and sharing characteristics of spectrum resources. To further explore the potential of intelligent reflective surfaces (IRSs) in enhancing spectrum sharing and secure transmission performance, a multiple intelligent reflection surface (multi-IRS)-assisted sensing-enhanced wideband spectrum sharing network is investigated by considering physical layer security techniques. An intelligent resource allocation scheme based on double deep Q networks (D3QN) algorithm and soft Actor-Critic (SAC) algorithm is proposed to maximize the secure transmission rate of the secondary network by jointly optimizing IRS pairings, subchannel assignment, transmit beamforming of the secondary base station, reflection coefficients of IRSs and the sensing time. To tackle the sparse reward problem caused by a significant amount of reflection elements of multiple IRSs, the method of hierarchical reinforcement learning is exploited. An alternative optimization (AO)-based conventional mathematical scheme is introduced to verify the computational complexity advantage of our proposed intelligent scheme. Simulation results demonstrate the efficiency of our proposed intelligent scheme as well as the superiority of multi-IRS design in enhancing secrecy rate and spectrum utilization. It is shown that inappropriate deployment of IRSs can reduce the security performance with the presence of multiple eavesdroppers (Eves), and the arrangement of IRSs deserves further consideration. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2312.01071v1-abstract-full').style.display = 'none'; document.getElementById('2312.01071v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 2 December, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> December 2023. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2311.15062">arXiv:2311.15062</a> <span> [<a href="https://arxiv.org/pdf/2311.15062">pdf</a>, <a href="https://arxiv.org/format/2311.15062">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Information Theory">cs.IT</span> </div> </div> <p class="title is-5 mathjax"> Simultaneous Beam Training and Target Sensing in ISAC Systems with RIS </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Chen%2C+K">Kangjian Chen</a>, <a href="/search/eess?searchtype=author&query=Qi%2C+C">Chenhao Qi</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a>, <a href="/search/eess?searchtype=author&query=Li%2C+G+Y">Geoffrey Ye Li</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2311.15062v1-abstract-short" style="display: inline;"> This paper investigates an integrated sensing and communication (ISAC) system with reconfigurable intelligent surface (RIS). Our simultaneous beam training and target sensing (SBTTS) scheme enables the base station to perform beam training with the user terminals (UTs) and the RIS, and simultaneously to sense the targets. Based on our findings, the energy of the echoes from the RIS is accumulated… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2311.15062v1-abstract-full').style.display = 'inline'; document.getElementById('2311.15062v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2311.15062v1-abstract-full" style="display: none;"> This paper investigates an integrated sensing and communication (ISAC) system with reconfigurable intelligent surface (RIS). Our simultaneous beam training and target sensing (SBTTS) scheme enables the base station to perform beam training with the user terminals (UTs) and the RIS, and simultaneously to sense the targets. Based on our findings, the energy of the echoes from the RIS is accumulated in the angle-delay domain while that from the targets is accumulated in the Doppler-delay domain. The SBTTS scheme can distinguish the RIS from the targets with the mixed echoes from the RIS and the targets. Then we propose a positioning and array orientation estimation (PAOE) scheme for both the line-of-sight channels and the non-line-of-sight channels based on the beam training results of SBTTS by developing a low-complexity two-dimensional fast search algorithm. Based on the SBTTS and PAOE schemes, we further compute the angle-of-arrival and angle-of-departure for the channels between the RIS and the UTs by exploiting the geometry relationship to accomplish the beam alignment of the ISAC system. Simulation results verify the effectiveness of the proposed schemes. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2311.15062v1-abstract-full').style.display = 'none'; document.getElementById('2311.15062v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 25 November, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2023. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2311.03659">arXiv:2311.03659</a> <span> [<a href="https://arxiv.org/pdf/2311.03659">pdf</a>, <a href="https://arxiv.org/format/2311.03659">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Systems and Control">eess.SY</span> </div> </div> <p class="title is-5 mathjax"> GNN-Based Beamforming for Sum-Rate Maximization in MU-MISO Networks </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Li%2C+Y">Yuhang Li</a>, <a href="/search/eess?searchtype=author&query=Lu%2C+Y">Yang Lu</a>, <a href="/search/eess?searchtype=author&query=Ai%2C+B">Bo Ai</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a>, <a href="/search/eess?searchtype=author&query=Ding%2C+Z">Zhiguo Ding</a>, <a href="/search/eess?searchtype=author&query=Niyato%2C+D">Dusit Niyato</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2311.03659v1-abstract-short" style="display: inline;"> The advantages of graph neural networks (GNNs) in leveraging the graph topology of wireless networks have drawn increasing attentions. This paper studies the GNN-based learning approach for the sum-rate maximization in multiple-user multiple-input single-output (MU-MISO) networks subject to the users' individual data rate requirements and the power budget of the base station. By modeling the MU-MI… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2311.03659v1-abstract-full').style.display = 'inline'; document.getElementById('2311.03659v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2311.03659v1-abstract-full" style="display: none;"> The advantages of graph neural networks (GNNs) in leveraging the graph topology of wireless networks have drawn increasing attentions. This paper studies the GNN-based learning approach for the sum-rate maximization in multiple-user multiple-input single-output (MU-MISO) networks subject to the users' individual data rate requirements and the power budget of the base station. By modeling the MU-MISO network as a graph, a GNN-based architecture named CRGAT is proposed to directly map the channel state information to the beamforming vectors. The attention-enabled aggregation and the residual-assisted combination are adopted to enhance the learning capability and avoid the oversmoothing issue. Furthermore, a novel activation function is proposed for the constraint due to the limited power budget at the base station. The CRGAT is trained in an unsupervised learning manner with two proposed loss functions. An evaluation method is proposed for the learning-based approach, based on which the effectiveness of the proposed CRGAT is validated in comparison with several convex optimization and learning based approaches. Numerical results are provided to reveal the advantages of the CRGAT including the millisecond-level response with limited optimality performance loss, the scalability to different number of users and power budgets, and the adaptability to different system settings. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2311.03659v1-abstract-full').style.display = 'none'; document.getElementById('2311.03659v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 6 November, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2023. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2308.09803">arXiv:2308.09803</a> <span> [<a href="https://arxiv.org/pdf/2308.09803">pdf</a>, <a href="https://arxiv.org/format/2308.09803">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> </div> <p class="title is-5 mathjax"> Liquid Crystal-Based RIS for VLC Transmitters: Performance Analysis, Challenges, and Opportunities </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Aboagye%2C+S">Sylvester Aboagye</a>, <a href="/search/eess?searchtype=author&query=Ngatched%2C+T+M+N">Telex M. N. Ngatched</a>, <a href="/search/eess?searchtype=author&query=Ndjiongue%2C+A+R">Alain R. Ndjiongue</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a>, <a href="/search/eess?searchtype=author&query=Shin%2C+H">Hyundong Shin</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2308.09803v1-abstract-short" style="display: inline;"> This article presents a novel approach of using reconfigurable intelligent surfaces (RISs) in the transmitter of indoor visible light communication (VLC) systems to enhance data rate uniformity and maintain adequate illumination. In this approach, a liquid crystal (LC)-based RIS is placed in front of the LED arrays of the transmitter to form an LC-based RIS-enabled VLC transmitter. This RIS-enable… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2308.09803v1-abstract-full').style.display = 'inline'; document.getElementById('2308.09803v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2308.09803v1-abstract-full" style="display: none;"> This article presents a novel approach of using reconfigurable intelligent surfaces (RISs) in the transmitter of indoor visible light communication (VLC) systems to enhance data rate uniformity and maintain adequate illumination. In this approach, a liquid crystal (LC)-based RIS is placed in front of the LED arrays of the transmitter to form an LC-based RIS-enabled VLC transmitter. This RIS-enabled transmitter is able to perform new functions such as transmit light steering and amplification and demonstrates very high data rate and illumination performance when compared with traditional VLC transmitters with circular and distributed LED arrays and the more recent angle diversity transmitter. Simulation results reveal the strong potential of LC-based RIS-aided transmitters in satisfying the joint illumination and communication needs of indoor VLC systems and positions VLC as a critical essential block for next generation communication networks. Several challenging and exciting issues related to the realization of such transmitters are discussed. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2308.09803v1-abstract-full').style.display = 'none'; document.getElementById('2308.09803v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 18 August, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> August 2023. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">This paper has been accepted for publication in IEEE</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2308.05813">arXiv:2308.05813</a> <span> [<a href="https://arxiv.org/pdf/2308.05813">pdf</a>, <a href="https://arxiv.org/format/2308.05813">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1109/JIOT.2023.3296319">10.1109/JIOT.2023.3296319 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Physical Layer Security for NOMA Systems: Requirements, Issues, and Recommendations </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Pakravan%2C+S">Saeid Pakravan</a>, <a href="/search/eess?searchtype=author&query=Chouinard%2C+J">Jean-Yves Chouinard</a>, <a href="/search/eess?searchtype=author&query=Li%2C+X">Xingwang Li</a>, <a href="/search/eess?searchtype=author&query=Zeng%2C+M">Ming Zeng</a>, <a href="/search/eess?searchtype=author&query=Hao%2C+W">Wanming Hao</a>, <a href="/search/eess?searchtype=author&query=Pham%2C+Q">Quoc-Viet Pham</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2308.05813v1-abstract-short" style="display: inline;"> Non-orthogonal multiple access (NOMA) has been viewed as a potential candidate for the upcoming generation of wireless communication systems. Comparing to traditional orthogonal multiple access (OMA), multiplexing users in the same time-frequency resource block can increase the number of served users and improve the efficiency of the systems in terms of spectral efficiency. Nevertheless, from a se… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2308.05813v1-abstract-full').style.display = 'inline'; document.getElementById('2308.05813v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2308.05813v1-abstract-full" style="display: none;"> Non-orthogonal multiple access (NOMA) has been viewed as a potential candidate for the upcoming generation of wireless communication systems. Comparing to traditional orthogonal multiple access (OMA), multiplexing users in the same time-frequency resource block can increase the number of served users and improve the efficiency of the systems in terms of spectral efficiency. Nevertheless, from a security view-point, when multiple users are utilizing the same time-frequency resource, there may be concerns regarding keeping information confidential. In this context, physical layer security (PLS) has been introduced as a supplement of protection to conventional encryption techniques by making use of the random nature of wireless transmission media for ensuring communication secrecy. The recent years have seen significant interests in PLS being applied to NOMA networks. Numerous scenarios have been investigated to assess the security of NOMA systems, including when active and passive eavesdroppers are present, as well as when these systems are combined with relay and reconfigurable intelligent surfaces (RIS). Additionally, the security of the ambient backscatter (AmB)-NOMA systems are other issues that have lately drawn a lot of attention. In this paper, a thorough analysis of the PLS-assisted NOMA systems research state-of-the-art is presented. In this regard, we begin by outlining the foundations of NOMA and PLS, respectively. Following that, we discuss the PLS performances for NOMA systems in four categories depending on the type of the eavesdropper, the existence of relay, RIS, and AmB systems in different conditions. Finally, a thorough explanation of the most recent PLS-assisted NOMA systems is given. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2308.05813v1-abstract-full').style.display = 'none'; document.getElementById('2308.05813v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 10 August, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> August 2023. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">17 pages, 4 figures</span> </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> IEEE Internet of Things Journal </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2306.06587">arXiv:2306.06587</a> <span> [<a href="https://arxiv.org/pdf/2306.06587">pdf</a>, <a href="https://arxiv.org/ps/2306.06587">ps</a>, <a href="https://arxiv.org/format/2306.06587">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Information Theory">cs.IT</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> </div> <p class="title is-5 mathjax"> Intelligent Reflecting Surface Assisted Multi-Cluster AirComp via Dynamic Beamforming </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Zhao%2C+Y">Yapeng Zhao</a>, <a href="/search/eess?searchtype=author&query=Wu%2C+Q">Qingqing Wu</a>, <a href="/search/eess?searchtype=author&query=Chen%2C+W">Wen Chen</a>, <a href="/search/eess?searchtype=author&query=Wu%2C+C">Celimuge Wu</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2306.06587v3-abstract-short" style="display: inline;"> This paper studies an multi-cluster over-the-air computation (AirComp) system, where an intelligent reflecting surface (IRS) assists the signal transmission from devices to an access point (AP). The clusters are activated to compute heterogeneous functions in a time-division manner. Specifically, two types of IRS beamforming (BF) schemes are proposed to reveal the performancecost tradeoff. One is… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2306.06587v3-abstract-full').style.display = 'inline'; document.getElementById('2306.06587v3-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2306.06587v3-abstract-full" style="display: none;"> This paper studies an multi-cluster over-the-air computation (AirComp) system, where an intelligent reflecting surface (IRS) assists the signal transmission from devices to an access point (AP). The clusters are activated to compute heterogeneous functions in a time-division manner. Specifically, two types of IRS beamforming (BF) schemes are proposed to reveal the performancecost tradeoff. One is the cluster-adaptive BF scheme, where each BF pattern is dedicated to one cluster, and the other is the dynamic BF scheme, which is applied to any number of IRS BF patterns. By deeply exploiting their inherent properties, both generic and lowcomplexity algorithms are proposed in which the IRS BF patterns, time and power resource allocation are jointly optimized. Numerical results show that IRS can significantly enhance the function computation performance, and demonstrate that the dynamic IRS BF scheme with half of the total IRS BF patterns can achieve near-optimal performance which can be deemed as a cost-efficient approach for IRS-aided multi-cluster AirComp systems. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2306.06587v3-abstract-full').style.display = 'none'; document.getElementById('2306.06587v3-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 15 July, 2023; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 11 June, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> June 2023. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2301.11066">arXiv:2301.11066</a> <span> [<a href="https://arxiv.org/pdf/2301.11066">pdf</a>, <a href="https://arxiv.org/format/2301.11066">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Information Theory">cs.IT</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> </div> <p class="title is-5 mathjax"> Channel Estimation for RIS-aided mmWave Massive MIMO System Using Few-bit ADCs </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Wang%2C+R">Ruizhe Wang</a>, <a href="/search/eess?searchtype=author&query=Ren%2C+H">Hong Ren</a>, <a href="/search/eess?searchtype=author&query=Pan%2C+C">Cunhua Pan</a>, <a href="/search/eess?searchtype=author&query=Fang%2C+J">Jun Fang</a>, <a href="/search/eess?searchtype=author&query=Dong%2C+M">Mianxiong Dong</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2301.11066v1-abstract-short" style="display: inline;"> Millimeter wave (mmWave) massive multiple-input multiple-output (massive MIMO) is one of the most promising technologies for the fifth generation and beyond wireless communication system. However, a large number of antennas incur high power consumption and hardware costs, and high-frequency communications place a heavy burden on the analog-to-digital converters (ADCs) at the base station (BS). Fur… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2301.11066v1-abstract-full').style.display = 'inline'; document.getElementById('2301.11066v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2301.11066v1-abstract-full" style="display: none;"> Millimeter wave (mmWave) massive multiple-input multiple-output (massive MIMO) is one of the most promising technologies for the fifth generation and beyond wireless communication system. However, a large number of antennas incur high power consumption and hardware costs, and high-frequency communications place a heavy burden on the analog-to-digital converters (ADCs) at the base station (BS). Furthermore, it is too costly to equipping each antenna with a high-precision ADC in a large antenna array system. It is promising to adopt low-resolution ADCs to address this problem. In this paper, we investigate the cascaded channel estimation for a mmWave massive MIMO system aided by a reconfigurable intelligent surface (RIS) with the BS equipped with few-bit ADCs. Due to the low-rank property of the cascaded channel, the estimation of the cascaded channel can be formulated as a low-rank matrix completion problem. We introduce a Bayesian optimal estimation framework for estimating the user-RIS-BS cascaded channel to tackle with the information loss caused by quantization. To implement the estimator and achieve the matrix completion, we use efficient bilinear generalized approximate message passing (BiG-AMP) algorithm. Extensive simulation results verify that our proposed method can accurately estimate the cascaded channel for the RIS-aided mmWave massive MIMO system with low-resolution ADCs. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2301.11066v1-abstract-full').style.display = 'none'; document.getElementById('2301.11066v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 26 January, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> January 2023. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2301.06549">arXiv:2301.06549</a> <span> [<a href="https://arxiv.org/pdf/2301.06549">pdf</a>, <a href="https://arxiv.org/format/2301.06549">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Information Theory">cs.IT</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> </div> <p class="title is-5 mathjax"> A Deep Learning & Fast Wavelet Transform-based Hybrid Approach for Denoising of PPG Signals </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Ahmed%2C+R">Rabia Ahmed</a>, <a href="/search/eess?searchtype=author&query=Mehmood%2C+A">Ahsan Mehmood</a>, <a href="/search/eess?searchtype=author&query=Rahman%2C+M+M+U">Muhammad Mahboob Ur Rahman</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2301.06549v1-abstract-short" style="display: inline;"> This letter presents a novel hybrid method that leverages deep learning to exploit the multi-resolution analysis capability of the wavelets, in order to denoise a photoplethysmography (PPG) signal. Under the proposed method, a noisy PPG sequence of length N is first decomposed into L detailed coefficients using the fast wavelet transform (FWT). Then, the clean PPG sequence is reconstructed as foll… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2301.06549v1-abstract-full').style.display = 'inline'; document.getElementById('2301.06549v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2301.06549v1-abstract-full" style="display: none;"> This letter presents a novel hybrid method that leverages deep learning to exploit the multi-resolution analysis capability of the wavelets, in order to denoise a photoplethysmography (PPG) signal. Under the proposed method, a noisy PPG sequence of length N is first decomposed into L detailed coefficients using the fast wavelet transform (FWT). Then, the clean PPG sequence is reconstructed as follows. A custom feedforward neural network (FFNN) provides the binary weights for each of the wavelet sub-signals outputted by the inverse-FWT block. This way, all those sub-signals which correspond to noise or artefacts are discarded during reconstruction. The FFNN is trained on the Beth Israel Deaconess Medical Center (BIDMC) dataset under the supervised learning framework, whereby we compute the mean squared-error (MSE) between the denoised sequence and the reference clean PPG signal, and compute the gradient of the MSE for the back-propagation. Numerical results show that the proposed method effectively denoises the corrupted PPG and video-PPG signal. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2301.06549v1-abstract-full').style.display = 'none'; document.getElementById('2301.06549v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 16 January, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> January 2023. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">4 pages, 8 figures</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2211.12891">arXiv:2211.12891</a> <span> [<a href="https://arxiv.org/pdf/2211.12891">pdf</a>, <a href="https://arxiv.org/ps/2211.12891">ps</a>, <a href="https://arxiv.org/format/2211.12891">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Information Theory">cs.IT</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> </div> <p class="title is-5 mathjax"> Integrated Sensing and Communication: Joint Pilot and Transmission Design </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Hua%2C+M">Meng Hua</a>, <a href="/search/eess?searchtype=author&query=Wu%2C+Q">Qingqing Wu</a>, <a href="/search/eess?searchtype=author&query=Chen%2C+W">Wen Chen</a>, <a href="/search/eess?searchtype=author&query=Jamalipour%2C+A">Abbas Jamalipour</a>, <a href="/search/eess?searchtype=author&query=Wu%2C+C">Celimuge Wu</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2211.12891v3-abstract-short" style="display: inline;"> This paper studies a communication-centric integrated sensing and communication (ISAC) system, where a multi-antenna base station (BS) simultaneously performs downlink communication and target detection. A novel target detection and information transmission protocol is proposed, where the BS executes the channel estimation and beamforming successively and meanwhile jointly exploits the pilot seque… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2211.12891v3-abstract-full').style.display = 'inline'; document.getElementById('2211.12891v3-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2211.12891v3-abstract-full" style="display: none;"> This paper studies a communication-centric integrated sensing and communication (ISAC) system, where a multi-antenna base station (BS) simultaneously performs downlink communication and target detection. A novel target detection and information transmission protocol is proposed, where the BS executes the channel estimation and beamforming successively and meanwhile jointly exploits the pilot sequences in the channel estimation stage and user information in the transmission stage to assist target detection. We investigate the joint design of pilot matrix, training duration, and transmit beamforming to maximize the probability of target detection, subject to the minimum achievable rate required by the user. However, designing the optimal pilot matrix is rather challenging since there is no closed-form expression of the detection probability with respect to the pilot matrix. To tackle this difficulty, we resort to designing the pilot matrix based on the information-theoretic criterion to maximize the mutual information (MI) between the received observations and BS-target channel coefficients for target detection. We first derive the optimal pilot matrix for both channel estimation and target detection, and then propose an unified pilot matrix structure to balance minimizing the channel estimation error (MSE) and maximizing MI. Based on the proposed structure, a low-complexity successive refinement algorithm is proposed. Simulation results demonstrate that the proposed pilot matrix structure can well balance the MSE-MI and the Rate-MI tradeoffs, and show the significant region improvement of our proposed design as compared to other benchmark schemes. Furthermore, it is unveiled that as the communication channel is more correlated, the Rate-MI region can be further enlarged. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2211.12891v3-abstract-full').style.display = 'none'; document.getElementById('2211.12891v3-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 20 February, 2024; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 23 November, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2022. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">This papar answers the optimal space code-time design for supporting ISAC</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2208.07424">arXiv:2208.07424</a> <span> [<a href="https://arxiv.org/pdf/2208.07424">pdf</a>, <a href="https://arxiv.org/ps/2208.07424">ps</a>, <a href="https://arxiv.org/format/2208.07424">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1109/LCOMM.2022.3170061">10.1109/LCOMM.2022.3170061 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Deep Reinforcement Learning for RIS-Assisted FD Systems: Single or Distributed RIS? </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Faisal%2C+A">Alice Faisal</a>, <a href="/search/eess?searchtype=author&query=Al-Nahhal%2C+I">Ibrahim Al-Nahhal</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a>, <a href="/search/eess?searchtype=author&query=Ngatched%2C+T+M+N">Telex M. N. Ngatched</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2208.07424v1-abstract-short" style="display: inline;"> This paper investigates reconfigurable intelligent surface (RIS)-assisted full-duplex multiple-input single-output wireless system, where the beamforming and RIS phase shifts are optimized to maximize the sum-rate for both single and distributed RIS deployment schemes. The preference of using the single or distributed RIS deployment scheme is investigated through three practical scenarios based on… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2208.07424v1-abstract-full').style.display = 'inline'; document.getElementById('2208.07424v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2208.07424v1-abstract-full" style="display: none;"> This paper investigates reconfigurable intelligent surface (RIS)-assisted full-duplex multiple-input single-output wireless system, where the beamforming and RIS phase shifts are optimized to maximize the sum-rate for both single and distributed RIS deployment schemes. The preference of using the single or distributed RIS deployment scheme is investigated through three practical scenarios based on the links' quality. The closed-form solution is derived to optimize the beamforming vectors and a novel deep reinforcement learning (DRL) algorithm is proposed to optimize the RIS phase shifts. Simulation results illustrate that the choice of the deployment scheme depends on the scenario and the links' quality. It is further shown that the proposed algorithm significantly improves the sum-rate compared to the non-optimized scenario in both single and distributed RIS deployment schemes. Besides, the proposed beamforming derivation achieves a remarkable improvement compared to the approximated derivation in previous works. Finally, the complexity analysis confirms that the proposed DRL algorithm reduces the computation complexity compared to the DRL algorithm in the literature. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2208.07424v1-abstract-full').style.display = 'none'; document.getElementById('2208.07424v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 15 August, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> August 2022. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">arXiv admin note: text overlap with arXiv:2110.04859</span> </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> IEEE Communications Letters, 2022 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2208.03705">arXiv:2208.03705</a> <span> [<a href="https://arxiv.org/pdf/2208.03705">pdf</a>, <a href="https://arxiv.org/format/2208.03705">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Information Theory">cs.IT</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> </div> <p class="title is-5 mathjax"> Rate Splitting Multiple Access for Next Generation Cognitive Radio Enabled LEO Satellite Networks </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Khan%2C+a+U">ali Ullah Khan</a>, <a href="/search/eess?searchtype=author&query=Ali%2C+Z">Zain Ali</a>, <a href="/search/eess?searchtype=author&query=Lagunas%2C+E">Eva Lagunas</a>, <a href="/search/eess?searchtype=author&query=Mahmood%2C+A">Asad Mahmood</a>, <a href="/search/eess?searchtype=author&query=Asif%2C+M">Muhammad Asif</a>, <a href="/search/eess?searchtype=author&query=Ihsan%2C+A">Asim Ihsan</a>, <a href="/search/eess?searchtype=author&query=Chatzinotas%2C+S">Symeon Chatzinotas</a>, <a href="/search/eess?searchtype=author&query=Ottersten%2C+B">Bj枚rn Ottersten</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2208.03705v2-abstract-short" style="display: inline;"> This paper proposes a cognitive radio enabled LEO SatCom using RSMA radio access technique with the coexistence of GEO SatCom network. In particular, this work aims to maximize the sum rate of LEO SatCom by simultaneously optimizing the power budget over different beams, RSMA power allocation for users over each beam, and subcarrier user assignment while restricting the interference temperature to… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2208.03705v2-abstract-full').style.display = 'inline'; document.getElementById('2208.03705v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2208.03705v2-abstract-full" style="display: none;"> This paper proposes a cognitive radio enabled LEO SatCom using RSMA radio access technique with the coexistence of GEO SatCom network. In particular, this work aims to maximize the sum rate of LEO SatCom by simultaneously optimizing the power budget over different beams, RSMA power allocation for users over each beam, and subcarrier user assignment while restricting the interference temperature to GEO SatCom. The problem of sum rate maximization is formulated as non-convex, where the global optimal solution is challenging to obtain. Thus, an efficient solution can be obtained in three steps: first we employ a successive convex approximation technique to reduce the complexity and make the problem more tractable. Second, for any given resource block user assignment, we adopt KKT conditions to calculate the transmit power over different beams and RSMA power allocation of users over each beam. Third, using the allocated power, we design an efficient algorithm based on the greedy approach for resource block user assignment. Numerical results demonstrate the benefits of the proposed optimization scheme compared to the benchmark schemes. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2208.03705v2-abstract-full').style.display = 'none'; document.getElementById('2208.03705v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 6 February, 2023; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 7 August, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> August 2022. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">32,9. arXiv admin note: substantial text overlap with arXiv:2208.02924</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2207.09095">arXiv:2207.09095</a> <span> [<a href="https://arxiv.org/pdf/2207.09095">pdf</a>, <a href="https://arxiv.org/ps/2207.09095">ps</a>, <a href="https://arxiv.org/format/2207.09095">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Information Theory">cs.IT</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> </div> <p class="title is-5 mathjax"> Secure Intelligent Reflecting Surface Aided Integrated Sensing and Communication </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Hua%2C+M">Meng Hua</a>, <a href="/search/eess?searchtype=author&query=Wu%2C+Q">Qingqing Wu</a>, <a href="/search/eess?searchtype=author&query=Chen%2C+W">Wen Chen</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a>, <a href="/search/eess?searchtype=author&query=Swindlehurst%2C+A+L">A. Lee Swindlehurst</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2207.09095v1-abstract-short" style="display: inline;"> In this paper, an intelligent reflecting surface (IRS) is leveraged to enhance the physical layer security of an integrated sensing and communication (ISAC) system in which the IRS is deployed to not only assist the downlink communication for multiple users, but also create a virtual line-of-sight (LoS) link for target sensing. In particular, we consider a challenging scenario where the target may… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2207.09095v1-abstract-full').style.display = 'inline'; document.getElementById('2207.09095v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2207.09095v1-abstract-full" style="display: none;"> In this paper, an intelligent reflecting surface (IRS) is leveraged to enhance the physical layer security of an integrated sensing and communication (ISAC) system in which the IRS is deployed to not only assist the downlink communication for multiple users, but also create a virtual line-of-sight (LoS) link for target sensing. In particular, we consider a challenging scenario where the target may be a suspicious eavesdropper that potentially intercepts the communication-user information transmitted by the base station (BS). We investigate the joint design of the phase shifts at the IRS and the communication as well as radar beamformers at the BS to maximize the sensing beampattern gain towards the target, subject to the maximum information leakage to the eavesdropping target and the minimum signal-to-interference-plus-noise ratio (SINR) required by users. Based on the availability of perfect channel state information (CSI) of all involved user links and the accurate target location at the BS, two scenarios are considered and two different optimization algorithms are proposed. For the ideal scenario where the CSI of the user links and the target location are perfectly known at the BS, a penalty-based algorithm is proposed to obtain a high-quality solution. In particular, the beamformers are obtained with a semi-closed-form solution using Lagrange duality and the IRS phase shifts are solved for in closed form by applying the majorization-minimization (MM) method. On the other hand, for the more practical scenario where the CSI is imperfect and the target location is uncertain, a robust algorithm based on the $\cal S$-procedure and sign-definiteness approaches is proposed. Simulation results demonstrate the effectiveness of the proposed scheme in achieving a trade-off between the communication quality and the sensing quality. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2207.09095v1-abstract-full').style.display = 'none'; document.getElementById('2207.09095v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 19 July, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> July 2022. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">This paper has been submitted to IEEE journal for possible publication</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2206.01567">arXiv:2206.01567</a> <span> [<a href="https://arxiv.org/pdf/2206.01567">pdf</a>, <a href="https://arxiv.org/ps/2206.01567">ps</a>, <a href="https://arxiv.org/format/2206.01567">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Information Theory">cs.IT</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> </div> <p class="title is-5 mathjax"> Energy-Efficient Resource Allocation for Aggregated RF/VLC Systems </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Aboagye%2C+S">Sylvester Aboagye</a>, <a href="/search/eess?searchtype=author&query=Ngatched%2C+T+M+N">Telex M. N. Ngatched</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a>, <a href="/search/eess?searchtype=author&query=Poor%2C+H+V">H. Vincent Poor</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2206.01567v1-abstract-short" style="display: inline;"> Visible light communication (VLC) is envisioned as a core component of future wireless communication networks due to, among others, the huge unlicensed bandwidth it offers and the fact that it does not cause any interference to existing radio frequency (RF) communication systems. Most research on RF and VLC coexistence has focused on hybrid designs where data transmission to any user could origina… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2206.01567v1-abstract-full').style.display = 'inline'; document.getElementById('2206.01567v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2206.01567v1-abstract-full" style="display: none;"> Visible light communication (VLC) is envisioned as a core component of future wireless communication networks due to, among others, the huge unlicensed bandwidth it offers and the fact that it does not cause any interference to existing radio frequency (RF) communication systems. Most research on RF and VLC coexistence has focused on hybrid designs where data transmission to any user could originate from either an RF or a VLC access point (AP). However, hybrid RF/VLC systems fail to exploit the distinct transmission characteristics of RF and VLC systems to fully reap the benefits they can offer. Aggregated RF/VLC systems, in which any user can be served simultaneously by both RF and VLC APs, have recently emerged as a more promising and robust design for the coexistence of RF and VLC systems. To this end, this paper, for the first time, investigates AP assignment, subchannel allocation (SA), and transmit power allocation (PA) to optimize the energy efficiency (EE) of aggregated RF/VLC systems while considering the effects of interference and VLC line-of-sight link blockages. A novel and challenging EE optimization problem is formulated for which an efficient joint solution based on alternating optimization is developed. More particularly, an energy-efficient AP assignment algorithm based on matching theory is proposed. Then, a low-complexity SA scheme that allocates subchannels to users based on their channel conditions is developed. Finally, an effective PA algorithm is presented by utilizing the quadratic transform approach and a multi-objective optimization framework. Extensive simulation results reveal that: 1) the proposed joint AP assignment, SA, and PA solution obtains significant EE, sum-rate, and outage performance gains with low complexity, and 2) the aggregated RF/VLC system provides considerable performance improvement compared to hybrid RF/VLC systems. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2206.01567v1-abstract-full').style.display = 'none'; document.getElementById('2206.01567v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 3 June, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> June 2022. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">30 pages, 11 figures, 1 table</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2203.12900">arXiv:2203.12900</a> <span> [<a href="https://arxiv.org/pdf/2203.12900">pdf</a>, <a href="https://arxiv.org/ps/2203.12900">ps</a>, <a href="https://arxiv.org/format/2203.12900">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Computer Science and Game Theory">cs.GT</span> </div> </div> <p class="title is-5 mathjax"> Two-timescale Resource Allocation for Automated Networks in IIoT </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=He%2C+Y">Yanhua He</a>, <a href="/search/eess?searchtype=author&query=Ren%2C+Y">Yun Ren</a>, <a href="/search/eess?searchtype=author&query=Zhou%2C+Z">Zhenyu Zhou</a>, <a href="/search/eess?searchtype=author&query=Mumtaz%2C+S">Shahid Mumtaz</a>, <a href="/search/eess?searchtype=author&query=Al-Rubaye%2C+S">Saba Al-Rubaye</a>, <a href="/search/eess?searchtype=author&query=Tsourdos%2C+A">Antonios Tsourdos</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2203.12900v1-abstract-short" style="display: inline;"> The rapid technological advances of cellular technologies will revolutionize network automation in industrial internet of things (IIoT). In this paper, we investigate the two-timescale resource allocation problem in IIoT networks with hybrid energy supply, where temporal variations of energy harvesting (EH), electricity price, channel state, and data arrival exhibit different granularity. The form… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2203.12900v1-abstract-full').style.display = 'inline'; document.getElementById('2203.12900v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2203.12900v1-abstract-full" style="display: none;"> The rapid technological advances of cellular technologies will revolutionize network automation in industrial internet of things (IIoT). In this paper, we investigate the two-timescale resource allocation problem in IIoT networks with hybrid energy supply, where temporal variations of energy harvesting (EH), electricity price, channel state, and data arrival exhibit different granularity. The formulated problem consists of energy management at a large timescale, as well as rate control, channel selection, and power allocation at a small timescale. To address this challenge, we develop an online solution to guarantee bounded performance deviation with only causal information. Specifically, Lyapunov optimization is leveraged to transform the long-term stochastic optimization problem into a series of short-term deterministic optimization problems. Then, a low-complexity rate control algorithm is developed based on alternating direction method of multipliers (ADMM), which accelerates the convergence speed via the decomposition-coordination approach. Next, the joint channel selection and power allocation problem is transformed into a one-to-many matching problem, and solved by the proposed price-based matching with quota restriction. Finally, the proposed algorithm is verified through simulations under various system configurations. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2203.12900v1-abstract-full').style.display = 'none'; document.getElementById('2203.12900v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 24 March, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> March 2022. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2203.06438">arXiv:2203.06438</a> <span> [<a href="https://arxiv.org/pdf/2203.06438">pdf</a>, <a href="https://arxiv.org/ps/2203.06438">ps</a>, <a href="https://arxiv.org/format/2203.06438">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Information Theory">cs.IT</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> </div> <p class="title is-5 mathjax"> Hierarchical Codebook based Multiuser Beam Training for Millimeter Massive MIMO </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Qi%2C+C">Chenhao Qi</a>, <a href="/search/eess?searchtype=author&query=Chen%2C+K">Kangjian Chen</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a>, <a href="/search/eess?searchtype=author&query=Li%2C+G+Y">Geoffrey Ye Li</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2203.06438v1-abstract-short" style="display: inline;"> In this paper, multiuser beam training based on hierarchical codebook for millimeter wave massive multi-input multi-output is investigated, where the base station (BS) simultaneously performs beam training with multiple user equipments (UEs). For the UEs, an alternative minimization method with a closed-form expression (AMCF) is proposed to design the hierarchical codebook under the constant modul… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2203.06438v1-abstract-full').style.display = 'inline'; document.getElementById('2203.06438v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2203.06438v1-abstract-full" style="display: none;"> In this paper, multiuser beam training based on hierarchical codebook for millimeter wave massive multi-input multi-output is investigated, where the base station (BS) simultaneously performs beam training with multiple user equipments (UEs). For the UEs, an alternative minimization method with a closed-form expression (AMCF) is proposed to design the hierarchical codebook under the constant modulus constraint. To speed up the convergence of the AMCF, an initialization method based on Zadoff-Chu sequence is proposed. For the BS, a simultaneous multiuser beam training scheme based on an adaptively designed hierarchical codebook is proposed, where the codewords in the current layer of the codebook are designed according to the beam training results of the previous layer. The codewords at the BS are designed with multiple mainlobes, each covering a spatial region for one or more UEs. Simulation results verify the effectiveness of the proposed hierarchical codebook design schemes and show that the proposed multiuser beam training scheme can approach the performance of the beam sweeping but with significantly reduced beam training overhead. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2203.06438v1-abstract-full').style.display = 'none'; document.getElementById('2203.06438v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 12 March, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> March 2022. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2203.03781">arXiv:2203.03781</a> <span> [<a href="https://arxiv.org/pdf/2203.03781">pdf</a>, <a href="https://arxiv.org/format/2203.03781">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Information Theory">cs.IT</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> </div> <p class="title is-5 mathjax"> Double-Sided Beamforming in OWC Systems Using Omni-Digital Reconfigurable Intelligent Surfaces </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Ndjiongue%2C+A+R">Alain R. Ndjiongue</a>, <a href="/search/eess?searchtype=author&query=Ngatched%2C+T+M+N">Telex M. N. Ngatched</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a>, <a href="/search/eess?searchtype=author&query=Haas%2C+H">Harald Haas</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2203.03781v1-abstract-short" style="display: inline;"> In this paper, we introduce a variant of reconfigurable intelligent surfaces (RISs) called omni-digital-RISs (DRISs), which allow multiple physical processes, with application to optical wireless communications systems. The proposed omni-DRIS contains both reflectors and refractive elements, as well as elements that perform both simultaneously. We describe and explain the concept of omni-DRIS, sug… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2203.03781v1-abstract-full').style.display = 'inline'; document.getElementById('2203.03781v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2203.03781v1-abstract-full" style="display: none;"> In this paper, we introduce a variant of reconfigurable intelligent surfaces (RISs) called omni-digital-RISs (DRISs), which allow multiple physical processes, with application to optical wireless communications systems. The proposed omni-DRIS contains both reflectors and refractive elements, as well as elements that perform both simultaneously. We describe and explain the concept of omni-DRIS, suggest and analyze an omni-DRIS coding structure, discuss metamaterials to be used, and provide a design example. Furthermore, we demonstrate that the achievable rate of an omni-DRIS system depends on the number of omni-DRIS elements, bits per phase shift, and the number of unused elements. In addition, we show that the achievable rate upper bound is related to the number of omni-DRIS elements, and conclude by discussing future research directions. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2203.03781v1-abstract-full').style.display = 'none'; document.getElementById('2203.03781v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 7 March, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> March 2022. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2202.07140">arXiv:2202.07140</a> <span> [<a href="https://arxiv.org/pdf/2202.07140">pdf</a>, <a href="https://arxiv.org/ps/2202.07140">ps</a>, <a href="https://arxiv.org/format/2202.07140">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Information Theory">cs.IT</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> </div> <p class="title is-5 mathjax"> Securing Reconfigurable Intelligent Surface-Aided Cell-Free Networks </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Hao%2C+W">Wanming Hao</a>, <a href="/search/eess?searchtype=author&query=Li%2C+J">Junjie Li</a>, <a href="/search/eess?searchtype=author&query=Sun%2C+G">Gangcan Sun</a>, <a href="/search/eess?searchtype=author&query=Zeng%2C+M">Ming Zeng</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2202.07140v1-abstract-short" style="display: inline;"> In this paper, we investigate the physical layer security in the reconfigurable intelligent surface (RIS)-aided cell-free networks. A maximum weighted sum secrecy rate problem is formulated by jointly optimizing the active beamforming (BF) at the base stations and passive BF at the RISs. To handle this non-trivial problem, we adopt the alternating optimization to decouple the original problem into… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2202.07140v1-abstract-full').style.display = 'inline'; document.getElementById('2202.07140v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2202.07140v1-abstract-full" style="display: none;"> In this paper, we investigate the physical layer security in the reconfigurable intelligent surface (RIS)-aided cell-free networks. A maximum weighted sum secrecy rate problem is formulated by jointly optimizing the active beamforming (BF) at the base stations and passive BF at the RISs. To handle this non-trivial problem, we adopt the alternating optimization to decouple the original problem into two sub-ones, which are solved using the semidefinite relaxation and continuous convex approximation theory. To decrease the complexity for obtaining overall channel state information (CSI), we extend the proposed framework to the case that only requires part of the RIS' CSI. This is achieved via deliberately discarding the RIS that has a small contribution to the user's secrecy rate. Based on this, we formulate a mixed integer non-linear programming problem, and the linear conic relaxation is used to obtained the solutions. Finally, the simulation results show that the proposed schemes can obtain a higher secrecy rate than the existing ones. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2202.07140v1-abstract-full').style.display = 'none'; document.getElementById('2202.07140v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 14 February, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> February 2022. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2202.07137">arXiv:2202.07137</a> <span> [<a href="https://arxiv.org/pdf/2202.07137">pdf</a>, <a href="https://arxiv.org/format/2202.07137">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Information Theory">cs.IT</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> </div> <p class="title is-5 mathjax"> Ultra Wide Band THz IRS Communications: Applications, Challenges, Key Techniques, and Research Opportunities </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Hao%2C+W">Wanming Hao</a>, <a href="/search/eess?searchtype=author&query=Zhou%2C+F">Fuhui Zhou</a>, <a href="/search/eess?searchtype=author&query=Zeng%2C+M">Ming Zeng</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a>, <a href="/search/eess?searchtype=author&query=Al-Dhahir%2C+N">Naofal Al-Dhahir</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2202.07137v1-abstract-short" style="display: inline;"> Terahertz (THz) communication is a promising technology for future wireless networks due to its ultra-wide bandwidth. However, THz signals suffer from severe attenuation and poor diffraction capability, making it vulnerable to blocking obstacles. To compensate for these two shortcomings and improve the system performance, an intelligent reflecting surface (IRS) can be exploited to change the propa… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2202.07137v1-abstract-full').style.display = 'inline'; document.getElementById('2202.07137v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2202.07137v1-abstract-full" style="display: none;"> Terahertz (THz) communication is a promising technology for future wireless networks due to its ultra-wide bandwidth. However, THz signals suffer from severe attenuation and poor diffraction capability, making it vulnerable to blocking obstacles. To compensate for these two shortcomings and improve the system performance, an intelligent reflecting surface (IRS) can be exploited to change the propagation direction and enhance the signal strength. In this article, we investigate this promising ultra wide band (UWB) THz IRS communication paradigm. We start by motivating our research and describing several potential application scenarios. Then, we identify major challenges faced by UWB THz IRS communications. To overcome these challenges, several effective key techniques are developed, i.e., the time delayer-based sparse radio frequency antenna structure, delay hybrid precoding and IRS deployment. Simulation results are also presented to compare the system performance for these proposed techniques, thus demonstrating their effectiveness. Finally, we highlight several open issues and research opportunities for UWB THz IRS communications. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2202.07137v1-abstract-full').style.display = 'none'; document.getElementById('2202.07137v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 14 February, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> February 2022. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> IEEE Network,2022 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2112.09984">arXiv:2112.09984</a> <span> [<a href="https://arxiv.org/pdf/2112.09984">pdf</a>, <a href="https://arxiv.org/format/2112.09984">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1109/JLT.2022.3176762">10.1109/JLT.2022.3176762 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Digital RIS (DRIS): The Future of Digital Beam Management in RIS-Assisted OWC Systems </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Ndjiongue%2C+A+R">Alain R. Ndjiongue</a>, <a href="/search/eess?searchtype=author&query=Ngatched%2C+T+M+N">Telex M. N. Ngatched</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a>, <a href="/search/eess?searchtype=author&query=Haas%2C+H">Harald Haas</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2112.09984v1-abstract-short" style="display: inline;"> Reconfigurable intelligent surfaces (RIS) have been recently introduced to optical wireless communication (OWC) networks to resolve skip areas and improve the signal-to-noise ratio at the user's end. In OWC networks, RIS are based on mirrors or metasurfaces. Metasurfaces have evolved significantly over the last few years. As a result, coding, digital, programmable, and information metamaterials ha… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2112.09984v1-abstract-full').style.display = 'inline'; document.getElementById('2112.09984v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2112.09984v1-abstract-full" style="display: none;"> Reconfigurable intelligent surfaces (RIS) have been recently introduced to optical wireless communication (OWC) networks to resolve skip areas and improve the signal-to-noise ratio at the user's end. In OWC networks, RIS are based on mirrors or metasurfaces. Metasurfaces have evolved significantly over the last few years. As a result, coding, digital, programmable, and information metamaterials have been developed. The advantage of these materials is that they can enable digital signal processing (DSP) techniques. For the first time, this paper proposes the use of digital RIS (DRIS) in OWC systems. We discuss the concept of DRIS and the application of DSP methods to the physical material. In addition, we examine metamaterials for optical DRIS with liquid crystals serving as the front row material. Finally, we present a design example and discuss future research directions. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2112.09984v1-abstract-full').style.display = 'none'; document.getElementById('2112.09984v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 18 December, 2021; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> December 2021. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2111.15110">arXiv:2111.15110</a> <span> [<a href="https://arxiv.org/pdf/2111.15110">pdf</a>, <a href="https://arxiv.org/ps/2111.15110">ps</a>, <a href="https://arxiv.org/format/2111.15110">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Information Theory">cs.IT</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1109/LCOMM.2021.3120560">10.1109/LCOMM.2021.3120560 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Reconfigurable Intelligent Surface Optimization for Uplink Sparse Code Multiple Access </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Al-Nahhal%2C+I">Ibrahim Al-Nahhal</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a>, <a href="/search/eess?searchtype=author&query=Basar%2C+E">Ertugrul Basar</a>, <a href="/search/eess?searchtype=author&query=Ngatched%2C+T+M+N">Telex M. N. Ngatched</a>, <a href="/search/eess?searchtype=author&query=Ikki%2C+S">Salama Ikki</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2111.15110v1-abstract-short" style="display: inline;"> The reconfigurable intelligent surface (RIS)-assisted sparse code multiple access (RIS-SCMA) is an attractive scheme for future wireless networks. In this letter, for the first time, the RIS phase shifts of the uplink RIS-SCMA system are optimized based on the alternate optimization (AO) technique to improve the received signal-to-noise ratio (SNR) for a discrete set of RIS phase shifts. The syste… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2111.15110v1-abstract-full').style.display = 'inline'; document.getElementById('2111.15110v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2111.15110v1-abstract-full" style="display: none;"> The reconfigurable intelligent surface (RIS)-assisted sparse code multiple access (RIS-SCMA) is an attractive scheme for future wireless networks. In this letter, for the first time, the RIS phase shifts of the uplink RIS-SCMA system are optimized based on the alternate optimization (AO) technique to improve the received signal-to-noise ratio (SNR) for a discrete set of RIS phase shifts. The system model of the uplink RIS-SCMA is formulated to utilize the AO algorithm. For further reduction in the computational complexity, a low-complexity AO (LC-AO) algorithm is proposed. The complexity analysis of the two proposed algorithms is performed. Monte Carlo simulations and complexity analysis show that the proposed algorithms significantly improve the received SNR compared to the non-optimized RIS-SCMA scenario. The LC-AO provides the same received SNR as the AO algorithm, with a significant reduction in complexity. Moreover, the deployment of RISs for the uplink RIS-SCMA is investigated. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2111.15110v1-abstract-full').style.display = 'none'; document.getElementById('2111.15110v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 29 November, 2021; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2021. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">6 pages, 5 figures, published in IEEE Communications Letters</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2111.08834">arXiv:2111.08834</a> <span> [<a href="https://arxiv.org/pdf/2111.08834">pdf</a>, <a href="https://arxiv.org/format/2111.08834">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> </div> <p class="title is-5 mathjax"> Federated Learning for Smart Healthcare: A Survey </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Nguyen%2C+D+C">Dinh C. Nguyen</a>, <a href="/search/eess?searchtype=author&query=Pham%2C+Q">Quoc-Viet Pham</a>, <a href="/search/eess?searchtype=author&query=Pathirana%2C+P+N">Pubudu N. Pathirana</a>, <a href="/search/eess?searchtype=author&query=Ding%2C+M">Ming Ding</a>, <a href="/search/eess?searchtype=author&query=Seneviratne%2C+A">Aruna Seneviratne</a>, <a href="/search/eess?searchtype=author&query=Lin%2C+Z">Zihuai Lin</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a>, <a href="/search/eess?searchtype=author&query=Hwang%2C+W">Won-Joo Hwang</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2111.08834v1-abstract-short" style="display: inline;"> Recent advances in communication technologies and Internet-of-Medical-Things have transformed smart healthcare enabled by artificial intelligence (AI). Traditionally, AI techniques require centralized data collection and processing that may be infeasible in realistic healthcare scenarios due to the high scalability of modern healthcare networks and growing data privacy concerns. Federated Learning… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2111.08834v1-abstract-full').style.display = 'inline'; document.getElementById('2111.08834v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2111.08834v1-abstract-full" style="display: none;"> Recent advances in communication technologies and Internet-of-Medical-Things have transformed smart healthcare enabled by artificial intelligence (AI). Traditionally, AI techniques require centralized data collection and processing that may be infeasible in realistic healthcare scenarios due to the high scalability of modern healthcare networks and growing data privacy concerns. Federated Learning (FL), as an emerging distributed collaborative AI paradigm, is particularly attractive for smart healthcare, by coordinating multiple clients (e.g., hospitals) to perform AI training without sharing raw data. Accordingly, we provide a comprehensive survey on the use of FL in smart healthcare. First, we present the recent advances in FL, the motivations, and the requirements of using FL in smart healthcare. The recent FL designs for smart healthcare are then discussed, ranging from resource-aware FL, secure and privacy-aware FL to incentive FL and personalized FL. Subsequently, we provide a state-of-the-art review on the emerging applications of FL in key healthcare domains, including health data management, remote health monitoring, medical imaging, and COVID-19 detection. Several recent FL-based smart healthcare projects are analyzed, and the key lessons learned from the survey are also highlighted. Finally, we discuss interesting research challenges and possible directions for future FL research in smart healthcare. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2111.08834v1-abstract-full').style.display = 'none'; document.getElementById('2111.08834v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 16 November, 2021; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2021. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">Accepted at ACM Computing Surveys, 35 pages</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2110.12610">arXiv:2110.12610</a> <span> [<a href="https://arxiv.org/pdf/2110.12610">pdf</a>, <a href="https://arxiv.org/format/2110.12610">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Information Theory">cs.IT</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> </div> <p class="title is-5 mathjax"> Antenna Array Enabled Space/Air/Ground Communications and Networking for 6G </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Xiao%2C+Z">Zhenyu Xiao</a>, <a href="/search/eess?searchtype=author&query=Han%2C+Z">Zhu Han</a>, <a href="/search/eess?searchtype=author&query=Nallanathan%2C+A">Arumugam Nallanathan</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a>, <a href="/search/eess?searchtype=author&query=Clerckx%2C+B">Bruno Clerckx</a>, <a href="/search/eess?searchtype=author&query=Choi%2C+J">Jinho Choi</a>, <a href="/search/eess?searchtype=author&query=He%2C+C">Chong He</a>, <a href="/search/eess?searchtype=author&query=Tong%2C+W">Wen Tong</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2110.12610v2-abstract-short" style="display: inline;"> Antenna arrays have a long history of more than 100 years and have evolved closely with the development of electronic and information technologies, playing an indispensable role in wireless communications and radar. With the rapid development of electronic and information technologies, the demand for all-time, all-domain, and full-space network services has exploded, and new communication requirem… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2110.12610v2-abstract-full').style.display = 'inline'; document.getElementById('2110.12610v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2110.12610v2-abstract-full" style="display: none;"> Antenna arrays have a long history of more than 100 years and have evolved closely with the development of electronic and information technologies, playing an indispensable role in wireless communications and radar. With the rapid development of electronic and information technologies, the demand for all-time, all-domain, and full-space network services has exploded, and new communication requirements have been put forward on various space/air/ground platforms. To meet the ever increasing requirements of the future sixth generation (6G) wireless communications, such as high capacity, wide coverage, low latency, and strong robustness, it is promising to employ different types of antenna arrays with various beamforming technologies in space/air/ground communication networks, bringing in advantages such as considerable antenna gains, multiplexing gains, and diversity gains. However, enabling antenna array for space/air/ground communication networks poses specific, distinctive and tricky challenges, which has aroused extensive research attention. This paper aims to overview the field of antenna array enabled space/air/ground communications and networking. The technical potentials and challenges of antenna array enabled space/air/ground communications and networking are presented first. Subsequently, the antenna array structures and designs are discussed. We then discuss various emerging technologies facilitated by antenna arrays to meet the new communication requirements of space/air/ground communication systems. Enabled by these emerging technologies, the distinct characteristics, challenges, and solutions for space communications, airborne communications, and ground communications are reviewed. Finally, we present promising directions for future research in antenna array enabled space/air/ground communications and networking. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2110.12610v2-abstract-full').style.display = 'none'; document.getElementById('2110.12610v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 26 March, 2022; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 24 October, 2021; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> October 2021. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2110.09997">arXiv:2110.09997</a> <span> [<a href="https://arxiv.org/pdf/2110.09997">pdf</a>, <a href="https://arxiv.org/ps/2110.09997">ps</a>, <a href="https://arxiv.org/format/2110.09997">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Information Theory">cs.IT</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> </div> </div> <p class="title is-5 mathjax"> Hybrid-Layers Neural Network Architectures for Modeling the Self-Interference in Full-Duplex Systems </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Elsayed%2C+M">Mohamed Elsayed</a>, <a href="/search/eess?searchtype=author&query=El-Banna%2C+A+A+A">Ahmad A. Aziz El-Banna</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a>, <a href="/search/eess?searchtype=author&query=Shiu%2C+W">Wanyi Shiu</a>, <a href="/search/eess?searchtype=author&query=Wang%2C+P">Peiwei Wang</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2110.09997v1-abstract-short" style="display: inline;"> Full-duplex (FD) systems have been introduced to provide high data rates for beyond fifth-generation wireless networks through simultaneous transmission of information over the same frequency resources. However, the operation of FD systems is practically limited by the self-interference (SI), and efficient SI cancelers are sought to make the FD systems realizable. Typically, polynomial-based cance… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2110.09997v1-abstract-full').style.display = 'inline'; document.getElementById('2110.09997v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2110.09997v1-abstract-full" style="display: none;"> Full-duplex (FD) systems have been introduced to provide high data rates for beyond fifth-generation wireless networks through simultaneous transmission of information over the same frequency resources. However, the operation of FD systems is practically limited by the self-interference (SI), and efficient SI cancelers are sought to make the FD systems realizable. Typically, polynomial-based cancelers are employed to mitigate the SI; nevertheless, they suffer from high complexity. This article proposes two novel hybrid-layers neural network (NN) architectures to cancel the SI with low complexity. The first architecture is referred to as hybrid-convolutional recurrent NN (HCRNN), whereas the second is termed as hybrid-convolutional recurrent dense NN (HCRDNN). In contrast to the state-of-the-art NNs that employ dense or recurrent layers for SI modeling, the proposed NNs exploit, in a novel manner, a combination of different hidden layers (e.g., convolutional, recurrent, and/or dense) in order to model the SI with lower computational complexity than the polynomial and the state-of-the-art NN-based cancelers. The key idea behind using hybrid layers is to build an NN model, which makes use of the characteristics of the different layers employed in its architecture. More specifically, in the HCRNN, a convolutional layer is employed to extract the input data features using a reduced network scale. Moreover, a recurrent layer is then applied to assist in learning the temporal behavior of the input signal from the localized feature map of the convolutional layer. In the HCRDNN, an additional dense layer is exploited to add another degree of freedom for adapting the NN settings in order to achieve the best compromise between the cancellation performance and computational complexity. Complexity analysis and numerical simulations are provided to prove the superiority of the proposed architectures. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2110.09997v1-abstract-full').style.display = 'none'; document.getElementById('2110.09997v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 18 October, 2021; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> October 2021. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">37 pages, 10 figures, to appear in the IEEE transactions on vehicular technology</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2110.05563">arXiv:2110.05563</a> <span> [<a href="https://arxiv.org/pdf/2110.05563">pdf</a>, <a href="https://arxiv.org/format/2110.05563">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1109/JLT.2021.3133475">10.1109/JLT.2021.3133475 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Perturbation Theory-Aided Learned Digital Back-Propagation Scheme for Optical Fiber Nonlinearity Compensation </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Lin%2C+X">Xiang Lin</a>, <a href="/search/eess?searchtype=author&query=Luo%2C+S">Shenghang Luo</a>, <a href="/search/eess?searchtype=author&query=Soman%2C+S+K+O">Sunish Kumar Orappanpara Soman</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a>, <a href="/search/eess?searchtype=author&query=Lampe%2C+L">Lutz Lampe</a>, <a href="/search/eess?searchtype=author&query=Chang%2C+D">Deyuan Chang</a>, <a href="/search/eess?searchtype=author&query=Li%2C+C">Chuandong Li</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2110.05563v1-abstract-short" style="display: inline;"> Derived from the regular perturbation treatment of the nonlinear Schrodinger equation, a machine learning-based scheme to mitigate the intra-channel optical fiber nonlinearity is proposed. Referred to as the perturbation theory-aided (PA) learned digital back-propagation (LDBP), the proposed scheme constructs a deep neural network (DNN) in a way similar to the split-step Fourier method: linear and… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2110.05563v1-abstract-full').style.display = 'inline'; document.getElementById('2110.05563v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2110.05563v1-abstract-full" style="display: none;"> Derived from the regular perturbation treatment of the nonlinear Schrodinger equation, a machine learning-based scheme to mitigate the intra-channel optical fiber nonlinearity is proposed. Referred to as the perturbation theory-aided (PA) learned digital back-propagation (LDBP), the proposed scheme constructs a deep neural network (DNN) in a way similar to the split-step Fourier method: linear and nonlinear operations alternate. Inspired by the perturbation analysis, the intra-channel cross-phase modulation term is conveniently represented by matrix operations in the DNN. The introduction of this term in each nonlinear operation considerably improves the performance, as well as enables the flexibility of PA-LDBP by adjusting the numbers of spans per step. The proposed scheme is evaluated by numerical simulations of a single carrier optical fiber communication system operating at 32 Gbaud with 64-quadrature amplitude modulation and 20*80 km transmission distance. The results show that the proposed scheme achieves approximately 3.5 dB, 1.8 dB, 1.4 dB, and 0.5 dB performance gain in terms of Q2 factor over the linear compensation, when the numbers of spans per step are 1, 2, 4, and 10, respectively. Two methods are proposed to reduce the complexity of PALDBP, i.e., pruning the number of perturbation coefficients and chromatic dispersion compensation in the frequency domain for multi-span per step cases. Investigation of the performance and complexity suggests that PA-LDBP attains improved performance gains with reduced complexity when compared to LDBP in the cases of 4 and 10 spans per step. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2110.05563v1-abstract-full').style.display = 'none'; document.getElementById('2110.05563v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 11 October, 2021; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> October 2021. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2110.04859">arXiv:2110.04859</a> <span> [<a href="https://arxiv.org/pdf/2110.04859">pdf</a>, <a href="https://arxiv.org/ps/2110.04859">ps</a>, <a href="https://arxiv.org/format/2110.04859">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1109/LCOMM.2021.3117929">10.1109/LCOMM.2021.3117929 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Deep Reinforcement Learning for Optimizing RIS-Assisted HD-FD Wireless Systems </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Faisal%2C+A">Alice Faisal</a>, <a href="/search/eess?searchtype=author&query=Al-Nahhal%2C+I">Ibrahim Al-Nahhal</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a>, <a href="/search/eess?searchtype=author&query=Ngatched%2C+T+M+N">Telex M. N. Ngatched</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2110.04859v1-abstract-short" style="display: inline;"> This letter investigates the reconfigurable intelligent surface (RIS)-assisted multiple-input single-output (MISO) wireless system, where both half-duplex (HD) and full-duplex (FD) operating modes are considered together, for the first time in the literature. The goal is to maximize the rate by optimizing the RIS phase shifts. A novel deep reinforcement learning (DRL) algorithm is proposed to solv… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2110.04859v1-abstract-full').style.display = 'inline'; document.getElementById('2110.04859v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2110.04859v1-abstract-full" style="display: none;"> This letter investigates the reconfigurable intelligent surface (RIS)-assisted multiple-input single-output (MISO) wireless system, where both half-duplex (HD) and full-duplex (FD) operating modes are considered together, for the first time in the literature. The goal is to maximize the rate by optimizing the RIS phase shifts. A novel deep reinforcement learning (DRL) algorithm is proposed to solve the formulated non-convex optimization problem. The complexity analysis and Monte Carlo simulations illustrate that the proposed DRL algorithm significantly improves the rate compared to the non-optimized scenario in both HD and FD operating modes using a single parameter setting. Besides, it significantly reduces the computational complexity of the downlink HD MISO system and improves the achievable rate with a reduced number of steps per episode compared to the conventional DRL algorithm. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2110.04859v1-abstract-full').style.display = 'none'; document.getElementById('2110.04859v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 10 October, 2021; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> October 2021. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">14 pages, 6 figures, IEEE Communications Letters</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2109.11509">arXiv:2109.11509</a> <span> [<a href="https://arxiv.org/pdf/2109.11509">pdf</a>, <a href="https://arxiv.org/format/2109.11509">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> </div> <p class="title is-5 mathjax"> Integration of Backscatter Communication with Multi-cell NOMA: A Spectral Efficiency Optimization under Imperfect SIC </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Khan%2C+W+U">Wali Ullah Khan</a>, <a href="/search/eess?searchtype=author&query=Lagunas%2C+E">Eva Lagunas</a>, <a href="/search/eess?searchtype=author&query=Mahmood%2C+A">Asad Mahmood</a>, <a href="/search/eess?searchtype=author&query=Ali%2C+Z">Zain Ali</a>, <a href="/search/eess?searchtype=author&query=Chatzinotas%2C+S">Symeon Chatzinotas</a>, <a href="/search/eess?searchtype=author&query=Ottersten%2C+B">Bj枚rn Ottersten</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2109.11509v4-abstract-short" style="display: inline;"> Future wireless networks are expected to connect large-scale low-powered communication devices using the available spectrum resources. Backscatter communications (BC) is an emerging technology towards battery-free transmission in future wireless networks by leveraging ambient radio frequency (RF) waves that enable communications among wireless devices. Non-orthogonal multiple access (NOMA) has rec… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2109.11509v4-abstract-full').style.display = 'inline'; document.getElementById('2109.11509v4-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2109.11509v4-abstract-full" style="display: none;"> Future wireless networks are expected to connect large-scale low-powered communication devices using the available spectrum resources. Backscatter communications (BC) is an emerging technology towards battery-free transmission in future wireless networks by leveraging ambient radio frequency (RF) waves that enable communications among wireless devices. Non-orthogonal multiple access (NOMA) has recently drawn significant attention due to its high spectral efficiency. The combination of these two technologies can play an important role in the development of future networks. This paper proposes a new optimization approach to enhance the spectral efficiency of nonorthogonal multiple access (NOMA)-BC network. Our framework simultaneously optimizes the power allocation of base station and reflection coefficient (RC) of the backscatter device in each cell under the assumption of imperfect signal decoding. The problem of spectral efficiency maximization is coupled on power and RC which is challenging to solve. To make this problem tractable, we first decouple it into two subproblems and then apply the decomposition method and Karush-Kuhn-Tucker conditions to obtain the efficient solution. Numerical results show the performance of the proposed NOMA-BC network over the pure NOMA network without BC. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2109.11509v4-abstract-full').style.display = 'none'; document.getElementById('2109.11509v4-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 1 August, 2022; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 23 September, 2021; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> September 2021. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">5 pages, 4 figures</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2108.05661">arXiv:2108.05661</a> <span> [<a href="https://arxiv.org/pdf/2108.05661">pdf</a>, <a href="https://arxiv.org/format/2108.05661">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> </div> <p class="title is-5 mathjax"> Deep Learning-based Time-varying Channel Estimation for RIS Assisted Communication </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Xu%2C+M">Meng Xu</a>, <a href="/search/eess?searchtype=author&query=Zhang%2C+S">Shun Zhang</a>, <a href="/search/eess?searchtype=author&query=Ma%2C+J">Jianpeng Ma</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2108.05661v1-abstract-short" style="display: inline;"> Reconfigurable intelligent surface (RIS) is considered as a revolutionary technology for future wireless communication networks. In this letter, we consider the acquisition of the time-varying cascaded channels, which is a challenging task due to the massive number of passive RIS elements and the small channel coherence time. To reduce the pilot overhead, a deep learning-based channel extrapolatio… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2108.05661v1-abstract-full').style.display = 'inline'; document.getElementById('2108.05661v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2108.05661v1-abstract-full" style="display: none;"> Reconfigurable intelligent surface (RIS) is considered as a revolutionary technology for future wireless communication networks. In this letter, we consider the acquisition of the time-varying cascaded channels, which is a challenging task due to the massive number of passive RIS elements and the small channel coherence time. To reduce the pilot overhead, a deep learning-based channel extrapolation is implemented over both antenna and time domains. We divide the neural network into two parts, i.e., the time-domain and the antenna-domain extrapolation networks, where the neural ordinary differential equations (ODE) are utilized. In the former, ODE accurately describes the dynamics of the RIS channels and improves the recurrent neural network's performance of time series reconstruction. In the latter, ODE is resorted to modify the relations among different data layers in a feedforward neural network. We cascade the two networks and jointly train them. Simulation results show that the proposed scheme can effectively extrapolate the cascaded RIS channels in high mobility scenario. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2108.05661v1-abstract-full').style.display = 'none'; document.getElementById('2108.05661v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 12 August, 2021; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> August 2021. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2108.03941">arXiv:2108.03941</a> <span> [<a href="https://arxiv.org/pdf/2108.03941">pdf</a>, <a href="https://arxiv.org/ps/2108.03941">ps</a>, <a href="https://arxiv.org/format/2108.03941">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Information Theory">cs.IT</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Artificial Intelligence">cs.AI</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> </div> <p class="title is-5 mathjax"> Deep Learning Based Antenna-time Domain Channel Extrapolation for Hybrid mmWave Massive MIMO </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Zhang%2C+S">Shunbo Zhang</a>, <a href="/search/eess?searchtype=author&query=Zhang%2C+S">Shun Zhang</a>, <a href="/search/eess?searchtype=author&query=Ma%2C+J">Jianpeng Ma</a>, <a href="/search/eess?searchtype=author&query=Liu%2C+T">Tian Liu</a>, <a href="/search/eess?searchtype=author&query=Dobre%2C+O+A">Octavia A. Dobre</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2108.03941v1-abstract-short" style="display: inline;"> In a time-varying massive multiple-input multipleoutput (MIMO) system, the acquisition of the downlink channel state information at the base station (BS) is a very challenging task due to the prohibitively high overheads associated with downlink training and uplink feedback. In this paper, we consider the hybrid precoding structure at BS and examine the antennatime domain channel extrapolation. We… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2108.03941v1-abstract-full').style.display = 'inline'; document.getElementById('2108.03941v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2108.03941v1-abstract-full" style="display: none;"> In a time-varying massive multiple-input multipleoutput (MIMO) system, the acquisition of the downlink channel state information at the base station (BS) is a very challenging task due to the prohibitively high overheads associated with downlink training and uplink feedback. In this paper, we consider the hybrid precoding structure at BS and examine the antennatime domain channel extrapolation. We design a latent ordinary differential equation (ODE)-based network under the variational auto-encoder (VAE) framework to learn the mapping function from the partial uplink channels to the full downlink ones at the BS side. Specifically, the gated recurrent unit is adopted for the encoder and the fully-connected neural network is used for the decoder. The end-to-end learning is utilized to optimize the network parameters. Simulation results show that the designed network can efficiently infer the full downlink channels from the partial uplink ones, which can significantly reduce the channel training overhead. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2108.03941v1-abstract-full').style.display = 'none'; document.getElementById('2108.03941v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 9 August, 2021; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> August 2021. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">5 pages, 5 figures</span> </p> </li> </ol> <nav class="pagination is-small is-centered breathe-horizontal" role="navigation" aria-label="pagination"> <a href="" class="pagination-previous 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