Pub Date : 2026-01-23DOI: 10.1109/LCOMM.2026.3657464
Bin Lyu;Haofan Du;Zongyuan Deng;Yan Liu;Changsheng You;Arumugam Nallanathan
This letter proposes a reconfigurable intelligent surface (RIS) assisted integrated sensing and hybrid symbiotic radio (ISAHSR) system, where the RIS is utilized to not only assist target sensing within the directions of interest, but also support hybrid symbiotic radio (HSR) communications with both parasitic SR (PSR) and commensal SR (CSR) in the absence of direct links. To enable HSR communications, we first introduce a hybrid modulation scheme combining RIS partitioning (RP) and hybrid phase shift (HPS), referred to as the RP–HPS scheme. For this scheme, we maximize the primary transmission performance under practical constraints on target sensing and hybrid secondary transmissions. A two-layer optimization framework is developed to obtain a high-quality solution. Then, we propose the Pure-HPS scheme, where both PSR and CSR setups are achieved solely through phase shift adjustments, eliminating the need for the RP operation. To optimize this scheme, we design a single-layer optimization algorithm with low complexity. Numerical results demonstrate that the Pure-HPS scheme achieves better performance with significantly reduced computational complexity compared to the RP–HPS scheme.
{"title":"RIS-Assisted Integrated Sensing and Hybrid Symbiotic Radio Systems","authors":"Bin Lyu;Haofan Du;Zongyuan Deng;Yan Liu;Changsheng You;Arumugam Nallanathan","doi":"10.1109/LCOMM.2026.3657464","DOIUrl":"https://doi.org/10.1109/LCOMM.2026.3657464","url":null,"abstract":"This letter proposes a reconfigurable intelligent surface (RIS) assisted integrated sensing and hybrid symbiotic radio (ISAHSR) system, where the RIS is utilized to not only assist target sensing within the directions of interest, but also support hybrid symbiotic radio (HSR) communications with both parasitic SR (PSR) and commensal SR (CSR) in the absence of direct links. To enable HSR communications, we first introduce a hybrid modulation scheme combining RIS partitioning (RP) and hybrid phase shift (HPS), referred to as the RP–HPS scheme. For this scheme, we maximize the primary transmission performance under practical constraints on target sensing and hybrid secondary transmissions. A two-layer optimization framework is developed to obtain a high-quality solution. Then, we propose the Pure-HPS scheme, where both PSR and CSR setups are achieved solely through phase shift adjustments, eliminating the need for the RP operation. To optimize this scheme, we design a single-layer optimization algorithm with low complexity. Numerical results demonstrate that the Pure-HPS scheme achieves better performance with significantly reduced computational complexity compared to the RP–HPS scheme.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"30 ","pages":"1116-1120"},"PeriodicalIF":4.4,"publicationDate":"2026-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147299585","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}
Pub Date : 2026-01-23DOI: 10.1109/LCOMM.2026.3657403
Guanxing Zhang;He Wen;Jie Zhang
To address signal blockage challenges associated with the millimeter-wave (mmWave) band, we explore the potential of reconfigurable intelligent surfaces (RIS) to enhance performance of integrated sensing and communication (ISAC) systems. Unlike most studies assuming continuous phase control, we consider the more practical scenario of discrete phase-shifted RIS. Simulation results show that RIS in mmWave ISAC systems can mitigate blockage by building a virtual line-of-sight (LOS). Besides, we present the trade-off analysis of communication and radar performance using discrete phase-shifted RIS, comparing the continuous and discrete phase configurations in terms of mean square error (MSE) and normalized sideband power (NSP).
{"title":"Beamforming Design and Performance Analysis of Discrete Phase-Controlled RIS-Assisted mmWave ISAC Systems","authors":"Guanxing Zhang;He Wen;Jie Zhang","doi":"10.1109/LCOMM.2026.3657403","DOIUrl":"https://doi.org/10.1109/LCOMM.2026.3657403","url":null,"abstract":"To address signal blockage challenges associated with the millimeter-wave (mmWave) band, we explore the potential of reconfigurable intelligent surfaces (RIS) to enhance performance of integrated sensing and communication (ISAC) systems. Unlike most studies assuming continuous phase control, we consider the more practical scenario of discrete phase-shifted RIS. Simulation results show that RIS in mmWave ISAC systems can mitigate blockage by building a virtual line-of-sight (LOS). Besides, we present the trade-off analysis of communication and radar performance using discrete phase-shifted RIS, comparing the continuous and discrete phase configurations in terms of mean square error (MSE) and normalized sideband power (NSP).","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"30 ","pages":"972-976"},"PeriodicalIF":4.4,"publicationDate":"2026-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146082058","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}
Deep-learning-based Radio Frequency Fingerprint Identification (RFFI) leverages hardware-induced imperfections for device authentication. However, cross-receiver shifts induce category-dependent errors, and practical deployment is constrained by the trade-off between model complexity and latency. To address this, we propose a receiver-agnostic, multi-modal RFFI method that integrates Convolutional Neural Network (CNN)-derived spatial cues, Bidirectional Encoder Representations from Transformers (BERT)-based temporal modeling, and Carrier Frequency Offset (CFO) features. A two-stage knowledge distillation strategy transfers knowledge from a high-capacity Teacher (utilizing all modalities with 7.15M parameters) to a lightweight Student (utilizing only spatial and CFO features with 2.38M parameters). The Student operates without the computationally intensive BERT module during inference, achieving 66.7% parameter reduction. Under challenging cross-receiver conditions with a 9:3 receiver split, the Teacher achieves 88.77% accuracy, while the Distilled Student achieves 89.82% accuracy. The standalone Student without distillation achieves only 85.40%, demonstrating a + 4.42% improvement from cross-modal knowledge transfer. With 2.5 ms inference latency, the distilled model enables practical, receiver-agnostic RFFI deployment.
{"title":"Receiver-Agnostic Radio Frequency Fingerprint Identification Using BERT and Two-Stage Knowledge Distillation","authors":"Jiawen Shao;Zijiang Yang;Tiantian Tang;Chengcheng Liu;Yun Lin;Guan Gui","doi":"10.1109/LCOMM.2026.3656814","DOIUrl":"https://doi.org/10.1109/LCOMM.2026.3656814","url":null,"abstract":"Deep-learning-based Radio Frequency Fingerprint Identification (RFFI) leverages hardware-induced imperfections for device authentication. However, cross-receiver shifts induce category-dependent errors, and practical deployment is constrained by the trade-off between model complexity and latency. To address this, we propose a receiver-agnostic, multi-modal RFFI method that integrates Convolutional Neural Network (CNN)-derived spatial cues, Bidirectional Encoder Representations from Transformers (BERT)-based temporal modeling, and Carrier Frequency Offset (CFO) features. A two-stage knowledge distillation strategy transfers knowledge from a high-capacity Teacher (utilizing all modalities with 7.15M parameters) to a lightweight Student (utilizing only spatial and CFO features with 2.38M parameters). The Student operates without the computationally intensive BERT module during inference, achieving 66.7% parameter reduction. Under challenging cross-receiver conditions with a 9:3 receiver split, the Teacher achieves 88.77% accuracy, while the Distilled Student achieves 89.82% accuracy. The standalone Student without distillation achieves only 85.40%, demonstrating a + 4.42% improvement from cross-modal knowledge transfer. With 2.5 ms inference latency, the distilled model enables practical, receiver-agnostic RFFI deployment.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"30 ","pages":"942-946"},"PeriodicalIF":4.4,"publicationDate":"2026-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146082073","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}
Pub Date : 2026-01-20DOI: 10.1109/LCOMM.2026.3656455
Masahiro Higashida;Yoshiaki Inoue
We analyze the mean squared error (MSE) in real-time monitoring of an Ornstein-Uhlenbeck (OU) process with observational noise, using multiple past samples to improve estimation. Assuming a D/GI/1 queueing model for system delay, we show that the time-averaged MSE decomposes into two components: (i) a term involving the Laplace-Stieltjes transform (LST) of the age of information (AoI), and (ii) a term determined by the number of observations $m$ and the parameters of the OU process and noise. We further derive a closed-form expression for this latter term and investigate its limiting behavior.
{"title":"Analysis of the Real-Time Monitoring Error for the Ornstein–Uhlenbeck Process in the D/GI/1 Queue","authors":"Masahiro Higashida;Yoshiaki Inoue","doi":"10.1109/LCOMM.2026.3656455","DOIUrl":"https://doi.org/10.1109/LCOMM.2026.3656455","url":null,"abstract":"We analyze the mean squared error (MSE) in real-time monitoring of an Ornstein-Uhlenbeck (OU) process with observational noise, using multiple past samples to improve estimation. Assuming a D/GI/1 queueing model for system delay, we show that the time-averaged MSE decomposes into two components: (i) a term involving the Laplace-Stieltjes transform (LST) of the age of information (AoI), and (ii) a term determined by the number of observations <inline-formula> <tex-math>$m$ </tex-math></inline-formula> and the parameters of the OU process and noise. We further derive a closed-form expression for this latter term and investigate its limiting behavior.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"30 ","pages":"1002-1006"},"PeriodicalIF":4.4,"publicationDate":"2026-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146175688","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}
In the dual-function radar-communication (DFRC) system, due to variations in communication information, the matched filter output of each DFRC waveform exhibits distinct range sidelobe structures, referred as range sidelobe modulation (RSM), which will degrade the clutter cancellation performance and increase residual clutter energy after moving target indication (MTI) processing. To solve this problem, a localized mismatch filter (LMMF) design method is proposed in this letter. First, a joint weighted optimization problem in terms of sidelobe level (SLL), similarity, and signal-to-noise ratio (SNR) loss is formulated. Then, the LMMF design method based on the alternating direction method of multipliers (ADMM) is proposed, and its convergence and complexity are discussed. Finally, several numerical results are given to demonstrate the effectiveness of the proposed method.
{"title":"Localized Mismatch Filter Design for Dual-Function Radar-Communication Waveforms","authors":"Hao Tang;Yongjun Liu;Guisheng Liao;Xuchen Liu;Heming Wang;Xiaoyang Dong","doi":"10.1109/LCOMM.2026.3655560","DOIUrl":"https://doi.org/10.1109/LCOMM.2026.3655560","url":null,"abstract":"In the dual-function radar-communication (DFRC) system, due to variations in communication information, the matched filter output of each DFRC waveform exhibits distinct range sidelobe structures, referred as range sidelobe modulation (RSM), which will degrade the clutter cancellation performance and increase residual clutter energy after moving target indication (MTI) processing. To solve this problem, a localized mismatch filter (LMMF) design method is proposed in this letter. First, a joint weighted optimization problem in terms of sidelobe level (SLL), similarity, and signal-to-noise ratio (SNR) loss is formulated. Then, the LMMF design method based on the alternating direction method of multipliers (ADMM) is proposed, and its convergence and complexity are discussed. Finally, several numerical results are given to demonstrate the effectiveness of the proposed method.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"30 ","pages":"927-931"},"PeriodicalIF":4.4,"publicationDate":"2026-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146026350","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}
Pub Date : 2026-01-19DOI: 10.1109/LCOMM.2026.3655827
Mert İlgüy;Berna Özbek;Didier Le Ruyet
Reconfigurable intelligent surfaces (RIS) have emerged as an important technology for next-generation wireless networks by intelligently manipulating the wireless propagation environment. Beyond Diagonal RIS (BD-RIS) extends the traditional RIS architecture by allowing non-diagonal reflection matrices, enabling more flexible signal manipulation. Transmissive RIS (T-RIS), on the other hand, facilitates the transmission of signals through the metasurfaces. In this paper, we propose a novel design called transmissive BD-RIS (T-BD-RIS), which integrates the functionalities of BD-RIS and T-RIS to enhance the user data rate. We design an algorithm for the group connected (GC) configuration, which jointly optimizes the beamforming at the base station, the T-BD-RIS transmission matrix, and the receive combiner at the user side. The fully connected (FC) and single connected (SC) cases are special instances of the proposed generic GC design, obtained by an appropriate choice of the number of groups. We evaluate the performance of various schemes, demonstrating the potential of the proposed approach.
{"title":"On Group Connected Transmissive Beyond Diagonal RIS for MIMO Systems","authors":"Mert İlgüy;Berna Özbek;Didier Le Ruyet","doi":"10.1109/LCOMM.2026.3655827","DOIUrl":"https://doi.org/10.1109/LCOMM.2026.3655827","url":null,"abstract":"Reconfigurable intelligent surfaces (RIS) have emerged as an important technology for next-generation wireless networks by intelligently manipulating the wireless propagation environment. Beyond Diagonal RIS (BD-RIS) extends the traditional RIS architecture by allowing non-diagonal reflection matrices, enabling more flexible signal manipulation. Transmissive RIS (T-RIS), on the other hand, facilitates the transmission of signals through the metasurfaces. In this paper, we propose a novel design called transmissive BD-RIS (T-BD-RIS), which integrates the functionalities of BD-RIS and T-RIS to enhance the user data rate. We design an algorithm for the group connected (GC) configuration, which jointly optimizes the beamforming at the base station, the T-BD-RIS transmission matrix, and the receive combiner at the user side. The fully connected (FC) and single connected (SC) cases are special instances of the proposed generic GC design, obtained by an appropriate choice of the number of groups. We evaluate the performance of various schemes, demonstrating the potential of the proposed approach.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"30 ","pages":"947-951"},"PeriodicalIF":4.4,"publicationDate":"2026-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146082052","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}
Pub Date : 2026-01-19DOI: 10.1109/LCOMM.2026.3655158
Yuan Ai;Xidong Mu;Pengbo Si;Yuanwei Liu
This letter proposes a novel pinching antenna systems (PASS) enabled non-orthogonal multiple access (NOMA) multi-access edge computing (MEC) framework. An optimization problem is formulated to minimize the maximum task delay by optimizing offloading ratios, transmit powers, and pinching antenna (PA) positions, subject to constraints on maximum transmit power, user energy budgets, and minimum PA separation to mitigate coupling effects. To address the non-convex problem, a bisection search-based alternating optimization (AO) algorithm is developed, where each subproblem is iteratively solved for a given task delay. Numerical simulations demonstrate that the proposed framework significantly reduces the task delay compared to benchmark schemes.
{"title":"Delay Minimization in Pinching-Antenna-Enabled NOMA-MEC Networks","authors":"Yuan Ai;Xidong Mu;Pengbo Si;Yuanwei Liu","doi":"10.1109/LCOMM.2026.3655158","DOIUrl":"https://doi.org/10.1109/LCOMM.2026.3655158","url":null,"abstract":"This letter proposes a novel pinching antenna systems (PASS) enabled non-orthogonal multiple access (NOMA) multi-access edge computing (MEC) framework. An optimization problem is formulated to minimize the maximum task delay by optimizing offloading ratios, transmit powers, and pinching antenna (PA) positions, subject to constraints on maximum transmit power, user energy budgets, and minimum PA separation to mitigate coupling effects. To address the non-convex problem, a bisection search-based alternating optimization (AO) algorithm is developed, where each subproblem is iteratively solved for a given task delay. Numerical simulations demonstrate that the proposed framework significantly reduces the task delay compared to benchmark schemes.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"30 ","pages":"962-966"},"PeriodicalIF":4.4,"publicationDate":"2026-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146082090","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}
In this letter, we address efficient communication and resource allocation for vehicular networks in urban environments. Due to spectrum reuse and rapidly varying interference, joint spectrum allocation and power control become particularly challenging in such scenarios. To tackle this problem, we formulate a system-level optimization framework and propose a multi-agent reinforcement learning approach termed the Predictive Residual Q-Network Method (P-RQNM). An LSTM-based predictor is employed to predict short-term interference from historical observations, while a residual Q-network refines individual Q-values using trajectory statistics to improve decision consistency and contribute to more stable training behavior. Simulation results under urban vehicular scenarios show that P-RQNM outperforms baseline multi-agent value-decomposition methods in terms of link capacity, transmission reliability, and convergence behavior, demonstrating robust performance across diverse traffic densities and loads and practical potential for urban vehicular networks.
{"title":"P-RQNM: Multi-Agent Resource Allocation Optimization in Vehicular Networks via Predictive Residual Q-Networks","authors":"Hui Ji;Fei Ding;Xuanjie Tong;Guangying Wang;Yue Zheng","doi":"10.1109/LCOMM.2026.3655445","DOIUrl":"https://doi.org/10.1109/LCOMM.2026.3655445","url":null,"abstract":"In this letter, we address efficient communication and resource allocation for vehicular networks in urban environments. Due to spectrum reuse and rapidly varying interference, joint spectrum allocation and power control become particularly challenging in such scenarios. To tackle this problem, we formulate a system-level optimization framework and propose a multi-agent reinforcement learning approach termed the Predictive Residual Q-Network Method (P-RQNM). An LSTM-based predictor is employed to predict short-term interference from historical observations, while a residual Q-network refines individual Q-values using trajectory statistics to improve decision consistency and contribute to more stable training behavior. Simulation results under urban vehicular scenarios show that P-RQNM outperforms baseline multi-agent value-decomposition methods in terms of link capacity, transmission reliability, and convergence behavior, demonstrating robust performance across diverse traffic densities and loads and practical potential for urban vehicular networks.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"30 ","pages":"1071-1075"},"PeriodicalIF":4.4,"publicationDate":"2026-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146223582","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}
Pub Date : 2026-01-19DOI: 10.1109/LCOMM.2026.3654956
Mingkun Li;Pengyu Wang;Yuhan Dong;Jinshu Chen;Zhaocheng Wang
With the development of wireless communication devices, due to limited spectrum resources and rising interference, the importance of effective spectrum sensing techniques has drawn much attention. Hereby, modulation recognition serves as a cornerstone for non-cooperative communications and anti-jamming operations. While deep learning becomes popular through autonomous feature extraction, its vulnerability to adversarial attacks poses critical security risks. To address this challenge, FlowSlicer is proposed based on diffusion models for the modulation recognition domain. Furthermore, we explore a segmented recognition strategy for communication signals and propose an aggregation algorithm to enhance the modulation recognition. Simulation results validate the robustness of FlowSlicer under various adversarial attack strategies.
{"title":"Adversarial Defense in Modulation Recognition via Diffusion and Segment-Wise Classification","authors":"Mingkun Li;Pengyu Wang;Yuhan Dong;Jinshu Chen;Zhaocheng Wang","doi":"10.1109/LCOMM.2026.3654956","DOIUrl":"https://doi.org/10.1109/LCOMM.2026.3654956","url":null,"abstract":"With the development of wireless communication devices, due to limited spectrum resources and rising interference, the importance of effective spectrum sensing techniques has drawn much attention. Hereby, modulation recognition serves as a cornerstone for non-cooperative communications and anti-jamming operations. While deep learning becomes popular through autonomous feature extraction, its vulnerability to adversarial attacks poses critical security risks. To address this challenge, FlowSlicer is proposed based on diffusion models for the modulation recognition domain. Furthermore, we explore a segmented recognition strategy for communication signals and propose an aggregation algorithm to enhance the modulation recognition. Simulation results validate the robustness of FlowSlicer under various adversarial attack strategies.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"30 ","pages":"987-991"},"PeriodicalIF":4.4,"publicationDate":"2026-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146175772","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}
Pub Date : 2026-01-19DOI: 10.1109/LCOMM.2026.3655084
Jingjing Zhao;Qingyi Huang;Kaiquan Cai;Quan Zhou;Xidong Mu;Yuanwei Liu
A point-to-point movable element (ME) enabled reconfigurable intelligent surface (ME-RIS) communication system is investigated, where each element position can be flexibly adjusted to create favorable channel conditions. For maximizing the communication rate, an efficient ME position optimization approach is proposed. Specifically, by characterizing the cascaded channel power gain in an element-wise manner, the position of each ME is iteratively updated by invoking the successive convex approximation method. Numerical results unveil that: 1) proposed element-wise ME position optimization algorithm outperforms the standard gradient ascent algorithm (GAA) which is easily trapped in local optima and 2) ME-RIS significantly improves the communication rate compared to the conventional RIS with fixed-position elements.
{"title":"Movable-Element RIS-Aided Wireless Communications: An Element-Wise Position Optimization Approach","authors":"Jingjing Zhao;Qingyi Huang;Kaiquan Cai;Quan Zhou;Xidong Mu;Yuanwei Liu","doi":"10.1109/LCOMM.2026.3655084","DOIUrl":"https://doi.org/10.1109/LCOMM.2026.3655084","url":null,"abstract":"A point-to-point movable element (ME) enabled reconfigurable intelligent surface (ME-RIS) communication system is investigated, where each element position can be flexibly adjusted to create favorable channel conditions. For maximizing the communication rate, an efficient ME position optimization approach is proposed. Specifically, by characterizing the cascaded channel power gain in an element-wise manner, the position of each ME is iteratively updated by invoking the successive convex approximation method. Numerical results unveil that: 1) proposed element-wise ME position optimization algorithm outperforms the standard gradient ascent algorithm (GAA) which is easily trapped in local optima and 2) ME-RIS significantly improves the communication rate compared to the conventional RIS with fixed-position elements.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"30 ","pages":"967-971"},"PeriodicalIF":4.4,"publicationDate":"2026-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146081996","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}
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