IEEE Transactions on Signal Processing最新文献_第6页

Stochastic Frank-Wolfe Algorithm for Constrained Bilevel Optimization With Improved Per-Iteration Complexity 改进迭代复杂度的约束双层优化随机Frank-Wolfe算法

IF 5.8 2区工程技术

IEEE Transactions on Signal Processing Pub Date : 2025-08-08 DOI: 10.1109/TSP.2025.3596231

Jie Hou;Xianlin Zeng;Shisheng Cui;Xia Jiang;Jian Sun

引用次数: 0

Channel Estimation and Sum Rate Analysis of Comparator Network-Aided MIMO Receivers With 1-Bit ADCs 带1位adc的比较器网络辅助MIMO接收机的信道估计和和率分析

IF 5.8 2区工程技术

IEEE Transactions on Signal Processing Pub Date : 2025-08-06 DOI: 10.1109/TSP.2025.3596521

Luiz Sampaio;Lukas T. N. Landau

引用次数: 0

Direct Localization with Direct-path Interference for Reference Channel-free Distributed Passive Radars 参考无信道分布式无源雷达直接路径干扰直接定位

IF 5.4 2区工程技术

IEEE Transactions on Signal Processing Pub Date : 2025-08-06 DOI: 10.1109/tsp.2025.3595854

Qiyu Zhou, Ye Yuan, Hongbin Li, Maria Sabrina Greco, Fulvio Gini, Wei Yi

引用次数: 0

Direct multi-emitter tracking based on the generalized labeled multi-Bernoulli filter 基于广义标记多伯努利滤波器的多发射器直接跟踪

IF 5.4 2区工程技术

IEEE Transactions on Signal Processing Pub Date : 2025-08-06 DOI: 10.1109/tsp.2025.3595842

Yiqi Chen, Lin Gao, Luigi Chisci, Ping Wei, Huaguo Zhang, Alfonso Farina

引用次数: 0

Mitigating Spatial-Wideband and Beam-Split Effects via Distributed IRSs: Design and Analysis 通过分布式IRSs减轻空间宽带和波束分裂效应：设计与分析

IF 5.8 2区工程技术

IEEE Transactions on Signal Processing Pub Date : 2025-08-06 DOI: 10.1109/TSP.2025.3593416

L. Yashvanth;Chandra R. Murthy;Bhaskar D. Rao

{"title":"Mitigating Spatial-Wideband and Beam-Split Effects via Distributed IRSs: Design and Analysis","authors":"L. Yashvanth;Chandra R. Murthy;Bhaskar D. Rao","doi":"10.1109/TSP.2025.3593416","DOIUrl":"10.1109/TSP.2025.3593416","url":null,"abstract":"This paper addresses the mitigation of spatial-wideband (SW) and the resulting beam-split (B-SP) effects in intelligent reflecting surface (IRS)-aided wideband systems. The SW effect occurs when the signal delay across the IRS aperture exceeds the system’s sampling duration, causing the user equipment’s (UE) channel angle to vary with frequency. This leads to the B-SP effect, wherein the IRS cannot coherently beamform to a given UE over the entire bandwidth, reducing array gain and throughput. We first show that partitioning a single IRS into multiple smaller IRSs and distributing them in the environment can naturally mitigate the SW effect (and hence the B-SP effect) by parallelizing the spatial delays and exploiting angle diversity benefits. Next, by determining the maximum number of elements at each smaller IRS to limit B-SP effects and analyzing the achievable sum-rate, we demonstrate that our approach ensures a minimum positive rate over the entire bandwidth of operation. However, distributed IRSs may introduce temporal delay spread (TDS) due to the differences in the path lengths through the IRSs and this may reduce the achievable flat channel gain. To minimize TDS and maintain the full array gain, we show that the optimal placement of the IRSs is on an ellipse with the base station (BS) and UE as the focal points. We also analyze the impact of the optimal IRS placement on TDS and throughput for a UE that is located within a hotspot served by the IRSs. Finally, we illustrate that distributed IRSs enhance angle diversity, which exponentially reduces the outage probability due to B-SP effects as the number of IRSs increases. Numerical results validate the efficacy and simplicity of our method compared to the existing solutions.","PeriodicalId":13330,"journal":{"name":"IEEE Transactions on Signal Processing","volume":"73 ","pages":"3286-3301"},"PeriodicalIF":5.8,"publicationDate":"2025-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144792554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Sparsity-Enhanced Multilayered Non-Convex Regularization with Epigraphical Relaxation for Debiased Signal Recovery 稀疏增强多层非凸正则化及其在去偏信号恢复中的应用

IF 5.4 2区工程技术

IEEE Transactions on Signal Processing Pub Date : 2025-08-06 DOI: 10.1109/tsp.2025.3596248

Akari Katsuma, Seisuke Kyochi, Shunsuke Ono, Ivan Selesnick

引用次数: 0

On Purely Data-Driven Massive MIMO Detectors 纯数据驱动的大规模MIMO探测器

IF 5.8 2区工程技术

IEEE Transactions on Signal Processing Pub Date : 2025-08-05 DOI: 10.1109/TSP.2025.3594197

Hao Ye;Le Liang

{"title":"On Purely Data-Driven Massive MIMO Detectors","authors":"Hao Ye;Le Liang","doi":"10.1109/TSP.2025.3594197","DOIUrl":"10.1109/TSP.2025.3594197","url":null,"abstract":"The development of learning-based detectors for massive multi-input multi-output (MIMO) systems has been hindered by the inherent complexities arising from the problem’s high dimensionality. To enhance scalability, most previous studies have adopted model-driven methodologies that integrate deep neural networks (DNNs) within existing iterative detection frameworks. However, these methods often lack flexibility and involve substantial computational complexity. In this paper, we introduce ChannelNet, a purely data-driven learning-based massive MIMO detector that overcomes these limitations. ChannelNet exploits the inherent symmetry of MIMO systems by incorporating channel-embedded layers and antenna-wise shared feature processors. These modules maintain equivariance to antenna permutations and enable ChannelNet to scale efficiently to large numbers of antennas and high modulation orders with low computational complexity, specifically <inline-formula><tex-math>$mathcal{O}(N_{t}N_{r})$</tex-math></inline-formula>, where <inline-formula><tex-math>$N_{t}$</tex-math></inline-formula> and <inline-formula><tex-math>$N_{r}$</tex-math></inline-formula> denote the numbers of transmit and receive antennas, respectively. Theoretically, ChannelNet can approximate any continuous permutation-symmetric function and the optimal maximum likelihood detection (ML) function with arbitrary precision under any continuous channel distribution. Empirical evaluations demonstrate that ChannelNet consistently outperforms or matches state-of-the-art detectors across different numbers of antennas, modulation schemes, and channel distributions, all while significantly reducing computational overhead. This study highlights the potential of purely data-driven designs in advancing efficient and scalable detectors for massive MIMO systems.","PeriodicalId":13330,"journal":{"name":"IEEE Transactions on Signal Processing","volume":"73 ","pages":"3079-3093"},"PeriodicalIF":5.8,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144787061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Downlink MIMO Channel Estimation from Bits: Recoverability and Algorithm 下行链路MIMO信道估计：可恢复性和算法

IF 5.4 2区工程技术

IEEE Transactions on Signal Processing Pub Date : 2025-08-01 DOI: 10.1109/tsp.2025.3593414

Rajesh Shrestha, Mingjie Shao, Mingyi Hong, Wing-Kin Ma, Xiao Fu

引用次数: 0

Signal Recovery Using a Spiked Mixture Model 使用尖刺混合模型的信号恢复

IF 5.4 2区工程技术

IEEE Transactions on Signal Processing Pub Date : 2025-07-30 DOI: 10.1109/tsp.2025.3593082

Paul-Louis Delacour, Sander Wahls, Jeffrey M. Spraggins, Lukasz Migas, Raf Van de Plas

引用次数: 0

Faster-than-Nyquist Signaling is Good for Single-Carrier ISAC: An Analytical Study 比奈奎斯特信号更快有利于单载波ISAC：一项分析研究

IF 5.4 2区工程技术

IEEE Transactions on Signal Processing Pub Date : 2025-07-29 DOI: 10.1109/tsp.2025.3592443

Shuangyang Li, Fan Liu, Yifeng Xiong, Weijie Yuan, Baoming Bai, Christos Masouros, Giuseppe Caire

引用次数: 0