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name="abstracts" type="radio" value="hide"> <label for="abstracts-1">Hide abstracts</label></li></ul> </div> <div class="box field is-grouped is-grouped-multiline level-item"> <div class="control"> <span class="select is-small"> <select id="size" name="size"><option value="25">25</option><option selected value="50">50</option><option value="100">100</option><option value="200">200</option></select> </span> <label for="size">results per page</label>. </div> <div class="control"> <label for="order">Sort results by</label> <span class="select is-small"> <select id="order" name="order"><option selected value="-announced_date_first">Announcement date (newest first)</option><option value="announced_date_first">Announcement date (oldest first)</option><option value="-submitted_date">Submission date (newest first)</option><option value="submitted_date">Submission date (oldest first)</option><option value="">Relevance</option></select> </span> </div> <div class="control"> <button class="button is-small is-link">Go</button> </div> </div> </form> </div> </div> <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/2503.14287">arXiv:2503.14287</a> <span> [<a href="https://arxiv.org/pdf/2503.14287">pdf</a>, <a href="https://arxiv.org/format/2503.14287">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="Systems and Control">eess.SY</span> </div> </div> <p class="title is-5 mathjax"> Cross-Environment Transfer Learning for Location-Aided Beam Prediction in 5G and Beyond Millimeter-Wave Networks </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Tosi%2C+E">Enrico Tosi</a>, <a href="/search/eess?searchtype=author&query=Hu%2C+P">Panwei Hu</a>, <a href="/search/eess?searchtype=author&query=Ichkov%2C+A">Aleksandar Ichkov</a>, <a href="/search/eess?searchtype=author&query=Petrova%2C+M">Marina Petrova</a>, <a href="/search/eess?searchtype=author&query=Simi%C4%87%2C+L">Ljiljana Simi膰</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="2503.14287v1-abstract-short" style="display: inline;"> Millimeter-wave (mm-wave) communications requirebeamforming and consequent precise beam alignmentbetween the gNodeB (gNB) and the user equipment (UE) toovercome high propagation losses. This beam alignment needs tobe constantly updated for different UE locations based on beamsweepingradio frequency measurements, leading to significantbeam management overhead. One potential solution involvesusing m… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2503.14287v1-abstract-full').style.display = 'inline'; document.getElementById('2503.14287v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2503.14287v1-abstract-full" style="display: none;"> Millimeter-wave (mm-wave) communications requirebeamforming and consequent precise beam alignmentbetween the gNodeB (gNB) and the user equipment (UE) toovercome high propagation losses. This beam alignment needs tobe constantly updated for different UE locations based on beamsweepingradio frequency measurements, leading to significantbeam management overhead. One potential solution involvesusing machine learning (ML) beam prediction algorithms thatleverage UE position information to select the serving beamwithout the overhead of beam sweeping. However, the highlysite-specific nature of mm-wave propagation means that MLmodels require training from scratch for each scenario, whichis inefficient in practice. In this paper, we propose a robustcross-environment transfer learning solution for location-aidedbeam prediction, whereby the ML model trained on a referencegNB is transferred to a target gNB by fine-tuning with a limiteddataset. Extensive simulation results based on ray-tracing in twourban environments show the effectiveness of our solution forboth inter- and intra-city model transfer. Our results show thatby training the model on a reference gNB and transferring themodel by fine-tuning with only 5% of the target gNB dataset,we can achieve 80% accuracy in predicting the best beamfor the target gNB. Importantly, our approach improves thepoor generalization accuracy of transferring the model to newenvironments without fine-tuning by around 75 percentage points.This demonstrates that transfer learning enables high predictionaccuracy while reducing the computational and training datasetcollection burden of ML-based beam prediction, making itpractical for 5G-and-beyond deployments. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2503.14287v1-abstract-full').style.display = 'none'; document.getElementById('2503.14287v1-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 March, 2025; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> March 2025. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2405.00714">arXiv:2405.00714</a> <span> [<a href="https://arxiv.org/pdf/2405.00714">pdf</a>, <a href="https://arxiv.org/format/2405.00714">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="Networking and Internet Architecture">cs.NI</span> </div> </div> <p class="title is-5 mathjax"> Multi-Band mm-Wave Measurement Platform Towards Environment-Aware Beam Management </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Ichkov%2C+A">Aleksandar Ichkov</a>, <a href="/search/eess?searchtype=author&query=Schott%2C+A">Aron Schott</a>, <a href="/search/eess?searchtype=author&query=Beckmann%2C+N">Niklas Beckmann</a>, <a href="/search/eess?searchtype=author&query=Simi%C4%87%2C+L">Ljiljana Simi膰</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="2405.00714v1-abstract-short" style="display: inline;"> Agile beam management is key for providing seamless millimeter wave (mm-wave) connectivity given the site-specific spatio-temporal variations of the mm-wave channel. Leveraging non radio frequency (RF) sensor inputs for environment awareness, e.g. via machine learning (ML) techniques, can greatly enhance RF-based beam steering. To overcome the lack of diverse publicly available multi-modal mm-wave… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2405.00714v1-abstract-full').style.display = 'inline'; document.getElementById('2405.00714v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2405.00714v1-abstract-full" style="display: none;"> Agile beam management is key for providing seamless millimeter wave (mm-wave) connectivity given the site-specific spatio-temporal variations of the mm-wave channel. Leveraging non radio frequency (RF) sensor inputs for environment awareness, e.g. via machine learning (ML) techniques, can greatly enhance RF-based beam steering. To overcome the lack of diverse publicly available multi-modal mm-wave datasets for the design and evaluation of such novel beam steering approaches, we demonstrate our software-defined radio multi-band mm-wave measurement platform which integrates multi-modal sensors towards environment-aware beam management. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2405.00714v1-abstract-full').style.display = 'none'; document.getElementById('2405.00714v1-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 April, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> May 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">2 pages, 1 figure</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2402.17573">arXiv:2402.17573</a> <span> [<a href="https://arxiv.org/pdf/2402.17573">pdf</a>, <a href="https://arxiv.org/format/2402.17573">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"> HBF MU-MIMO with Interference-Aware Beam Pair Link Allocation for Beyond-5G mm-Wave Networks </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Ichkov%2C+A">Aleksandar Ichkov</a>, <a href="/search/eess?searchtype=author&query=Wietfeld%2C+A">Alexander Wietfeld</a>, <a href="/search/eess?searchtype=author&query=Petrova%2C+M">Marina Petrova</a>, <a href="/search/eess?searchtype=author&query=Simi%C4%87%2C+L">Ljiljana Simi膰</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="2402.17573v1-abstract-short" style="display: inline;"> Hybrid beamforming (HBF) multi-user multiple-input multiple-output (MU-MIMO) is a key technology for unlocking the directional millimeter-wave (mm-wave) nature for spatial multiplexing beyond current codebook-based 5G-NR networks. In order to suppress co-scheduled users' interference, HBF MU-MIMO is predicated on having sufficient radio frequency chains and accurate channel state information (CSI)… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2402.17573v1-abstract-full').style.display = 'inline'; document.getElementById('2402.17573v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2402.17573v1-abstract-full" style="display: none;"> Hybrid beamforming (HBF) multi-user multiple-input multiple-output (MU-MIMO) is a key technology for unlocking the directional millimeter-wave (mm-wave) nature for spatial multiplexing beyond current codebook-based 5G-NR networks. In order to suppress co-scheduled users' interference, HBF MU-MIMO is predicated on having sufficient radio frequency chains and accurate channel state information (CSI), which can otherwise lead to performance losses due to imperfect interference cancellation. In this work, we propose IABA, a 5G-NR standard-compliant beam pair link (BPL) allocation scheme for mitigating spatial interference in practical HBF MU-MIMO networks. IABA solves the network sum throughput optimization via either a distributed or a centralized BPL allocation using dedicated CSI reference signals for candidate BPL monitoring. We present a comprehensive study of practical multi-cell mm-wave networks and demonstrate that HBF MU-MIMO without interference-aware BPL allocation experiences strong residual interference which limits the achievable network performance. Our results show that IABA offers significant performance gains over the default interference-agnostic 5G-NR BPL allocation, and even allows HBF MU-MIMO to outperform the fully digital MU-MIMO baseline, by facilitating allocation of secondary BPLs other than the strongest BPL found during initial access. We further demonstrate the scalability of IABA with increased gNB antennas and densification for beyond-5G mm-wave networks. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2402.17573v1-abstract-full').style.display = 'none'; document.getElementById('2402.17573v1-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> 27 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">13 pages, 11 figures. This work has been submitted to IEEE for possible publication (copyright may be transferred without notice, after which this version may no longer be accessible)</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2002.01450">arXiv:2002.01450</a> <span> [<a href="https://arxiv.org/pdf/2002.01450">pdf</a>, <a href="https://arxiv.org/format/2002.01450">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"> Multi-User Provisioning in Millimeter-Wave Urban Cellular Networks </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Ichkov%2C+A">Aleksandar Ichkov</a>, <a href="/search/eess?searchtype=author&query=Sialkowski%2C+D">Daniel Sialkowski</a>, <a href="/search/eess?searchtype=author&query=M%C3%A4h%C3%B6nen%2C+P">Petri M盲h枚nen</a>, <a href="/search/eess?searchtype=author&query=Simi%C4%87%2C+L">Ljiljana Simi膰</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="2002.01450v1-abstract-short" style="display: inline;"> In this paper we present the first comprehensive study of the multi-user capacity of millimeter-wave (mm-wave) urban cellular networks, using site-specific ray-tracing propagation data and realistic antenna array patterns. We compare the performance of TDMA and SDMA (time and spatial division multiple access, respectively) for diverse network scenarios and antenna configurations. We propose a gree… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2002.01450v1-abstract-full').style.display = 'inline'; document.getElementById('2002.01450v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2002.01450v1-abstract-full" style="display: none;"> In this paper we present the first comprehensive study of the multi-user capacity of millimeter-wave (mm-wave) urban cellular networks, using site-specific ray-tracing propagation data and realistic antenna array patterns. We compare the performance of TDMA and SDMA (time and spatial division multiple access, respectively) for diverse network scenarios and antenna configurations. We propose a greedy heuristic algorithm to solve the network-wide directional link allocation problem, thereby estimating the achievable capacity and coverage of multi-user mm-wave networks. Our results show that inter-cell interference is negligible, so that TDMA performance is strictly limited by air-time sharing. By contrast, the major limiting factor for SDMA is intra-cell interference, emphasizing the impact of real antenna array sidelobes. Nonetheless, SDMA significantly outperforms TDMA in terms of average UE throughput, by up to 2 Gbps using 8x8 arrays. As an important design insight, our results show that larger base station antenna arrays limit intra-cell interference while compensating for small UE arrays, reducing costs and beamforming requirements in practical SDMA networks. Our analysis also shows that the limited number of antenna sub-arrays in a practical hybrid beamforming architecture may force SDMA to drop UEs with good coverage, highlighting a tradeoff between base station densification and antenna resources. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2002.01450v1-abstract-full').style.display = 'none'; document.getElementById('2002.01450v1-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> 4 February, 2020; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> February 2020. </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, 17 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/1909.12024">arXiv:1909.12024</a> <span> [<a href="https://arxiv.org/pdf/1909.12024">pdf</a>, <a href="https://arxiv.org/format/1909.12024">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="Networking and Internet Architecture">cs.NI</span> </div> </div> <p class="title is-5 mathjax"> Urban Outdoor Measurement Study of Phased Antenna Array Impact on Millimeter-Wave Link Opportunities and Beam Misalignment </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Kuger%2C+L">Lars Kuger</a>, <a href="/search/eess?searchtype=author&query=Ichkov%2C+A">Aleksandar Ichkov</a>, <a href="/search/eess?searchtype=author&query=M%C3%A4h%C3%B6nen%2C+P">Petri M盲h枚nen</a>, <a href="/search/eess?searchtype=author&query=Simi%C4%87%2C+L">Ljiljana Simi膰</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="1909.12024v2-abstract-short" style="display: inline;"> Exploiting multi-antenna technologies for robust beamsteering to overcome the effects of blockage and beam misalignment is the key to providing seamless multi-Gbps connectivity in millimeter-wave (mm-wave) networks. In this paper, we present the first large-scale outdoor mm-wave measurement study using a phased antenna array in a typical European town. We systematically collect fine-grained 3D ang… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1909.12024v2-abstract-full').style.display = 'inline'; document.getElementById('1909.12024v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1909.12024v2-abstract-full" style="display: none;"> Exploiting multi-antenna technologies for robust beamsteering to overcome the effects of blockage and beam misalignment is the key to providing seamless multi-Gbps connectivity in millimeter-wave (mm-wave) networks. In this paper, we present the first large-scale outdoor mm-wave measurement study using a phased antenna array in a typical European town. We systematically collect fine-grained 3D angle-of-arrival (AoA) and angle-of-departure (AoD) data, totaling over 50,000 received signal strength measurements. We study the impact of phased antenna arrays in terms of number of link opportunities, achievable data rate and robustness under small-scale mobility, and compare this against reference horn antenna measurements. Our results show a limited number of 2--4 link opportunities per receiver location, indicating that the mm-wave multipath richness in a European town is surprisingly similar to that of dense urban metropolises. The results for the phased antenna array reveal that significant losses in estimated data rate occur for beam misalignments in the order of the half-power beamwidth, with significant and irregular variations for larger misalignments. By contrast, the loss for horn antennas is monotonically increasing with the misalignment. Our results strongly suggest that the effect of non-ideal phased antenna arrays must be explicitly considered in the design of agile beamsteering algorithms. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1909.12024v2-abstract-full').style.display = 'none'; document.getElementById('1909.12024v2-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 January, 2020; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 26 September, 2019; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> September 2019. </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, 16 figures</span> </p> </li> </ol> <div class="is-hidden-tablet">  <span class="help" style="display: inline-block;"><a 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