IEEE Journal of Selected Topics in Signal Processing最新文献_第3页

Decentralized MIMO Systems With Imperfect CSI Using LMMSE Receivers 使用LMMSE接收器的不完美CSI分散MIMO系统

IF 8.7 1区工程技术

IEEE Journal of Selected Topics in Signal Processing Pub Date : 2025-02-10 DOI: 10.1109/JSTSP.2025.3539098

Zeyan Zhuang;Xin Zhang;Dongfang Xu;Shenghui Song;Yonina C. Eldar

{"title":"Decentralized MIMO Systems With Imperfect CSI Using LMMSE Receivers","authors":"Zeyan Zhuang;Xin Zhang;Dongfang Xu;Shenghui Song;Yonina C. Eldar","doi":"10.1109/JSTSP.2025.3539098","DOIUrl":"https://doi.org/10.1109/JSTSP.2025.3539098","url":null,"abstract":"Centralized baseband processing (CBP) is required to achieve the full potential of massive multiple-input multiple-output (MIMO) systems. However, due to the large number of antennas, CBP suffers from two major issues: 1) Extensive data interconnection between radio frequency (RF) circuitry and the central processing unit; and 2) high-dimensional computation. To this end, decentralized baseband processing (DBP) has been proposed, where the antennas at the base station are partitioned into clusters connected to separate RF circuits and equipped with separate computing units. However, the optimal fusion scheme that maximizes signal-to-interference-and-noise ratio (SINR) and the related performance analysis for DBP with general spatial correlation and imperfect channel state information (CSI) have not been studied. In this paper, we consider a decentralized MIMO system where all clusters adopt linear minimum mean-square error (LMMSE) receivers. We first establish an optimal linear fusion scheme that has high computational and data input/output costs. To reduce the cost, we then propose two suboptimal fusion schemes with reduced complexity. For all three schemes, we study the SINR performance by leveraging random matrix theory and demonstrate conditions under which the suboptimal schemes are optimal. Furthermore, we determine the optimal regularization parameter for the LMMSE receiver, identify the best antenna partitioning strategy, and prove that the SINR will decrease as the number of clusters increases. Numerical simulations validate the accuracy of the theoretical results.","PeriodicalId":13038,"journal":{"name":"IEEE Journal of Selected Topics in Signal Processing","volume":"19 2","pages":"331-348"},"PeriodicalIF":8.7,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143900474","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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IEEE Signal Processing Society Information IEEE信号处理学会信息

IF 8.7 1区工程技术

IEEE Journal of Selected Topics in Signal Processing Pub Date : 2025-02-05 DOI: 10.1109/JSTSP.2025.3535108

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IEEE Signal Processing Society Information IEEE信号处理学会信息

IF 8.7 1区工程技术

IEEE Journal of Selected Topics in Signal Processing Pub Date : 2025-02-05 DOI: 10.1109/JSTSP.2025.3535110

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List of Reviewers 2024 2024 年审查员名单

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IEEE Journal of Selected Topics in Signal Processing Pub Date : 2025-02-05 DOI: 10.1109/JSTSP.2025.3534376

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Editorial JSTSP NSAC Editorial 编辑JSTSP NSAC编辑

IF 8.7 1区工程技术

IEEE Journal of Selected Topics in Signal Processing Pub Date : 2025-02-05 DOI: 10.1109/JSTSP.2024.3522737

Jan Skoglund;Minje Kim;Xiulian Peng;Lars Villemoes

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Distributed Distortion-Aware Beamforming Designs for Cell-Free mMIMO Systems 无小区mimo系统的分布式畸变感知波束形成设计

IF 8.7 1区工程技术

IEEE Journal of Selected Topics in Signal Processing Pub Date : 2025-02-03 DOI: 10.1109/JSTSP.2025.3537798

Mengzhen Liu;Ming Li;Rang Liu;Qian Liu

{"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}

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Spatial Ultra-Sparse Array Formation on LEO Distributed Satellite Cluster: An Enhanced Hybrid Particle Swarm Method LEO分布式卫星簇空间超稀疏阵列形成：一种增强的混合粒子群方法

IF 8.7 1区工程技术

IEEE Journal of Selected Topics in Signal Processing Pub Date : 2025-01-27 DOI: 10.1109/JSTSP.2025.3534428

Yuanzhi He;Peng Yang;Yunying Man;Changxu Wang;Chengwu Qi

{"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}

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Stochastic Geometry Analysis of Scalable Cell-Free RAN With Dynamic Association and Deployment 具有动态关联和部署的可扩展无小区无线局域网的随机几何分析

IF 8.7 1区工程技术

IEEE Journal of Selected Topics in Signal Processing Pub Date : 2025-01-27 DOI: 10.1109/JSTSP.2025.3533897

Yunxiang Guo;Dongming Wang;Xinjiang Xia;Ziyang Zhang;Jiamin Li;Pengcheng Zhu;Xiaohu You

{"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}

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IEEE Journal of Selected Topics in Signal Processing Pub Date : 2025-01-24 DOI: 10.1109/JSTSP.2025.3526289

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Federated Learning-Assisted Predictive Beamforming for Extremely Large-Scale Antenna Array Systems With Rate-Splitting Multiple Access 具有速率分裂多址的超大型天线阵列系统的联邦学习辅助预测波束形成

IF 8.7 1区工程技术

IEEE Journal of Selected Topics in Signal Processing Pub Date : 2025-01-24 DOI: 10.1109/JSTSP.2025.3532040

Shengyu Zhang;Yijie Mao;Zihan Chen;Bruno Clerckx;Tony Q.S. Quek

{"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}

引用次数: 0