Pub Date : 2025-02-03DOI: 10.1109/JSTSP.2025.3537798
Mengzhen Liu;Ming Li;Rang Liu;Qian Liu
Cell-free massive multi-input multi-output (CF-mMIMO) systems have emerged as a promising paradigm for next-generation wireless communications, offering enhanced spectral efficiency and coverage through distributed antenna arrays. However, the non-linearity of power amplifiers (PAs) in these arrays introduce spatial distortion, which may significantly degrade system performance. This paper presents the first investigation of distortion-aware beamforming in a distributed framework tailored for CF-mMIMO systems, enabling pre-compensation for beam dispersion caused by nonlinear PA distortion. Using a third-order memoryless polynomial distortion model, the impact of the nonlinear PA on the performance of CF-mMIMO systems is firstly analyzed by evaluating the signal-to-interference-noise-and-distortion ratio (SINDR) at user equipment (UE). Then, we develop two distributed distortion-aware beamforming designs based on ring topology and star topology, respectively. In particular, the ring-topology-based fully-distributed approach reduces interconnection costs and computational complexity, while the star-topology-based partially-distributed scheme leverages the superior computation capability of the central processor to achieve improved sum-rate performance. Extensive simulations demonstrate the effectiveness of the proposed distortion-aware beamforming designs in mitigating the effect of nonlinear PA distortion, while also reducing computational complexity and backhaul information exchange in CF-mMIMO systems.
{"title":"Distributed Distortion-Aware Beamforming Designs for Cell-Free mMIMO Systems","authors":"Mengzhen Liu;Ming Li;Rang Liu;Qian Liu","doi":"10.1109/JSTSP.2025.3537798","DOIUrl":"https://doi.org/10.1109/JSTSP.2025.3537798","url":null,"abstract":"Cell-free massive multi-input multi-output (CF-mMIMO) systems have emerged as a promising paradigm for next-generation wireless communications, offering enhanced spectral efficiency and coverage through distributed antenna arrays. However, the non-linearity of power amplifiers (PAs) in these arrays introduce spatial distortion, which may significantly degrade system performance. This paper presents the first investigation of distortion-aware beamforming in a distributed framework tailored for CF-mMIMO systems, enabling pre-compensation for beam dispersion caused by nonlinear PA distortion. Using a third-order memoryless polynomial distortion model, the impact of the nonlinear PA on the performance of CF-mMIMO systems is firstly analyzed by evaluating the signal-to-interference-noise-and-distortion ratio (SINDR) at user equipment (UE). Then, we develop two distributed distortion-aware beamforming designs based on ring topology and star topology, respectively. In particular, the ring-topology-based fully-distributed approach reduces interconnection costs and computational complexity, while the star-topology-based partially-distributed scheme leverages the superior computation capability of the central processor to achieve improved sum-rate performance. Extensive simulations demonstrate the effectiveness of the proposed distortion-aware beamforming designs in mitigating the effect of nonlinear PA distortion, while also reducing computational complexity and backhaul information exchange in CF-mMIMO systems.","PeriodicalId":13038,"journal":{"name":"IEEE Journal of Selected Topics in Signal Processing","volume":"19 2","pages":"381-397"},"PeriodicalIF":8.7,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143900476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The rapid development of Direct-to-device (D2D) services has put forward higher requirements for the performance of satellite antenna systems. The Spatial Ultra-Sparse Distributed Array (SUSDA) constructed by Distributed Satellite Cluster (DSC) has the characteristics of strong directivity, high flexibility and strong anti-jamming ability, which can better meet the communication requirements in future D2D scenarios. However, the non-uniform arrangement of SUSDA leads to the increase of the side lobe level (SLL) and the decrease of the overall antenna performance. To solve this problem, this paper proposes for the first time a configuration design method for a Low Earth Orbit (LEO) SUSDA capable of supporting D2D services in future 6G scenarios. It constructs a mathematical model related to the configuration design of the LEO SUSDA and provides a rapid prediction of the performance of the SUSDA radiation pattern function based on a probabilistic model. Then, an Enhanced Hybrid Particle Swarm Optimization (EHPSO) algorithm is proposed to solve the configuration design problem, which overcomes the slow convergence problem of traditional HPSO algorithm particularly when the array scale is large. The EHPSO algorithm adapts to the search requirements of different stages by adjusting parameters adaptively. It introduces a single suboptimal particle solution to enhance competition and cooperation among particles and employs a local search strategy to precisely narrow the search domain. Simulation results show that the algorithm can significantly reduce the number of iterations and running time of the algorithm while ensuring computational accuracy, which provides a new solution to the configuration design problem of large-scale LEO SUSDA in the future.
{"title":"Spatial Ultra-Sparse Array Formation on LEO Distributed Satellite Cluster: An Enhanced Hybrid Particle Swarm Method","authors":"Yuanzhi He;Peng Yang;Yunying Man;Changxu Wang;Chengwu Qi","doi":"10.1109/JSTSP.2025.3534428","DOIUrl":"https://doi.org/10.1109/JSTSP.2025.3534428","url":null,"abstract":"The rapid development of Direct-to-device (D2D) services has put forward higher requirements for the performance of satellite antenna systems. The Spatial Ultra-Sparse Distributed Array (SUSDA) constructed by Distributed Satellite Cluster (DSC) has the characteristics of strong directivity, high flexibility and strong anti-jamming ability, which can better meet the communication requirements in future D2D scenarios. However, the non-uniform arrangement of SUSDA leads to the increase of the side lobe level (SLL) and the decrease of the overall antenna performance. To solve this problem, this paper proposes for the first time a configuration design method for a Low Earth Orbit (LEO) SUSDA capable of supporting D2D services in future 6G scenarios. It constructs a mathematical model related to the configuration design of the LEO SUSDA and provides a rapid prediction of the performance of the SUSDA radiation pattern function based on a probabilistic model. Then, an Enhanced Hybrid Particle Swarm Optimization (EHPSO) algorithm is proposed to solve the configuration design problem, which overcomes the slow convergence problem of traditional HPSO algorithm particularly when the array scale is large. The EHPSO algorithm adapts to the search requirements of different stages by adjusting parameters adaptively. It introduces a single suboptimal particle solution to enhance competition and cooperation among particles and employs a local search strategy to precisely narrow the search domain. Simulation results show that the algorithm can significantly reduce the number of iterations and running time of the algorithm while ensuring computational accuracy, which provides a new solution to the configuration design problem of large-scale LEO SUSDA in the future.","PeriodicalId":13038,"journal":{"name":"IEEE Journal of Selected Topics in Signal Processing","volume":"19 2","pages":"447-460"},"PeriodicalIF":8.7,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143900528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-27DOI: 10.1109/JSTSP.2025.3533897
Yunxiang Guo;Dongming Wang;Xinjiang Xia;Ziyang Zhang;Jiamin Li;Pengcheng Zhu;Xiaohu You
Cell-free radio access network (CF-RAN) breaks away from the traditional cellular network, forming a scalable wireless access network structure. Based on the conventional cell-free massive multiple input multiple output (CF-mMIMO) system, CF-RAN strategically partitions physical layer functionalities into remote radio unit (RRU), edge distributed unit (EDU) and user-centric distributed unit (UCDU), which enable the CF-mMIMO system to achieve a trade-off between complexity and performance in cooperative transmission. We use scalable full-pilot zero-forcing (FZF) combining/precoding in uplink/downlink and consider the impact of channel estimation error and pilot contamination, the closed-form expressions of uplink/downlink achievable signal-to-interference-noise ratio (SINR) of CF-RAN are given. For both uplink and downlink transmissions, we derive the closed-form achievable rate expressions when channel distribution information (CDI) or channel state information (CSI) is known in signal detection, respectively. Addressing the scalability of CF-RAN, the initial access of user equipment (UE) and dynamic RRU association scheme based on the contention mechanism, multiple RRU-EDU deployment schemes, as well as fractional uplink power control and downlink power allocation is considered. The deployment between RRU and EDU determines the performance of CF-RAN, in which we adopt random deployment, clustering deployment based on k-means algorithm, interleaving deployment based on genetic algorithm (GA), interleaving deployment based on graph coloring algorithm (GCA), respectively. Considering the spatial location randomness of UE and RRU, we model the locations of UE and RRU as two independent binomial point processes (BPP) within a limited area, and derive the expression of user rate coverage probability. Finally, the accuracy of our theoretical results is verified through Monte Carlo simulation.
{"title":"Stochastic Geometry Analysis of Scalable Cell-Free RAN With Dynamic Association and Deployment","authors":"Yunxiang Guo;Dongming Wang;Xinjiang Xia;Ziyang Zhang;Jiamin Li;Pengcheng Zhu;Xiaohu You","doi":"10.1109/JSTSP.2025.3533897","DOIUrl":"https://doi.org/10.1109/JSTSP.2025.3533897","url":null,"abstract":"Cell-free radio access network (CF-RAN) breaks away from the traditional cellular network, forming a scalable wireless access network structure. Based on the conventional cell-free massive multiple input multiple output (CF-mMIMO) system, CF-RAN strategically partitions physical layer functionalities into remote radio unit (RRU), edge distributed unit (EDU) and user-centric distributed unit (UCDU), which enable the CF-mMIMO system to achieve a trade-off between complexity and performance in cooperative transmission. We use scalable full-pilot zero-forcing (FZF) combining/precoding in uplink/downlink and consider the impact of channel estimation error and pilot contamination, the closed-form expressions of uplink/downlink achievable signal-to-interference-noise ratio (SINR) of CF-RAN are given. For both uplink and downlink transmissions, we derive the closed-form achievable rate expressions when channel distribution information (CDI) or channel state information (CSI) is known in signal detection, respectively. Addressing the scalability of CF-RAN, the initial access of user equipment (UE) and dynamic RRU association scheme based on the contention mechanism, multiple RRU-EDU deployment schemes, as well as fractional uplink power control and downlink power allocation is considered. The deployment between RRU and EDU determines the performance of CF-RAN, in which we adopt random deployment, clustering deployment based on k-means algorithm, interleaving deployment based on genetic algorithm (GA), interleaving deployment based on graph coloring algorithm (GCA), respectively. Considering the spatial location randomness of UE and RRU, we model the locations of UE and RRU as two independent binomial point processes (BPP) within a limited area, and derive the expression of user rate coverage probability. Finally, the accuracy of our theoretical results is verified through Monte Carlo simulation.","PeriodicalId":13038,"journal":{"name":"IEEE Journal of Selected Topics in Signal Processing","volume":"19 2","pages":"398-411"},"PeriodicalIF":8.7,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143900475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Achieving perfect Channel State Information at the Transmitter (CSIT) is often infeasible in Extremely Large-scale Antenna Array (ELAA) systems due to user mobility and feedback/processing delay. This results in severe multi-user interference. Therefore, how to effectively and efficiently manage interference with partial/historical CSIT is one of the most important challenges for implementing ELAA. In this paper, we propose a Federated Learning (FL)-assisted predictive beamforming framework for ELAA systems to address this challenge. Specifically, we introduce Rate-Splitting Multiple Access (RSMA) to relax the sensitivity to imperfect CSIT while still benefiting from the spatial resolution. Moreover, a predictive beamforming protocol is designed to optimize the precoder design under the imperfections in the channel estimate quality originating from user mobility and latency. To calculate the beamformers, we first propose a lightweight patch-mixing approach to split the historical CSIT data samples into smaller manageable segments. Then, we propose an FL-based training method that enables parallel processing of these CSI segments, thereby accelerating the training process. Simulation results show the effectiveness and efficacy of the proposed FL-assisted predictive beamforming framework, which paves the way for real-world implementation of ELAA.
{"title":"Federated Learning-Assisted Predictive Beamforming for Extremely Large-Scale Antenna Array Systems With Rate-Splitting Multiple Access","authors":"Shengyu Zhang;Yijie Mao;Zihan Chen;Bruno Clerckx;Tony Q.S. Quek","doi":"10.1109/JSTSP.2025.3532040","DOIUrl":"https://doi.org/10.1109/JSTSP.2025.3532040","url":null,"abstract":"Achieving perfect Channel State Information at the Transmitter (CSIT) is often infeasible in Extremely Large-scale Antenna Array (ELAA) systems due to user mobility and feedback/processing delay. This results in severe multi-user interference. Therefore, how to effectively and efficiently manage interference with partial/historical CSIT is one of the most important challenges for implementing ELAA. In this paper, we propose a Federated Learning (FL)-assisted predictive beamforming framework for ELAA systems to address this challenge. Specifically, we introduce Rate-Splitting Multiple Access (RSMA) to relax the sensitivity to imperfect CSIT while still benefiting from the spatial resolution. Moreover, a predictive beamforming protocol is designed to optimize the precoder design under the imperfections in the channel estimate quality originating from user mobility and latency. To calculate the beamformers, we first propose a lightweight patch-mixing approach to split the historical CSIT data samples into smaller manageable segments. Then, we propose an FL-based training method that enables parallel processing of these CSI segments, thereby accelerating the training process. Simulation results show the effectiveness and efficacy of the proposed FL-assisted predictive beamforming framework, which paves the way for real-world implementation of ELAA.","PeriodicalId":13038,"journal":{"name":"IEEE Journal of Selected Topics in Signal Processing","volume":"19 2","pages":"461-476"},"PeriodicalIF":8.7,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143900587","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-24DOI: 10.1109/JSTSP.2025.3526289
{"title":"IEEE Signal Processing Society Information","authors":"","doi":"10.1109/JSTSP.2025.3526289","DOIUrl":"https://doi.org/10.1109/JSTSP.2025.3526289","url":null,"abstract":"","PeriodicalId":13038,"journal":{"name":"IEEE Journal of Selected Topics in Signal Processing","volume":"18 6","pages":"C3-C3"},"PeriodicalIF":8.7,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10852386","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143106605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-24DOI: 10.1109/JSTSP.2025.3530171
Yinghao Aaron Li;Cong Han;Nima Mesgarani
Text-to-Speech (TTS) has recently seen great progress in synthesizing high-quality speech owing to the rapid development of parallel TTS systems. Yet producing speech with naturalistic prosodic variations, speaking styles, and emotional tones remains challenging. In addition, many existing parallel TTS models often struggle with identifying optimal monotonic alignments since speech and duration generation typically occur independently. Here, we propose StyleTTS, a style-based generative model for parallel TTS that can synthesize diverse speech with natural prosody from a reference speech utterance. Using our novel Transferable Monotonic Aligner (TMA) and duration-invariant data augmentation, StyleTTS significantly outperforms other baseline models on both single and multi-speaker datasets in subjective tests of speech naturalness and synthesized speaker similarity. It also demonstrates higher robustness and emotional similarity to the reference speech as indicated by word error rate (WER) and acoustic feature correlations. Through self-supervised learning, StyleTTS can generate speech with the same emotional and prosodic tone as the reference speech without needing explicit labels for these categories. In addition, when trained with a large number of speakers, our model can perform zero-shot speaker adaption. The source code and audio samples can be found on our demo page at https://styletts.github.io/.
{"title":"StyleTTS: A Style-Based Generative Model for Natural and Diverse Text-to-Speech Synthesis","authors":"Yinghao Aaron Li;Cong Han;Nima Mesgarani","doi":"10.1109/JSTSP.2025.3530171","DOIUrl":"https://doi.org/10.1109/JSTSP.2025.3530171","url":null,"abstract":"Text-to-Speech (TTS) has recently seen great progress in synthesizing high-quality speech owing to the rapid development of parallel TTS systems. Yet producing speech with naturalistic prosodic variations, speaking styles, and emotional tones remains challenging. In addition, many existing parallel TTS models often struggle with identifying optimal monotonic alignments since speech and duration generation typically occur independently. Here, we propose StyleTTS, a style-based generative model for parallel TTS that can synthesize diverse speech with natural prosody from a reference speech utterance. Using our novel Transferable Monotonic Aligner (TMA) and duration-invariant data augmentation, StyleTTS significantly outperforms other baseline models on both single and multi-speaker datasets in subjective tests of speech naturalness and synthesized speaker similarity. It also demonstrates higher robustness and emotional similarity to the reference speech as indicated by word error rate (WER) and acoustic feature correlations. Through self-supervised learning, StyleTTS can generate speech with the same emotional and prosodic tone as the reference speech without needing explicit labels for these categories. In addition, when trained with a large number of speakers, our model can perform zero-shot speaker adaption. The source code and audio samples can be found on our demo page at <uri>https://styletts.github.io/</uri>.","PeriodicalId":13038,"journal":{"name":"IEEE Journal of Selected Topics in Signal Processing","volume":"19 1","pages":"283-296"},"PeriodicalIF":8.7,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143512981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-24DOI: 10.1109/JSTSP.2024.3522438
Yi Ma;Yuejie Chi;Ivan Dokmanić;Bihan Wen;John N. Wright;Zhihui Zhu
{"title":"Editorial Introduction to the Special Issue Seeking Low-Dimensionality in Deep Neural Networks (SLowDNN)","authors":"Yi Ma;Yuejie Chi;Ivan Dokmanić;Bihan Wen;John N. Wright;Zhihui Zhu","doi":"10.1109/JSTSP.2024.3522438","DOIUrl":"https://doi.org/10.1109/JSTSP.2024.3522438","url":null,"abstract":"","PeriodicalId":13038,"journal":{"name":"IEEE Journal of Selected Topics in Signal Processing","volume":"18 6","pages":"980-984"},"PeriodicalIF":8.7,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10852363","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143106517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-24DOI: 10.1109/JSTSP.2025.3526293
{"title":"IEEE Signal Processing Society Information","authors":"","doi":"10.1109/JSTSP.2025.3526293","DOIUrl":"https://doi.org/10.1109/JSTSP.2025.3526293","url":null,"abstract":"","PeriodicalId":13038,"journal":{"name":"IEEE Journal of Selected Topics in Signal Processing","volume":"18 6","pages":"C2-C2"},"PeriodicalIF":8.7,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10852354","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143106515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-23DOI: 10.1109/JSTSP.2025.3533111
Alessio Fascista;Benjamin J. B. Deutschmann;Musa Furkan Keskin;Thomas Wilding;Angelo Coluccia;Klaus Witrisal;Erik Leitinger;Gonzalo Seco-Granados;Henk Wymeersch
Extremely large-scale antenna array (ELAA) systems emerge as a promising technology in beyond 5G and 6G wireless networks to support the deployment of distributed architectures. This paper explores the use of ELAAs to enable joint localization, synchronization and mapping in sub-6 GHz uplink channels, capitalizing on the near-field effects of phase-coherent distributed arrays. We focus on a scenario where a single-antenna user equipment (UE) communicates with a network of access points (APs) distributed in an indoor environment, considering both specular reflections from walls and scattering from objects. The UE is assumed to be unsynchronized to the network, while the APs can be time- and phase-synchronized to each other. We formulate the problem of joint estimation of location, clock offset and phase offset of the UE, and the locations of scattering points (SPs) (i.e., mapping). Through comprehensive Fisher information analysis, we assess the impact of bandwidth, AP array size, wall reflections, SPs and phase synchronization on localization accuracy. Furthermore, we derive the maximum likelihood (ML) estimator for the joint localization, synchronization, and mapping problem, which optimally combines the information collected by all the distributed arrays. To overcome its intractable high dimensionality, we propose a novel three-stage algorithm that first estimates phase offset leveraging carrier phase information of line-of-sight (LoS) paths, then determines the UE location and clock offset via LoS paths and wall reflections, and finally locates SPs using a null-space transformation technique. Simulation results demonstrate the effectiveness of our approach in distributed architectures supported by radio stripes (RSs)—an innovative alternative for implementing ELAAs—while revealing the benefits of carrier phase exploitation and showcasing the interplay between delay and angular information under different bandwidth regimes.
{"title":"Joint Localization, Synchronization and Mapping via Phase-Coherent Distributed Arrays","authors":"Alessio Fascista;Benjamin J. B. Deutschmann;Musa Furkan Keskin;Thomas Wilding;Angelo Coluccia;Klaus Witrisal;Erik Leitinger;Gonzalo Seco-Granados;Henk Wymeersch","doi":"10.1109/JSTSP.2025.3533111","DOIUrl":"https://doi.org/10.1109/JSTSP.2025.3533111","url":null,"abstract":"Extremely large-scale antenna array (ELAA) systems emerge as a promising technology in beyond 5G and 6G wireless networks to support the deployment of distributed architectures. This paper explores the use of ELAAs to enable joint localization, synchronization and mapping in sub-6 GHz uplink channels, capitalizing on the near-field effects of phase-coherent distributed arrays. We focus on a scenario where a single-antenna user equipment (UE) communicates with a network of access points (APs) distributed in an indoor environment, considering both specular reflections from walls and scattering from objects. The UE is assumed to be unsynchronized to the network, while the APs can be time- and phase-synchronized to each other. We formulate the problem of joint estimation of location, clock offset and phase offset of the UE, and the locations of scattering points (SPs) (i.e., mapping). Through comprehensive Fisher information analysis, we assess the impact of bandwidth, AP array size, wall reflections, SPs and phase synchronization on localization accuracy. Furthermore, we derive the maximum likelihood (ML) estimator for the joint localization, synchronization, and mapping problem, which optimally combines the information collected by all the distributed arrays. To overcome its intractable high dimensionality, we propose a novel three-stage algorithm that first estimates phase offset leveraging carrier phase information of line-of-sight (LoS) paths, then determines the UE location and clock offset via LoS paths and wall reflections, and finally locates SPs using a null-space transformation technique. Simulation results demonstrate the effectiveness of our approach in distributed architectures supported by radio stripes (RSs)—an innovative alternative for implementing ELAAs—while revealing the benefits of carrier phase exploitation and showcasing the interplay between delay and angular information under different bandwidth regimes.","PeriodicalId":13038,"journal":{"name":"IEEE Journal of Selected Topics in Signal Processing","volume":"19 2","pages":"412-429"},"PeriodicalIF":8.7,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143900572","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-23DOI: 10.1109/JSTSP.2025.3533115
Neng Ye;Sirui Miao;Jianxiong Pan;Yiyue Xiang;Shahid Mumtaz
Mega constellation, as an extremely large-scale radio access network, faces severe multi-user interference when accommodating ubiquitous access. Distributed multi-user detection (MUD) can utilize the multi-satellite spatial diversities and processing capabilities to alleviate inter-user interference. However, the spaceborne nature makes it seriously chained by inter-satellite link (ISL) constraints including the limited number and the constrained bandwidth of ISL ports. Therefore, this paper proposes an efficient message passing (MP) based distributed MUD framework under stringent ISL constraints. First, the overheads on ISL ports and bandwidth introduced by fully-connected distributed MUD are quantitatively characterized using distributed factor graph (FG) model. On this basis, we propose two ISL-compatible design principles for distributed MUD, i.e., orchestrating message flow (MF) hierarchically among satellites to save ports, and propagating messages selectively to save bandwidth. Specifically, a novel multi-branch tree-like MF orchestration is proposed to forward and aggregate the locally generated detection messages in a partially-connected manner. The relationship between MF structure and overall performance is revealed via EXIT chart and a fairness-aware orchestration algorithm is developed. Further, we introduce a novel squeeze node into the distributed FG, compressing messages and facilitating selective MP under bandwidth constraint. Three criteria are correspondingly proposed to identify the most effective messages for distributed MUD. Our proposed MUD framework is evaluated under practical settings, which demonstrates a reduction of 50% ISL bandwidth costs with less than 1 dB loss in terms of BER compared to the fully-connected MUD, and achieves up to 5 dB gain in BER over the state-of-the-art distributed reception methods.
{"title":"Dancing With Chains: Spaceborne Distributed Multi-User Detection Under Inter-Satellite Link Constraints","authors":"Neng Ye;Sirui Miao;Jianxiong Pan;Yiyue Xiang;Shahid Mumtaz","doi":"10.1109/JSTSP.2025.3533115","DOIUrl":"https://doi.org/10.1109/JSTSP.2025.3533115","url":null,"abstract":"Mega constellation, as an extremely large-scale radio access network, faces severe multi-user interference when accommodating ubiquitous access. Distributed multi-user detection (MUD) can utilize the multi-satellite spatial diversities and processing capabilities to alleviate inter-user interference. However, the spaceborne nature makes it seriously chained by inter-satellite link (ISL) constraints including the limited number and the constrained bandwidth of ISL ports. Therefore, this paper proposes an efficient message passing (MP) based distributed MUD framework under stringent ISL constraints. First, the overheads on ISL ports and bandwidth introduced by fully-connected distributed MUD are quantitatively characterized using distributed factor graph (FG) model. On this basis, we propose two ISL-compatible design principles for distributed MUD, i.e., orchestrating message flow (MF) hierarchically among satellites to save ports, and propagating messages selectively to save bandwidth. Specifically, a novel multi-branch tree-like MF orchestration is proposed to forward and aggregate the locally generated detection messages in a partially-connected manner. The relationship between MF structure and overall performance is revealed via EXIT chart and a fairness-aware orchestration algorithm is developed. Further, we introduce a novel squeeze node into the distributed FG, compressing messages and facilitating selective MP under bandwidth constraint. Three criteria are correspondingly proposed to identify the most effective messages for distributed MUD. Our proposed MUD framework is evaluated under practical settings, which demonstrates a reduction of 50% ISL bandwidth costs with less than 1 dB loss in terms of BER compared to the fully-connected MUD, and achieves up to 5 dB gain in BER over the state-of-the-art distributed reception methods.","PeriodicalId":13038,"journal":{"name":"IEEE Journal of Selected Topics in Signal Processing","volume":"19 2","pages":"430-446"},"PeriodicalIF":8.7,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143900586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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