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Capacity of Wireless Channels Under Transceiver Hardware Impairments and Adaptive Transmission Techniques 收发器硬件损伤和自适应传输技术下的无线信道容量
IF 3.7 3区 计算机科学
IEEE Communications Letters Pub Date : 2025-02-18 DOI: 10.1109/LCOMM.2025.3543217
Yazan H. Al-Badarneh;Osamah S. Badarneh;Mustafa K. Alshawaqfeh;Mazen O. Hasna;Tamer M. Khattab
{"title":"Capacity of Wireless Channels Under Transceiver Hardware Impairments and Adaptive Transmission Techniques","authors":"Yazan H. Al-Badarneh;Osamah S. Badarneh;Mustafa K. Alshawaqfeh;Mazen O. Hasna;Tamer M. Khattab","doi":"10.1109/LCOMM.2025.3543217","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3543217","url":null,"abstract":"We provide an analytic framework for the capacity of adaptive transmission techniques, taking into account both generalized fading channels and Gaussian-distributed transceiver hardware impairments (THI). We derive exact expressions for the capacity of optimal power and rate adaptation, optimal rate adaptation with constant power, channel inversion with fixed rate, and truncated channel inversion with fixed rate. These expressions are general enough to cover a wide range of wireless channels. Due to the high susceptibility of high-data-rate terahertz (THz) communications to THI, we apply our results to investigate the capacity of THz communication systems and confirm the validity of our approach using numerical simulations.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"29 4","pages":"764-768"},"PeriodicalIF":3.7,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143821823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Channel Estimation for Near-Field Line-of-Sight XL-MIMO Communications Using Geometric Prior
IF 3.7 3区 计算机科学
IEEE Communications Letters Pub Date : 2025-02-18 DOI: 10.1109/LCOMM.2025.3543429
Yuqing Guo;Xufeng Guo;Ying Wang
{"title":"Channel Estimation for Near-Field Line-of-Sight XL-MIMO Communications Using Geometric Prior","authors":"Yuqing Guo;Xufeng Guo;Ying Wang","doi":"10.1109/LCOMM.2025.3543429","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3543429","url":null,"abstract":"This letter investigates the channel estimation for near-field line-of-sight (LoS) extremely-large multiple-input-multiple-output (XL-MIMO) communications, where both the transceivers are equipped with uniform linear arrays (ULAs). For near-field LoS channels within millimeter wave and sub-teraherz frequency bands, electromagnetic waves typically propagate with little diffraction or scattering, implying the propagation direction of each plane-wave component remains almost invariant under the Fourier plane-wave series expansion. This invariance indicates a strong correlation between the propagation directions of transmitted and received plane-wave components, called geometric prior in this letter. Initially, we utilize the wavenumber-domain sparsifying basis to decompose the channel into several plane-wave components. Then, we deduce the potential locations of non-zero entries in the wavenumber-domain channel matrix for any relative orientation angle between the ULAs. Subsequently, a two-stage channel estimation framework is further proposed. Specifically, the first stage aims to derive the orientation angle, and the second stage performs compressed sensing within a reduced search space. Simulation results are provided to validate the robustness of our proposed angle and channel estimation.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"29 4","pages":"779-783"},"PeriodicalIF":3.7,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143817859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Graph Network-Based UWB Localization via Learning Spatial-Temporal and Geometric Features
IF 3.7 3区 计算机科学
IEEE Communications Letters Pub Date : 2025-02-18 DOI: 10.1109/LCOMM.2025.3543434
Sizhen He;Bo Yang;Tao Liu;Jun Li
{"title":"Graph Network-Based UWB Localization via Learning Spatial-Temporal and Geometric Features","authors":"Sizhen He;Bo Yang;Tao Liu;Jun Li","doi":"10.1109/LCOMM.2025.3543434","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3543434","url":null,"abstract":"In this letter, we propose a Graph-Attention-Recurrent Neural Network (Graph-ARNN) to improve UWB localization in complex environment by incorporating spatial, temporal and geometric information. We first build the ranging measurements from UWB sensors as a large spatial-temporal graph structure, and then the Graph-ARNN including the graph convolutional model, graph-attention model and deep RNN model are designed to extract the high-level spatial-temporal and geometric features which beneficial to tag location estimation. Thus, the localization performance can be improved. We also conduct three real-world experiments with both LOS and NLOS environments to suggest the advantages of our proposed method.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"29 4","pages":"784-788"},"PeriodicalIF":3.7,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143818045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Coverage Analysis and Beamwidth Adjustment for Sensing-Assisted mmWave Networks With Beam Misalignment
IF 3.7 3区 计算机科学
IEEE Communications Letters Pub Date : 2025-02-17 DOI: 10.1109/LCOMM.2025.3542787
Yinghong Guo;Yixiao Gu;Junhua Liu;Bin Xia
{"title":"Coverage Analysis and Beamwidth Adjustment for Sensing-Assisted mmWave Networks With Beam Misalignment","authors":"Yinghong Guo;Yixiao Gu;Junhua Liu;Bin Xia","doi":"10.1109/LCOMM.2025.3542787","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3542787","url":null,"abstract":"This letter studies the coverage performance of the sensing-assisted millimeter wave networks with imperfect beam alignment to guide beamwidth adjustment. A sensing-assisted adaptive beamforming (SABF) scheme is proposed where the transmitted beamwidth is dynamically adjusted based on sensing estimation to achieve a favorable tradeoff between beamforming gain and beam misalignment probability. To guide beamwidth optimization in network deployment, the stochastic geometry-based expressions for network coverage probability are derived, considering the beam misalignment caused by imperfect sensing estimation. Numerical results validate the accuracy of the analytical expressions, demonstrating the superiority of the SABF scheme that maximizes overall network coverage.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"29 4","pages":"754-758"},"PeriodicalIF":3.7,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143821869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Finite-Length Puncturing Pattern Design for LDPC Codes With Hadamard Constraints
IF 3.7 3区 计算机科学
IEEE Communications Letters Pub Date : 2025-02-17 DOI: 10.1109/LCOMM.2025.3543011
Junyi Du;Peng Kang;Lei Xiao
{"title":"Finite-Length Puncturing Pattern Design for LDPC Codes With Hadamard Constraints","authors":"Junyi Du;Peng Kang;Lei Xiao","doi":"10.1109/LCOMM.2025.3543011","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3543011","url":null,"abstract":"In this letter, we propose a two-stage method to design finite-length puncturing patterns for LDPC codes with Hadamard constraints. At the first stage, we propose the distribution of puncturing patterns and develop extrinsic information transfer functions for distribution optimization in terms of the lowest decoding threshold. At the second stage, we analyze the iterative update process of a Hadamard check node (HCN) and find that the Euclidean distance determines the reliability of its output extrinsic information. Based on this, we propose a greedy algorithm to design puncturing patterns to maximize the number of punctured variable nodes with reliable input information. Simulations verify the good performance of the Hadamard-LDPC code with our designed puncturing patterns, compared to the 5G new radio LDPC code and the same Hadamard-LDPC code with other puncturing patterns.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"29 4","pages":"759-763"},"PeriodicalIF":3.7,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143821547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Optimal Cut Layer Bounds for Split Learning
IF 3.7 3区 计算机科学
IEEE Communications Letters Pub Date : 2025-02-14 DOI: 10.1109/LCOMM.2025.3542541
Matea Marinova;Marija Poposka;Zoran Hadzi-Velkov;Valentin Rakovic
{"title":"Optimal Cut Layer Bounds for Split Learning","authors":"Matea Marinova;Marija Poposka;Zoran Hadzi-Velkov;Valentin Rakovic","doi":"10.1109/LCOMM.2025.3542541","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3542541","url":null,"abstract":"Split learning (SL) is a distributed learning method where a deep learning model is partitioned between the client and server, aiming to optimize the training process. A key challenge in split learning is selecting the cut layer to minimize energy consumption while considering both computational and communication overheads. In this letter, we address this challenge within the context of a wireless system with multiple clients and a central server. We introduce a pruning-based cut layer selection scheme that effectively reduces the energy consumption for each client. Our approach leverages analytical bounds for optimal cut layer location, which we derive and validate against state-of-the-art SL benchmark schemes, demonstrating the high efficiency of our proposed method.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"29 4","pages":"749-753"},"PeriodicalIF":3.7,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143821660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Low Complexity Iterative Channel Estimation and Detection Based on Pilot-Assisted for ZP-OTFS
IF 3.7 3区 计算机科学
IEEE Communications Letters Pub Date : 2025-02-14 DOI: 10.1109/LCOMM.2025.3542020
Qiang Guo;Hanyu Jiang;Jianhong Xiang;Yu Zhong
{"title":"Low Complexity Iterative Channel Estimation and Detection Based on Pilot-Assisted for ZP-OTFS","authors":"Qiang Guo;Hanyu Jiang;Jianhong Xiang;Yu Zhong","doi":"10.1109/LCOMM.2025.3542020","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3542020","url":null,"abstract":"Orthogonal Time Frequency Space (OTFS) modulation offers a novel solution for high-mobility communication. However, iterative channel estimation and detection methods with high complexity limit the application of OTFS. In this letter, a pilot-assisted low complexity iterative channel estimation and detection approach is presented to tackle this challenge. First, we design a generalized compressed sensing-BEM (GCS-BEM) pilot insertion strategy to reduce inter-symbol interference (ISI) of data symbols and enhance the initial channel estimation performance. Second, a pilot-assisted alternative iterative channel estimation (PAAI-CE) method that combines local and global symbols to accelerate channel updates. Specifically, the pilot constrained confidence region (PCCR) is designed to facilitate the convergence of maximum ratio combining (MRC) detection. Simulation results demonstrate that the proposed approach achieves lower computational complexity while maintaining a satisfactory bit error rate (BER).","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"29 4","pages":"724-728"},"PeriodicalIF":3.7,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143821819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Iterative Strong Targets Cancellation for Multi-Target Detection in JRC Systems
IF 3.7 3区 计算机科学
IEEE Communications Letters Pub Date : 2025-02-14 DOI: 10.1109/LCOMM.2025.3542371
Xiaojuan Zhang;Yonghong Zeng;Sumei Sun
{"title":"Iterative Strong Targets Cancellation for Multi-Target Detection in JRC Systems","authors":"Xiaojuan Zhang;Yonghong Zeng;Sumei Sun","doi":"10.1109/LCOMM.2025.3542371","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3542371","url":null,"abstract":"A Joint Radar and Communication (JRC) system utilizing 5G signals is proposed. To address the challenges of detecting multiple closely spaced targets in the range-Doppler map, an iterative strong target cancellation algorithm is introduced. This algorithm mitigates the impact of dominant targets, which can obscure weaker signals and complicate detection for conventional methods such as range- or speed-based searches and CFAR algorithms. By progressively canceling strong targets, the method enhances the detection and differentiation of weaker ones, significantly improving overall system performance. Its adaptability and robustness make it suitable for JRC systems, ensuring accurate detection in resource-constrained and spectrum-sharing environments. A JRC prototype based on software-defined radio (SDR) is developed. Extensive simulations and experiments with the prototype validate the algorithm’s effectiveness.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"29 4","pages":"734-738"},"PeriodicalIF":3.7,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143821548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Near-Field Channel Estimation and Sparse Reconstruction for FDD XL-MIMO Systems
IF 3.7 3区 计算机科学
IEEE Communications Letters Pub Date : 2025-02-14 DOI: 10.1109/LCOMM.2025.3542482
Ze Wang;Guoping Zhang;Ji Wang;Hongbo Xu
{"title":"Near-Field Channel Estimation and Sparse Reconstruction for FDD XL-MIMO Systems","authors":"Ze Wang;Guoping Zhang;Ji Wang;Hongbo Xu","doi":"10.1109/LCOMM.2025.3542482","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3542482","url":null,"abstract":"The exponential growth of antennas in extremely large-scale MIMO (XL-MIMO) systems can lead to substantial overhead in pilot transmission for channel estimation and feedback, resulting in a decline in spectrum efficiency. This letter proposes a deep learning (DL)-based framework tailored for frequency division duplex (FDD) XL-MIMO, focusing on specialized neural networks for channel estimation and sparse reconstruction. For channel estimation, we design frequency-aware pilots by using dense layers according to the signal model and develop an attention mechanism-based residual channel estimation (A-RCE) network, which leverages inherent correlations within the channel matrix across subcarriers and antennas to improve estimation accuracy. To reduce channel state information (CSI) feedback overhead, we introduce a trainable fast iterative shrinkage thresholding (TFIST) network that leverages the polar-domain sparsity of the near-field channel to achieve a low-dimensional sparse representation. The simulation results validate the effectiveness of our proposed scheme, which can significantly enhance the estimation performance compared to other benchmark schemes.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"29 4","pages":"744-748"},"PeriodicalIF":3.7,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143821820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Semantic Approach to Full-Duplex Cooperative Communication for Haptic Interactions
IF 3.7 3区 计算机科学
IEEE Communications Letters Pub Date : 2025-02-14 DOI: 10.1109/LCOMM.2025.3542293
Nargis Fayaz;Justin Jose;Ranjan K. Mallik;Brejesh Lall;Vimal Bhatia
{"title":"A Semantic Approach to Full-Duplex Cooperative Communication for Haptic Interactions","authors":"Nargis Fayaz;Justin Jose;Ranjan K. Mallik;Brejesh Lall;Vimal Bhatia","doi":"10.1109/LCOMM.2025.3542293","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3542293","url":null,"abstract":"This letter introduces a novel semantic-based full-duplex (FD) cooperative communication system for haptic interactions, specifically addressing scenarios where direct communication paths are unavailable. The proposed system employs an FD relay to facilitate communication between a haptic glove and a robotic hand, operating in conventional decode-and-forward (DF) and semantic decode-and-forward (SDF) modes. In SDF mode, the system prioritizes the transmission of essential semantic content, resulting in significant bandwidth savings in comparison to DF. The performance of the system is evaluated through metrics such as bit error rate, mean squared error, and semantic class match (SCM) under generalized Nakagami-m fading conditions. Further, an optimization problem is formulated to maximize the SCM metric of the system and solved using a particle swarm optimization algorithm. Results show that the proposed SDF outperforms DF, particularly in low signal-to-noise ratio conditions, providing improved reliability and efficiency for haptic interactions.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"29 4","pages":"729-733"},"PeriodicalIF":3.7,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143821663","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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