Pub Date : 2026-03-04DOI: 10.1109/LCOMM.2026.3670309
Xuewan Zhang;Keqi Wang
Sparse vector transmission (SVT) has garnered attention for short-packet communications due to its simple implementation and reliable transmission. However, its reliability in mobile scenarios remains an open challenge. To address this issue, a joint pilot-data SVT scheme tailored to the SVT block coding structure is proposed, in which both pilots and data are mapped into a unified sparse vector, and then forms a transmitted vector over an orthogonal frequency-division multiplexing (OFDM) symbol through random spreading. At the receiver, a joint iterative channel estimation and data detection algorithm is designed to progressively refine performance by selecting highly reliable decoded data as pseudo-pilots. Simulations indicate that the proposed SVT scheme outperforms both conventional separated pilot-data mapping and power-allocation-based superposition in block error rate (BLER) performance. Impressively, its first-iteration performance is already close to the converged performance of the power-allocation-based superposition scheme.
{"title":"A Joint Pilot-Data Sparse Vector Transmission Framework for Short-Packet URLLC","authors":"Xuewan Zhang;Keqi Wang","doi":"10.1109/LCOMM.2026.3670309","DOIUrl":"https://doi.org/10.1109/LCOMM.2026.3670309","url":null,"abstract":"Sparse vector transmission (SVT) has garnered attention for short-packet communications due to its simple implementation and reliable transmission. However, its reliability in mobile scenarios remains an open challenge. To address this issue, a joint pilot-data SVT scheme tailored to the SVT block coding structure is proposed, in which both pilots and data are mapped into a unified sparse vector, and then forms a transmitted vector over an orthogonal frequency-division multiplexing (OFDM) symbol through random spreading. At the receiver, a joint iterative channel estimation and data detection algorithm is designed to progressively refine performance by selecting highly reliable decoded data as pseudo-pilots. Simulations indicate that the proposed SVT scheme outperforms both conventional separated pilot-data mapping and power-allocation-based superposition in block error rate (BLER) performance. Impressively, its first-iteration performance is already close to the converged performance of the power-allocation-based superposition scheme.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"30 ","pages":"1265-1269"},"PeriodicalIF":4.4,"publicationDate":"2026-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147440563","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 : 2026-03-02DOI: 10.1109/LCOMM.2026.3669227
Tu-Trinh Thi Nguyen;Xuan-Xinh Nguyen;Ngan V. T. Nguyen
In this letter, we study the average block error rate (BLER) performance of short-packet communications (SPC) for pinching-antenna systems (PASS). A base station equipped with a pinching antenna serves an Internet of Things downlink user using SPC. Closed-form expressions for the average BLER of SPC for PASS networks are analytically derived under in-waveguide attenuation. Simulation results demonstrate that PASS-aided SPC networks significantly outperform conventional fixed-antenna-aided SPC systems in terms of BLER, especially in the low in-waveguide attenuation regime.
{"title":"Short-Packet Communications for Pinching-Antenna Systems","authors":"Tu-Trinh Thi Nguyen;Xuan-Xinh Nguyen;Ngan V. T. Nguyen","doi":"10.1109/LCOMM.2026.3669227","DOIUrl":"https://doi.org/10.1109/LCOMM.2026.3669227","url":null,"abstract":"In this letter, we study the average block error rate (BLER) performance of short-packet communications (SPC) for pinching-antenna systems (PASS). A base station equipped with a pinching antenna serves an Internet of Things downlink user using SPC. Closed-form expressions for the average BLER of SPC for PASS networks are analytically derived under in-waveguide attenuation. Simulation results demonstrate that PASS-aided SPC networks significantly outperform conventional fixed-antenna-aided SPC systems in terms of BLER, especially in the low in-waveguide attenuation regime.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"30 ","pages":"1270-1274"},"PeriodicalIF":4.4,"publicationDate":"2026-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147440565","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 : 2026-03-02DOI: 10.1109/LCOMM.2026.3669606
Jianfeng Shi;Zhongping Tan
Federated learning (FL) enables privacy-preserving distributed learning but faces significant communication bottlenecks, especially for resource-constrained edge devices. Existing approaches often incur additional computational cost or require auxiliary data. To address these problems, we propose FedSNN-QC, a lightweight FL framework leveraging Spiking Neural Networks (SNNs) for their efficiency and robustness to Non-IID and noisy data. The framework incorporates a gradient quantization scheme exploiting SNN sparsity to minimize transmission and joint gradient clipping techniques to enhance robustness and convergence. Experimental results demonstrate that the FedSNN-QC maintains competitive accuracy while substantially reducing both communication and computational energy costs compared to conventional methods.
{"title":"Lightweight Federated Learning Based on SNNs and Gradient Quantization Clipping","authors":"Jianfeng Shi;Zhongping Tan","doi":"10.1109/LCOMM.2026.3669606","DOIUrl":"https://doi.org/10.1109/LCOMM.2026.3669606","url":null,"abstract":"Federated learning (FL) enables privacy-preserving distributed learning but faces significant communication bottlenecks, especially for resource-constrained edge devices. Existing approaches often incur additional computational cost or require auxiliary data. To address these problems, we propose FedSNN-QC, a lightweight FL framework leveraging Spiking Neural Networks (SNNs) for their efficiency and robustness to Non-IID and noisy data. The framework incorporates a gradient quantization scheme exploiting SNN sparsity to minimize transmission and joint gradient clipping techniques to enhance robustness and convergence. Experimental results demonstrate that the FedSNN-QC maintains competitive accuracy while substantially reducing both communication and computational energy costs compared to conventional methods.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"30 ","pages":"1260-1264"},"PeriodicalIF":4.4,"publicationDate":"2026-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147440567","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 : 2026-03-02DOI: 10.1109/LCOMM.2026.3669196
Ahmed Al-Amri;Akram Al-Hourani;Saman Atapattu;Bassel Al Homssi
Urban environments pose a fundamental challenge to millimeter-wave (mmWave) satellite communications (SatCom) by introducing spatially correlated line-of-sight (LoS) blockage, also known as shadowing, which degrades reliability, even with the assistance of reconfigurable intelligent surfaces (RIS). We develop a tractable analytical framework to evaluate the success probability of SatCom systems aided by multi-RIS deployments while considering the crucial factor of correlated LoS conditions. First, we derive an analytical closed-form expression for the exact per-realization success probability. To address the intractability of averaging over minimum-distance constrained (repulsive) RIS deployments, we propose a geometry-averaged formulation by approximating the Matérn hard-core (MHC) process with an inhomogeneous PPP (IPPP) of a known conditional intensity. We then propose a scalable annular-averaging method that replaces the radial integral with ringwise averages, enabling efficient large-scale analysis. Monte Carlo simulations confirm the model’s validity and reveal the impact of blockage intensity, correlation decay, and RIS–user separation, thus providing practical guidelines for RIS deployment to assist future non-terrestrial networks.
{"title":"Satellite Coverage Probability With Multi-RIS Deployments Under Correlated LoS Conditions","authors":"Ahmed Al-Amri;Akram Al-Hourani;Saman Atapattu;Bassel Al Homssi","doi":"10.1109/LCOMM.2026.3669196","DOIUrl":"https://doi.org/10.1109/LCOMM.2026.3669196","url":null,"abstract":"Urban environments pose a fundamental challenge to millimeter-wave (mmWave) satellite communications (SatCom) by introducing spatially correlated line-of-sight (LoS) blockage, also known as shadowing, which degrades reliability, even with the assistance of reconfigurable intelligent surfaces (RIS). We develop a tractable analytical framework to evaluate the success probability of SatCom systems aided by multi-RIS deployments while considering the crucial factor of correlated LoS conditions. First, we derive an analytical closed-form expression for the exact per-realization success probability. To address the intractability of averaging over minimum-distance constrained (repulsive) RIS deployments, we propose a geometry-averaged formulation by approximating the Matérn hard-core (MHC) process with an inhomogeneous PPP (IPPP) of a known conditional intensity. We then propose a scalable annular-averaging method that replaces the radial integral with ringwise averages, enabling efficient large-scale analysis. Monte Carlo simulations confirm the model’s validity and reveal the impact of blockage intensity, correlation decay, and RIS–user separation, thus providing practical guidelines for RIS deployment to assist future non-terrestrial networks.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"30 ","pages":"1250-1254"},"PeriodicalIF":4.4,"publicationDate":"2026-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147440566","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}
Accurate prediction of cellular traffic is essential for enabling intelligent networks. However, this requires effectively capturing the dynamic variations within the traffic. Thus, we propose a Pre-Denoising Adaptive Decomposition Spatial-Temporal Transformer (PAD-STT). First, to mitigate noise interference in sequence decomposition, we apply a Savitzky–Golay filter for pre-denoising. Second, a dual-correlation mechanism is designed based on cross-correlation theory, enabling PAD-STT to perform synchronized modeling by jointly learning spatial and temporal relationships rather than in a sequential manner. Finally, we develop an adaptive decomposition to replace the original moving average, aiming to effectively capture dynamic variations. Experiments on real-world datasets demonstrate that PAD-STT outperforms representative state-of-the-art methods.
{"title":"PAD-STT: A Pre-Denoising Adaptive Decomposition Spatial–Temporal Transformer for Cellular Traffic Prediction","authors":"Geng Chen;Xiantao Du;Fei Shen;Qingtian Zeng;Yu-Dong Zhang","doi":"10.1109/LCOMM.2026.3668938","DOIUrl":"https://doi.org/10.1109/LCOMM.2026.3668938","url":null,"abstract":"Accurate prediction of cellular traffic is essential for enabling intelligent networks. However, this requires effectively capturing the dynamic variations within the traffic. Thus, we propose a Pre-Denoising Adaptive Decomposition Spatial-Temporal Transformer (PAD-STT). First, to mitigate noise interference in sequence decomposition, we apply a Savitzky–Golay filter for pre-denoising. Second, a dual-correlation mechanism is designed based on cross-correlation theory, enabling PAD-STT to perform synchronized modeling by jointly learning spatial and temporal relationships rather than in a sequential manner. Finally, we develop an adaptive decomposition to replace the original moving average, aiming to effectively capture dynamic variations. Experiments on real-world datasets demonstrate that PAD-STT outperforms representative state-of-the-art methods.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"30 ","pages":"1245-1249"},"PeriodicalIF":4.4,"publicationDate":"2026-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147362322","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 : 2026-02-27DOI: 10.1109/LCOMM.2026.3669035
Abdullah Othman;Georges Kaddoum;João V. C. Evangelista;Minh Au;Basile L. Agba
Digital Twins (DTs) offer a powerful tool for outage management in wireless networks, but their direct deployment during emergencies is limited by the high cost of near real-time ray tracing. This work develops a DT-enabled outage management framework that combines vision-based outage detection with availability-oriented uplink control. A lightweight detector (DTOD), trained on DT renders and SINR-consistent labels, produces calibrated outage probabilities in almost real time. These predictions trigger a threshold-capped (ThreshCap) uplink power allocator, which leverages UAV relays to sustain service during macro base station (MBS) failures. Using Markovian MBS outages, realistic DT mobility, and surrogate channels fitted to ray-traced propagation, we show that UAV relays substantially improve availability and that ThreshCap consistently outperforms baselines under varying load and outage intensities.
{"title":"Digital-Twin-Enabled Outage Detection and Uplink Availability Optimization With UAV Assistance","authors":"Abdullah Othman;Georges Kaddoum;João V. C. Evangelista;Minh Au;Basile L. Agba","doi":"10.1109/LCOMM.2026.3669035","DOIUrl":"https://doi.org/10.1109/LCOMM.2026.3669035","url":null,"abstract":"Digital Twins (DTs) offer a powerful tool for outage management in wireless networks, but their direct deployment during emergencies is limited by the high cost of near real-time ray tracing. This work develops a DT-enabled outage management framework that combines vision-based outage detection with availability-oriented uplink control. A lightweight detector (DTOD), trained on DT renders and SINR-consistent labels, produces calibrated outage probabilities in almost real time. These predictions trigger a threshold-capped (ThreshCap) uplink power allocator, which leverages UAV relays to sustain service during macro base station (MBS) failures. Using Markovian MBS outages, realistic DT mobility, and surrogate channels fitted to ray-traced propagation, we show that UAV relays substantially improve availability and that ThreshCap consistently outperforms baselines under varying load and outage intensities.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"30 ","pages":"1255-1259"},"PeriodicalIF":4.4,"publicationDate":"2026-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147440564","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 : 2026-02-23DOI: 10.1109/LCOMM.2026.3666785
Jingchen Wu;Ruiding Hou;Jiaheng Wang;Yongming Huang;Sen Wang;Liang Xia;Jing Jin
Multiple-input multiple-output (MIMO) technology is fundamental in communication systems, where precoding plays a crucial role in improving spectral efficiency. Most existing precoding methods either assume infinite blocklength (IBL) or handle only a single sum power constraint (SPC). However, realistic systems often operate with finite blocklength (FBL), especially in ultra-reliable low-latency communication (URLLC), and face diverse power limits, such as per-antenna and per-group power constraints. This renders the IBL rate formulation insufficient and necessitates precoding methods tackling various power constraints in the FBL regime. In this letter, we aim to enhance overall FBL rate performance of MIMO systems under quality-of-service (QoS) requirements and mixed power constraints (MPCs) that can encompass various power limitations. Unlike previous methods that directly solve the original nonconvex precoding design problem, we first convert it to an equivalent SINR-allocation problem and then propose two efficient algorithms, i.e., a bi-direction gradient method (BDGM) and an iterative water-filling (IWF) algorithm with guaranteed convergence properties. The proposed algorithms are applicable to single-cell, multi-cell, and cell-free systems, and can achieve satisfactory performance at lower complexity.
{"title":"Finite Blocklength MIMO Precoding With Mixed Power and QoS Constraints","authors":"Jingchen Wu;Ruiding Hou;Jiaheng Wang;Yongming Huang;Sen Wang;Liang Xia;Jing Jin","doi":"10.1109/LCOMM.2026.3666785","DOIUrl":"https://doi.org/10.1109/LCOMM.2026.3666785","url":null,"abstract":"Multiple-input multiple-output (MIMO) technology is fundamental in communication systems, where precoding plays a crucial role in improving spectral efficiency. Most existing precoding methods either assume infinite blocklength (IBL) or handle only a single sum power constraint (SPC). However, realistic systems often operate with finite blocklength (FBL), especially in ultra-reliable low-latency communication (URLLC), and face diverse power limits, such as per-antenna and per-group power constraints. This renders the IBL rate formulation insufficient and necessitates precoding methods tackling various power constraints in the FBL regime. In this letter, we aim to enhance overall FBL rate performance of MIMO systems under quality-of-service (QoS) requirements and mixed power constraints (MPCs) that can encompass various power limitations. Unlike previous methods that directly solve the original nonconvex precoding design problem, we first convert it to an equivalent SINR-allocation problem and then propose two efficient algorithms, i.e., a bi-direction gradient method (BDGM) and an iterative water-filling (IWF) algorithm with guaranteed convergence properties. The proposed algorithms are applicable to single-cell, multi-cell, and cell-free systems, and can achieve satisfactory performance at lower complexity.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"30 ","pages":"1235-1239"},"PeriodicalIF":4.4,"publicationDate":"2026-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147362323","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 : 2026-02-23DOI: 10.1109/LCOMM.2026.3667034
Long Yang;Wencong Li;Zhenhan Zhao;Yuchen Zhou;Fanggang Wang;Huaiyu Tang
Deep learning methods exhibit limited performance in few-shot specific emitter identification tasks due to the scarcity of labeled training samples. To address this challenge, this letter proposes an attention-enhanced masked autoencoder framework that consists of a pre-training stage with unlabeled auxiliary samples and a fine-tuning stage with limited labeled samples. During the pre-training stage, we employ a teacher-student training framework that integrates masked sample reconstruction and teacher-student feature alignment. In particular, for the student network, we introduce an attention-enhanced masking strategy and a scaled mean squared error loss to enhance representation capabilities. During the fine-tuning stage, the pre-trained feature extractor and classifier are jointly optimized on the limited labeled data. Simulation experiments demonstrate that our proposed framework outperforms other state-of-the-art methods by using an open-source LoRa dataset.
{"title":"Masked Autoencoder for Few-Shot Specific Emitter Identification: An Attention-Enhanced Approach","authors":"Long Yang;Wencong Li;Zhenhan Zhao;Yuchen Zhou;Fanggang Wang;Huaiyu Tang","doi":"10.1109/LCOMM.2026.3667034","DOIUrl":"https://doi.org/10.1109/LCOMM.2026.3667034","url":null,"abstract":"Deep learning methods exhibit limited performance in few-shot specific emitter identification tasks due to the scarcity of labeled training samples. To address this challenge, this letter proposes an attention-enhanced masked autoencoder framework that consists of a pre-training stage with unlabeled auxiliary samples and a fine-tuning stage with limited labeled samples. During the pre-training stage, we employ a teacher-student training framework that integrates masked sample reconstruction and teacher-student feature alignment. In particular, for the student network, we introduce an attention-enhanced masking strategy and a scaled mean squared error loss to enhance representation capabilities. During the fine-tuning stage, the pre-trained feature extractor and classifier are jointly optimized on the limited labeled data. Simulation experiments demonstrate that our proposed framework outperforms other state-of-the-art methods by using an open-source LoRa dataset.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"30 ","pages":"1240-1244"},"PeriodicalIF":4.4,"publicationDate":"2026-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147362321","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 : 2026-02-19DOI: 10.1109/LCOMM.2026.3664862
Ajay Kumar;Sateesh Kumar Awasthi
Estimation of the flight velocity of unmanned aerial vehicles (UAVs) in cellular networks is essential for effective resource management. In this letter, we present a novel approach for estimating the flying velocity of a cellular-connected UAV along a three-dimensional (3D) linear trajectory using handover count. The azimuth and elevation angles of the UAV, along with its velocity, ground base station (GBS) density, and the handover control parameters, all have a significant impact on the handover count for a UAV flying along a 3D linear path. To provide a realistic description of the wireless environment, we use stochastic geometry in our system model to depict the distribution of GBSs with a density of $lambda $ . We use the observed handover count as the primary input and structure the velocity estimate problem as a maximum likelihood estimate (MLE) problem. The Cramér-Rao Lower Bound (CRLB) for the UAV estimated velocity is also determined. The proposed estimator shows statistical efficiency, as its variance closely matches the Cramér-Rao Lower Bound (CRLB). The numerical findings validate the accuracy of our approach for estimating the velocity of the UAV in a realistic cellular environment.
{"title":"Cellular-Connected UAV Flight Velocity Estimation Using a 3D Linear Path","authors":"Ajay Kumar;Sateesh Kumar Awasthi","doi":"10.1109/LCOMM.2026.3664862","DOIUrl":"https://doi.org/10.1109/LCOMM.2026.3664862","url":null,"abstract":"Estimation of the flight velocity of unmanned aerial vehicles (UAVs) in cellular networks is essential for effective resource management. In this letter, we present a novel approach for estimating the flying velocity of a cellular-connected UAV along a three-dimensional (3D) linear trajectory using handover count. The azimuth and elevation angles of the UAV, along with its velocity, ground base station (GBS) density, and the handover control parameters, all have a significant impact on the handover count for a UAV flying along a 3D linear path. To provide a realistic description of the wireless environment, we use stochastic geometry in our system model to depict the distribution of GBSs with a density of <inline-formula> <tex-math>$lambda $ </tex-math></inline-formula>. We use the observed handover count as the primary input and structure the velocity estimate problem as a maximum likelihood estimate (MLE) problem. The Cramér-Rao Lower Bound (CRLB) for the UAV estimated velocity is also determined. The proposed estimator shows statistical efficiency, as its variance closely matches the Cramér-Rao Lower Bound (CRLB). The numerical findings validate the accuracy of our approach for estimating the velocity of the UAV in a realistic cellular environment.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"30 ","pages":"1171-1174"},"PeriodicalIF":4.4,"publicationDate":"2026-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147299513","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 : 2026-02-16DOI: 10.1109/LCOMM.2026.3665107
Raed Mesleh;Saud Althunibat
A computationally secure physical-layer obfuscation framework for multiple-input multiple-output (MIMO) systems based on space shift keying (SSK) is proposed in this letter, while accounting for imperfect channel estimation and spatial channel correlation. The obfuscation principle relies on exploiting channel reciprocity in time-division duplexing (TDD), whereby the transmitter and the legitimate receiver independently estimate per-antenna fading powers and construct an identical permutation vector to reorder the transmit constellation in each coherence interval. For an SSK system with $N_{t}$ transmit antennas, the permutation is derived from the relative ordering of per-antenna channel powers. This design allows for refreshed key that avoids explicit key exchange with negligible signaling overhead. At the same time, an eavesdropper observing an independent or partially correlated channel is forced to decode using a mismatched constellation. Consequently, decoding ambiguity is significantly increased, enlarging the brute-force search space to the order of $N_{t}!$ , which render blind constellation recovery computationally infeasible. Results demonstrate that channel estimation errors and spatial correlation impairments introduce only modest performance degradation at the legitimate receiver while strongly suppressing the eavesdropper’s achievable information rate. Performance is investigated in terms of average bit error rate (ABER), mutual information (MI), generalized mutual information (GMI), equivocation, and information leakage.
{"title":"Physical-Layer Obfuscation in MIMO–SSK Systems With Imperfect CSI and Spatial Correlation","authors":"Raed Mesleh;Saud Althunibat","doi":"10.1109/LCOMM.2026.3665107","DOIUrl":"https://doi.org/10.1109/LCOMM.2026.3665107","url":null,"abstract":"A computationally secure physical-layer obfuscation framework for multiple-input multiple-output (MIMO) systems based on space shift keying (SSK) is proposed in this letter, while accounting for imperfect channel estimation and spatial channel correlation. The obfuscation principle relies on exploiting channel reciprocity in time-division duplexing (TDD), whereby the transmitter and the legitimate receiver independently estimate per-antenna fading powers and construct an identical permutation vector to reorder the transmit constellation in each coherence interval. For an SSK system with <inline-formula> <tex-math>$N_{t}$ </tex-math></inline-formula> transmit antennas, the permutation is derived from the relative ordering of per-antenna channel powers. This design allows for refreshed key that avoids explicit key exchange with negligible signaling overhead. At the same time, an eavesdropper observing an independent or partially correlated channel is forced to decode using a mismatched constellation. Consequently, decoding ambiguity is significantly increased, enlarging the brute-force search space to the order of <inline-formula> <tex-math>$N_{t}!$ </tex-math></inline-formula>, which render blind constellation recovery computationally infeasible. Results demonstrate that channel estimation errors and spatial correlation impairments introduce only modest performance degradation at the legitimate receiver while strongly suppressing the eavesdropper’s achievable information rate. Performance is investigated in terms of average bit error rate (ABER), mutual information (MI), generalized mutual information (GMI), equivocation, and information leakage.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"30 ","pages":"1156-1160"},"PeriodicalIF":4.4,"publicationDate":"2026-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147299591","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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