Pub Date : 2026-01-19DOI: 10.1109/TWC.2026.3653252
Byunghyun Lee;Rang Liu;David J. Love;James V. Krogmeier;A. Lee Swindlehurst
Polarization diversity offers a cost- and space-efficient solution to enhance the performance of integrated sensing and communication systems. Polarimetric sensing exploits the signal’s polarity to extract details about the target such as shape, pose, and material composition. From a communication perspective, polarization diversity can enhance the reliability and throughput of communication channels. This paper proposes an integrated polarimetric sensing and communication (IPSAC) system that jointly conducts polarimetric sensing and communications. We study the use of single-port polarization-reconfigurable antennas to adapt to channel depolarization effects, without the need for separate RF chains for each polarization. We address two core sensing tasks in IPSAC systems, target parameter estimation and target detection. For parameter estimation, we consider the problem of minimizing the mean square error (MSE) of the target depolarization parameter estimate, which is a critical task for various polarimetric radar applications such as rainfall forecasting, vegetation identification, and target classification. To address this nonconvex problem, we apply semi-definite relaxation (SDR) and majorization-minimization (MM) optimization techniques. Next, we consider a design that maximizes the target signal-to-interference-plus-noise ratio (SINR) leveraging prior knowledge of the target and clutter depolarization statistics to enhance the target detection performance. To tackle this problem, we modify the solution developed for MSE minimization subject to the same quality-of-service (QoS) constraints. Extensive simulations show that the proposed polarization reconfiguration method substantially improves the depolarization parameter MSE. Furthermore, the proposed method considerably boosts the target SINR due to polarization diversity, particularly in cluttered environments.
{"title":"Integrated Polarimetric Sensing and Communication With Polarization-Reconfigurable Arrays","authors":"Byunghyun Lee;Rang Liu;David J. Love;James V. Krogmeier;A. Lee Swindlehurst","doi":"10.1109/TWC.2026.3653252","DOIUrl":"10.1109/TWC.2026.3653252","url":null,"abstract":"Polarization diversity offers a cost- and space-efficient solution to enhance the performance of integrated sensing and communication systems. Polarimetric sensing exploits the signal’s polarity to extract details about the target such as shape, pose, and material composition. From a communication perspective, polarization diversity can enhance the reliability and throughput of communication channels. This paper proposes an integrated polarimetric sensing and communication (IPSAC) system that jointly conducts polarimetric sensing and communications. We study the use of single-port polarization-reconfigurable antennas to adapt to channel depolarization effects, without the need for separate RF chains for each polarization. We address two core sensing tasks in IPSAC systems, target parameter estimation and target detection. For parameter estimation, we consider the problem of minimizing the mean square error (MSE) of the target depolarization parameter estimate, which is a critical task for various polarimetric radar applications such as rainfall forecasting, vegetation identification, and target classification. To address this nonconvex problem, we apply semi-definite relaxation (SDR) and majorization-minimization (MM) optimization techniques. Next, we consider a design that maximizes the target signal-to-interference-plus-noise ratio (SINR) leveraging prior knowledge of the target and clutter depolarization statistics to enhance the target detection performance. To tackle this problem, we modify the solution developed for MSE minimization subject to the same quality-of-service (QoS) constraints. Extensive simulations show that the proposed polarization reconfiguration method substantially improves the depolarization parameter MSE. Furthermore, the proposed method considerably boosts the target SINR due to polarization diversity, particularly in cluttered environments.","PeriodicalId":13431,"journal":{"name":"IEEE Transactions on Wireless Communications","volume":"25 ","pages":"10618-10634"},"PeriodicalIF":10.7,"publicationDate":"2026-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146001084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-16DOI: 10.1109/TWC.2026.3652154
Lihao Zhang;Haijian Sun;Samuel Berweger;Camillo Gentile;Rose Qingyang Hu
Precisely modeling radio propagation in complex environments has been a significant challenge, especially with the advent of 5G and beyond networks, where managing massive antenna arrays demands more detailed information. Traditional methods, such as empirical models and ray tracing, often fall short, either due to insufficient details or because of challenges for real-time applications. Inspired by the newly proposed 3D Gaussian Splatting method in the computer vision domain, which outperforms other methods in reconstructing optical radiance fields, we propose RF-3DGS, a novel approach that enables precise site-specific reconstruction of radio radiance fields from sparse samples. RF-3DGS offers high efficiency, requiring only a few minutes for training and achieving fast inference for any arbitrary receiver pose within milliseconds. Furthermore, RF-3DGS can provide fine-grained Spatial Channel State Information (Spatial-CSI) of these paths, including the channel gain, the delay, the angle of arrival (AoA), and the angle of departure (AoD). Our experiments, calibrated through real-world measurements, demonstrate that RF-3DGS not only significantly improves reconstruction quality, training efficiency, and rendering speed compared to state-of-the-art methods, but also holds great potential for supporting wireless communication and advanced applications such as Integrated Sensing and Communication (ISAC). Code and dataset are available at https://github.com/SunLab-UGA/RF-3DGS
{"title":"RF-3DGS: Wireless Channel Modeling With Radio Radiance Field and 3D Gaussian Splatting","authors":"Lihao Zhang;Haijian Sun;Samuel Berweger;Camillo Gentile;Rose Qingyang Hu","doi":"10.1109/TWC.2026.3652154","DOIUrl":"https://doi.org/10.1109/TWC.2026.3652154","url":null,"abstract":"Precisely modeling radio propagation in complex environments has been a significant challenge, especially with the advent of 5G and beyond networks, where managing massive antenna arrays demands more detailed information. Traditional methods, such as empirical models and ray tracing, often fall short, either due to insufficient details or because of challenges for real-time applications. Inspired by the newly proposed 3D Gaussian Splatting method in the computer vision domain, which outperforms other methods in reconstructing optical radiance fields, we propose RF-3DGS, a novel approach that enables precise site-specific reconstruction of radio radiance fields from sparse samples. RF-3DGS offers high efficiency, requiring only a few minutes for training and achieving fast inference for any arbitrary receiver pose within milliseconds. Furthermore, RF-3DGS can provide fine-grained Spatial Channel State Information (Spatial-CSI) of these paths, including the channel gain, the delay, the angle of arrival (AoA), and the angle of departure (AoD). Our experiments, calibrated through real-world measurements, demonstrate that RF-3DGS not only significantly improves reconstruction quality, training efficiency, and rendering speed compared to state-of-the-art methods, but also holds great potential for supporting wireless communication and advanced applications such as Integrated Sensing and Communication (ISAC). Code and dataset are available at <uri>https://github.com/SunLab-UGA/RF-3DGS</uri>","PeriodicalId":13431,"journal":{"name":"IEEE Transactions on Wireless Communications","volume":"25 ","pages":"10419-10433"},"PeriodicalIF":10.7,"publicationDate":"2026-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145982228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The integration of multicarrier modulation and multiple-input-multiple-output (MIMO) is critical for reliable transmission of wireless signals in complex environments, which significantly improve spectrum efficiency. Existing studies have shown that popular orthogonal time frequency space (OTFS) and affine frequency division multiplexing (AFDM) offer significant advantages over orthogonal frequency division multiplexing (OFDM) in uncoded doubly selective channels. However, it remains uncertain whether these benefits extend to coded systems. Meanwhile, the information-theoretic limit analysis of coded MIMO multicarrier systems and the corresponding low-complexity receiver design remain unclear. To overcome these challenges, this paper proposes a multi-slot cross-domain memory approximate message passing (MS-CD-MAMP) receiver as well as develops its information-theoretic (i.e., achievable rate) limit and optimal coding principle for MIMO-multicarrier modulation (e.g., OFDM, OTFS, and AFDM) systems. The proposed MS-CD-MAMP receiver can exploit not only the time domain channel sparsity for low complexity but also the corresponding symbol domain constellation constraints for performance enhancement. Meanwhile, limited by the high-dimensional complex state evolution (SE), a simplified single-input single-output variational SE is proposed to derive the achievable rate of MS-CD-MAMP and the optimal coding principle with the goal of maximizing the achievable rate. Numerical results show that coded MIMO-OFDM/OTFS/AFDM with MS-CD-MAMP achieve the same maximum achievable rate in doubly selective channels, whose finite-length performance with practical optimized low-density parity-check (LDPC) codes is only $0.5sim 1.8$ dB away from the associated theoretical limit, and has $0.8sim 4.4$ dB gain over the well-designed point-to-point LDPC codes.
{"title":"Achievable Rate and Coding Principle for MIMO Multicarrier Systems With Cross-Domain MAMP Receiver Over Doubly Selective Channels","authors":"Yuhao Chi;Zhiyuan Peng;Lei Liu;Ying Li;Yao Ge;Chau Yuen","doi":"10.1109/TWC.2026.3652964","DOIUrl":"https://doi.org/10.1109/TWC.2026.3652964","url":null,"abstract":"The integration of multicarrier modulation and multiple-input-multiple-output (MIMO) is critical for reliable transmission of wireless signals in complex environments, which significantly improve spectrum efficiency. Existing studies have shown that popular orthogonal time frequency space (OTFS) and affine frequency division multiplexing (AFDM) offer significant advantages over orthogonal frequency division multiplexing (OFDM) in uncoded doubly selective channels. However, it remains uncertain whether these benefits extend to coded systems. Meanwhile, the information-theoretic limit analysis of coded MIMO multicarrier systems and the corresponding low-complexity receiver design remain unclear. To overcome these challenges, this paper proposes a multi-slot cross-domain memory approximate message passing (MS-CD-MAMP) receiver as well as develops its information-theoretic (i.e., achievable rate) limit and optimal coding principle for MIMO-multicarrier modulation (e.g., OFDM, OTFS, and AFDM) systems. The proposed MS-CD-MAMP receiver can exploit not only the time domain channel sparsity for low complexity but also the corresponding symbol domain constellation constraints for performance enhancement. Meanwhile, limited by the high-dimensional complex state evolution (SE), a simplified single-input single-output variational SE is proposed to derive the achievable rate of MS-CD-MAMP and the optimal coding principle with the goal of maximizing the achievable rate. Numerical results show that coded MIMO-OFDM/OTFS/AFDM with MS-CD-MAMP achieve the same maximum achievable rate in doubly selective channels, whose finite-length performance with practical optimized low-density parity-check (LDPC) codes is only <inline-formula> <tex-math>$0.5sim 1.8$ </tex-math></inline-formula> dB away from the associated theoretical limit, and has <inline-formula> <tex-math>$0.8sim 4.4$ </tex-math></inline-formula> dB gain over the well-designed point-to-point LDPC codes.","PeriodicalId":13431,"journal":{"name":"IEEE Transactions on Wireless Communications","volume":"25 ","pages":"10354-10370"},"PeriodicalIF":10.7,"publicationDate":"2026-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145982137","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-16DOI: 10.1109/twc.2026.3652128
Yue Xiu, Yang Zhao, Ran Yang, Wanting Lyu, Dusit Niyato, Dong In Kim, Guangyi Liu, Ning Wei
{"title":"Robust Optimization for Movable Antenna-Aided Cell-Free ISAC With Time Synchronization Errors","authors":"Yue Xiu, Yang Zhao, Ran Yang, Wanting Lyu, Dusit Niyato, Dong In Kim, Guangyi Liu, Ning Wei","doi":"10.1109/twc.2026.3652128","DOIUrl":"https://doi.org/10.1109/twc.2026.3652128","url":null,"abstract":"","PeriodicalId":13431,"journal":{"name":"IEEE Transactions on Wireless Communications","volume":"58 1","pages":""},"PeriodicalIF":10.4,"publicationDate":"2026-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145993263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-16DOI: 10.1109/TWC.2025.3645992
Eunsun Kim;Ian P. Roberts;Taekyun Lee;Jeffrey G. Andrews
We study spectrum sharing between two dense low-earth orbit (LEO) satellite constellations, an incumbent primary system and a secondary system that must respect interference protection constraints on the primary system. In particular, we propose a secondary satellite selection framework and algorithm that maximizes capacity while guaranteeing that the time-average interference and absolute interference inflicted upon each primary ground user never exceeds specified thresholds. We solve this NP-hard constrained, combinatorial satellite selection problem through Lagrangian relaxation to decompose it into simpler problems which can then be solved through subgradient methods. A high-fidelity simulation is developed based on public FCC filings and technical specifications of the Starlink and Kuiper systems. We use this case study to illustrate the effectiveness of our approach and that explicit protection is indeed necessary for healthy coexistence. We further demonstrate that deep learning models can be used to predict the primary satellite system associations, which helps the secondary system avoid inflicting excessive interference and maximize its own capacity.
{"title":"Satellite Selection for In-Band Coexistence of Dense LEO Networks","authors":"Eunsun Kim;Ian P. Roberts;Taekyun Lee;Jeffrey G. Andrews","doi":"10.1109/TWC.2025.3645992","DOIUrl":"https://doi.org/10.1109/TWC.2025.3645992","url":null,"abstract":"We study spectrum sharing between two dense low-earth orbit (LEO) satellite constellations, an incumbent primary system and a secondary system that must respect interference protection constraints on the primary system. In particular, we propose a secondary satellite selection framework and algorithm that maximizes capacity while guaranteeing that the time-average interference and absolute interference inflicted upon each primary ground user never exceeds specified thresholds. We solve this NP-hard constrained, combinatorial satellite selection problem through Lagrangian relaxation to decompose it into simpler problems which can then be solved through subgradient methods. A high-fidelity simulation is developed based on public FCC filings and technical specifications of the Starlink and Kuiper systems. We use this case study to illustrate the effectiveness of our approach and that explicit protection is indeed necessary for healthy coexistence. We further demonstrate that deep learning models can be used to predict the primary satellite system associations, which helps the secondary system avoid inflicting excessive interference and maximize its own capacity.","PeriodicalId":13431,"journal":{"name":"IEEE Transactions on Wireless Communications","volume":"25 ","pages":"10274-10289"},"PeriodicalIF":10.7,"publicationDate":"2026-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145982136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Utilizing communication signals to extract motion parameters has emerged as a key direction in Vehicle-to-Everything (V2X) networks. Accurately modeling the relationship between communication signals and sensing performance is critical for the advancement of such systems. Unlike prior work that relies primarily on qualitative analysis, this paper derives the Cramér-Rao Bound (CRB) for radar parameter estimation in the context of Orthogonal Frequency Division Multiplexing (OFDM) waveforms and Uniform Planar Array (UPA) configurations. Recognizing that vehicles may act as extended targets, we propose two New Radio (NR)-V2X-compatible beamforming schemes tailored to different phases of the communication process. During the initial beam establishment phase, we develop a beamforming approach based on the union of predictive error ellipses, which enhances scatterer localization through temporally assisted beam training. In the beam adjustment phase, we introduce an adaptive narrowest-beam strategy that leverages the positions of scatterers and the communication receiver (CR), enabling effective tracking with reduced complexity. The beam design problem is addressed using the minimum enclosing ellipse algorithm and tailored antenna control methods. Simulation results validate the proposed approach, showing up to a 32.4% improvement in achievable rate with a $32times 32$ transmit antenna array and a 5.2% gain with an $8times 8$ array, compared to conventional beam sweeping under identical SNR conditions.
{"title":"Extended Target Adaptive Beamforming for ISAC: A Perspective of Predictive Error Ellipse","authors":"Shengcai Zhou;Luping Xiang;Yi Wang;Kun Yang;Kai Kit Wong;Chan-Byoung Chae","doi":"10.1109/TWC.2026.3652714","DOIUrl":"10.1109/TWC.2026.3652714","url":null,"abstract":"Utilizing communication signals to extract motion parameters has emerged as a key direction in Vehicle-to-Everything (V2X) networks. Accurately modeling the relationship between communication signals and sensing performance is critical for the advancement of such systems. Unlike prior work that relies primarily on qualitative analysis, this paper derives the Cramér-Rao Bound (CRB) for radar parameter estimation in the context of Orthogonal Frequency Division Multiplexing (OFDM) waveforms and Uniform Planar Array (UPA) configurations. Recognizing that vehicles may act as extended targets, we propose two New Radio (NR)-V2X-compatible beamforming schemes tailored to different phases of the communication process. During the initial beam establishment phase, we develop a beamforming approach based on the union of predictive error ellipses, which enhances scatterer localization through temporally assisted beam training. In the beam adjustment phase, we introduce an adaptive narrowest-beam strategy that leverages the positions of scatterers and the communication receiver (CR), enabling effective tracking with reduced complexity. The beam design problem is addressed using the minimum enclosing ellipse algorithm and tailored antenna control methods. Simulation results validate the proposed approach, showing up to a 32.4% improvement in achievable rate with a <inline-formula> <tex-math>$32times 32$ </tex-math></inline-formula> transmit antenna array and a 5.2% gain with an <inline-formula> <tex-math>$8times 8$ </tex-math></inline-formula> array, compared to conventional beam sweeping under identical SNR conditions.","PeriodicalId":13431,"journal":{"name":"IEEE Transactions on Wireless Communications","volume":"25 ","pages":"10604-10617"},"PeriodicalIF":10.7,"publicationDate":"2026-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145993265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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