Pub Date : 2025-12-24DOI: 10.1109/LCOMM.2025.3648306
Yaoxian Gao;Yongmei Sun;Yuefeng Ji
In quantum-classical coexistence systems, classical noise and system loss can significantly affect the performance of quantum key distribution (QKD), while the fixed-parameter QKD (FPQ) cannot adapt to varying conditions. In this letter, we propose a local search algorithm (LSA) for QKD to optimize the parameters in wavelength division multiplexing (WDM) and space division multiplexing (SDM) systems. Simulation results show that LSA can achieve 99.9% performance of the exhaustive search algorithm, while significantly reducing computational complexity. Moreover, LSA improves QKD performance by 31.9% over standard single mode fiber and 24.5% over multicore fiber in quantum-classical coexistence systems.
{"title":"Parameter Optimization of Quantum Key Distribution in Quantum-Classical WDM-SDM Coexistence Systems","authors":"Yaoxian Gao;Yongmei Sun;Yuefeng Ji","doi":"10.1109/LCOMM.2025.3648306","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3648306","url":null,"abstract":"In quantum-classical coexistence systems, classical noise and system loss can significantly affect the performance of quantum key distribution (QKD), while the fixed-parameter QKD (FPQ) cannot adapt to varying conditions. In this letter, we propose a local search algorithm (LSA) for QKD to optimize the parameters in wavelength division multiplexing (WDM) and space division multiplexing (SDM) systems. Simulation results show that LSA can achieve 99.9% performance of the exhaustive search algorithm, while significantly reducing computational complexity. Moreover, LSA improves QKD performance by 31.9% over standard single mode fiber and 24.5% over multicore fiber in quantum-classical coexistence systems.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"30 ","pages":"697-701"},"PeriodicalIF":4.4,"publicationDate":"2025-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145886682","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 : 2025-12-24DOI: 10.1109/LCOMM.2025.3648035
Himani Verma;Kamal Singh;Ranjan K. Mallik
Coherent free-space optical (FSO) communication is recognized as a key enabler for ultra-high-capacity fronthaul and backhaul links in next-generation wireless networks. Spectrally efficient $M$ –ary quadrature amplitude modulation (MQAM) formats are well-suited for these links. However, theoretical analyses of adaptive MQAM transmissions over terrestrial FSO channels remain limited. In this letter, we first derive the spectral efficiency limit of adaptive unconstrained MQAM over gamma-gamma turbulence with pointing error. We then show that adaptive transmissions using only six square MQAM constellations performs close to the theoretical limit (within ${0.10 - 0.12}$ bits/s/Hz) across a wide range of signal-to-noise ratios and channel conditions.
{"title":"Maximum Spectral Efficiency With Adaptive MQAM Transmissions Over Terrestrial Coherent FSO Links","authors":"Himani Verma;Kamal Singh;Ranjan K. Mallik","doi":"10.1109/LCOMM.2025.3648035","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3648035","url":null,"abstract":"Coherent free-space optical (FSO) communication is recognized as a key enabler for ultra-high-capacity fronthaul and backhaul links in next-generation wireless networks. Spectrally efficient <inline-formula> <tex-math>$M$ </tex-math></inline-formula>–ary quadrature amplitude modulation (MQAM) formats are well-suited for these links. However, theoretical analyses of adaptive MQAM transmissions over terrestrial FSO channels remain limited. In this letter, we first derive the spectral efficiency limit of adaptive unconstrained MQAM over gamma-gamma turbulence with pointing error. We then show that adaptive transmissions using only six square MQAM constellations performs close to the theoretical limit (within <inline-formula> <tex-math>${0.10 - 0.12}$ </tex-math></inline-formula> bits/s/Hz) across a wide range of signal-to-noise ratios and channel conditions.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"30 ","pages":"677-681"},"PeriodicalIF":4.4,"publicationDate":"2025-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145886670","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}
This letter presents the first study on the feasibility of automatic modulation classification (AMC) for orthogonal time-sequency multiplexing (OTSM). Through rigorous analyses, it is observed that Walsh-Hadamard transform (WHT) spreading induces global feature mixing, severely degrading modulation-specific structures. Analyses reveal up to a 93.55% loss in magnitude-domain distinctiveness using Wasserstein distance and show that performance degradation intensifies with the presence of correlated modulation schemes. Benchmarking with a dual-channel vision-transformer (ViT) in the extended vehicular A (EVA) channel shows that OTSM underperforms OTFS by 8.58% (100 km/h) and 9.32% (500 km/h) on average. Even with larger frames ($64 times 64$ ) and doubled training data, OTSM accuracy saturates at 39.13%, far below OTFS’s 54.59%. Furthermore, impact of timing and carrier frequency offsets in OTSM-based AMC systems are evaluated and compared with OTFS and OFDM counterparts under similar channel conditions. The findings underscore that WHT-induced feature homogenization, not channel impairment, is the fundamental classification bottleneck.
{"title":"On the Effect of Walsh–Hadamard Spreading on Modulation Classification in OTSM Transceivers","authors":"Tonmoy Rajkhowa;Sanjeev Sharma;Kuntal Deka;Om Jee Pandey","doi":"10.1109/LCOMM.2025.3647601","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3647601","url":null,"abstract":"This letter presents the first study on the feasibility of automatic modulation classification (AMC) for orthogonal time-sequency multiplexing (OTSM). Through rigorous analyses, it is observed that Walsh-Hadamard transform (WHT) spreading induces global feature mixing, severely degrading modulation-specific structures. Analyses reveal up to a 93.55% loss in magnitude-domain distinctiveness using Wasserstein distance and show that performance degradation intensifies with the presence of correlated modulation schemes. Benchmarking with a dual-channel vision-transformer (ViT) in the extended vehicular A (EVA) channel shows that OTSM underperforms OTFS by 8.58% (100 km/h) and 9.32% (500 km/h) on average. Even with larger frames (<inline-formula> <tex-math>$64 times 64$ </tex-math></inline-formula>) and doubled training data, OTSM accuracy saturates at 39.13%, far below OTFS’s 54.59%. Furthermore, impact of timing and carrier frequency offsets in OTSM-based AMC systems are evaluated and compared with OTFS and OFDM counterparts under similar channel conditions. The findings underscore that WHT-induced feature homogenization, not channel impairment, is the fundamental classification bottleneck.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"30 ","pages":"652-656"},"PeriodicalIF":4.4,"publicationDate":"2025-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145886669","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 : 2025-12-23DOI: 10.1109/LCOMM.2025.3647492
Jie Yang;Wanchen Hu;Shitong Bai;Shuangyang Li;Siyao Li;Kai Wan;Xin Wang
Millimeter-wave (mmWave) technology is a key enabling technology for next-generation wireless communications. However, beam prediction (BP) in millimeter-wave massive multiple-input multiple-output (MIMO) systems is challenging in high mobility scenarios, especially in non-stationary time-varying hybrid-field channels. In this case, the number of multi paths, time delay, angle of departure (AoD), Doppler offset, and the propagation distance vary simultaneously at different time instants. In this letter, we introduce a BP framework leveraging generative large language models (LLM), specifically GPT-2. The proposed BP-GPT approach utilizes historical channel state information (CSI) to predict optimal beamforming vectors that maximize spectral efficiency in these non-stationary time-varying hybrid-field conditions. Extensive simulations demonstrate the superior performance and robustness of BP-GPT over conventional neural network-based methods.
{"title":"Large Language Models for Beam Prediction Under the mmWave Massive MIMO Hybrid-Field Channels","authors":"Jie Yang;Wanchen Hu;Shitong Bai;Shuangyang Li;Siyao Li;Kai Wan;Xin Wang","doi":"10.1109/LCOMM.2025.3647492","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3647492","url":null,"abstract":"Millimeter-wave (mmWave) technology is a key enabling technology for next-generation wireless communications. However, beam prediction (BP) in millimeter-wave massive multiple-input multiple-output (MIMO) systems is challenging in high mobility scenarios, especially in non-stationary time-varying hybrid-field channels. In this case, the number of multi paths, time delay, angle of departure (AoD), Doppler offset, and the propagation distance vary simultaneously at different time instants. In this letter, we introduce a BP framework leveraging generative large language models (LLM), specifically GPT-2. The proposed BP-GPT approach utilizes historical channel state information (CSI) to predict optimal beamforming vectors that maximize spectral efficiency in these non-stationary time-varying hybrid-field conditions. Extensive simulations demonstrate the superior performance and robustness of BP-GPT over conventional neural network-based methods.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"30 ","pages":"627-631"},"PeriodicalIF":4.4,"publicationDate":"2025-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145886648","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 : 2025-12-23DOI: 10.1109/LCOMM.2025.3647715
Yanwei Shao;Yuan Zeng;Yi Gong
In wireless communication systems, the modulated radio signals are commonly susceptible to sensor-level changes and defects during transmission, resulting in data distribution shifts in the received signals. Deep learning-based automatic modulation recognition (AMR) has made significant strides but still struggles with performance on out-of-distribution (OOD) samples due to domain shifts in practical communication systems. Test-time adaptation (TTA) methods adapt models using test samples at inference time, emerging as a promising solution to this challenge. In this letter, we propose a novel self-supervised TTA strategy to adapt mask autoencoders to better recognize modulation modes in OOD scenarios. The key idea is to optimize the main modulation recognition task and the modulated signal spectrogram reconstruction task during training toward effective feature extraction, and design an entropy control mechanism to adapt the model toward better modulation recognition of the test signals. With extensive experiments, we show that the proposed method effectively improves the performance of TTA for AMR in various distribution shift scenarios.
{"title":"Test-Time Adaptation for Robust Modulation Recognition Under Unknown Channel Distortions","authors":"Yanwei Shao;Yuan Zeng;Yi Gong","doi":"10.1109/LCOMM.2025.3647715","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3647715","url":null,"abstract":"In wireless communication systems, the modulated radio signals are commonly susceptible to sensor-level changes and defects during transmission, resulting in data distribution shifts in the received signals. Deep learning-based automatic modulation recognition (AMR) has made significant strides but still struggles with performance on out-of-distribution (OOD) samples due to domain shifts in practical communication systems. Test-time adaptation (TTA) methods adapt models using test samples at inference time, emerging as a promising solution to this challenge. In this letter, we propose a novel self-supervised TTA strategy to adapt mask autoencoders to better recognize modulation modes in OOD scenarios. The key idea is to optimize the main modulation recognition task and the modulated signal spectrogram reconstruction task during training toward effective feature extraction, and design an entropy control mechanism to adapt the model toward better modulation recognition of the test signals. With extensive experiments, we show that the proposed method effectively improves the performance of TTA for AMR in various distribution shift scenarios.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"30 ","pages":"657-661"},"PeriodicalIF":4.4,"publicationDate":"2025-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145886673","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}
This letter proposes a method to enhance satellite communication security based on high-dimensional spatiotemporal chaos. It separates information into two parts and processes both parts simultaneously using a single 2D spatiotemporal chaotic signal matrix. One part is mapped to the spatial-domain index value as Chaos Shift Keying (CSK), and another part is spread spectrum (SS) using a sequence generated by the spatiotemporal chaotic time-domain array determined by the index value. At the receiver, the spatiotemporal chaotic matrix is reconstructed to demodulate the spatial index and then despread the chaotic sequence. CSK and SS using one spatiotemporal chaos can simplify the transmitting and receiving process. And the theoretical analysis and simulation results show that the method proposed in this letter can improve the security performance while reducing the bit error rate.
{"title":"Spatiotemporal Chaotic Spread Dimension Shift Keying for Enhanced Symbol Security","authors":"Yinxia Zhu;Jian Zhang;Hongpeng Zhu;Bangning Zhang;Daoxing Guo;Jian Cheng","doi":"10.1109/LCOMM.2025.3647553","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3647553","url":null,"abstract":"This letter proposes a method to enhance satellite communication security based on high-dimensional spatiotemporal chaos. It separates information into two parts and processes both parts simultaneously using a single 2D spatiotemporal chaotic signal matrix. One part is mapped to the spatial-domain index value as Chaos Shift Keying (CSK), and another part is spread spectrum (SS) using a sequence generated by the spatiotemporal chaotic time-domain array determined by the index value. At the receiver, the spatiotemporal chaotic matrix is reconstructed to demodulate the spatial index and then despread the chaotic sequence. CSK and SS using one spatiotemporal chaos can simplify the transmitting and receiving process. And the theoretical analysis and simulation results show that the method proposed in this letter can improve the security performance while reducing the bit error rate.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"30 ","pages":"752-756"},"PeriodicalIF":4.4,"publicationDate":"2025-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145929382","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 : 2025-12-22DOI: 10.1109/LCOMM.2025.3647351
Haoran Gao;Yinuo Du;Yi Li;Hanying Zhao;Yuan Shen
Network ranging plays a role in achieving high-accuracy clock synchronization and localization in large-scale networks. However, compared to point-to-point ranging, it is more vulnerable to timestamp anomalies, since a single corrupted timestamp can influence multiple range estimates. In contrast to conventional distance-based approaches, this paper proposes a collaborative timestamp-based anomaly detection method that enhances security by sequentially identifying malicious nodes and spoofed timestamps. Furthermore, a timestamp-based maximum likelihood (ML) localization method with alternating optimization is proposed for robust localization and clock synchronization. Simulation and experimental results demonstrate that our method significantly enhances the robustness of network ranging.
{"title":"Detecting Timestamp Anomalies in Network Ranging","authors":"Haoran Gao;Yinuo Du;Yi Li;Hanying Zhao;Yuan Shen","doi":"10.1109/LCOMM.2025.3647351","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3647351","url":null,"abstract":"Network ranging plays a role in achieving high-accuracy clock synchronization and localization in large-scale networks. However, compared to point-to-point ranging, it is more vulnerable to timestamp anomalies, since a single corrupted timestamp can influence multiple range estimates. In contrast to conventional distance-based approaches, this paper proposes a collaborative timestamp-based anomaly detection method that enhances security by sequentially identifying malicious nodes and spoofed timestamps. Furthermore, a timestamp-based maximum likelihood (ML) localization method with alternating optimization is proposed for robust localization and clock synchronization. Simulation and experimental results demonstrate that our method significantly enhances the robustness of network ranging.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"30 ","pages":"667-671"},"PeriodicalIF":4.4,"publicationDate":"2025-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145886533","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 : 2025-12-22DOI: 10.1109/LCOMM.2025.3646724
Qianfan Wang;Jifan Liang;Lvzhou Li;Linqi Song;Xiao Ma
Belief propagation (BP) combined with ordered statistics decoding (OSD) can achieve near-optimal logical error rates for surface codes. However, OSD requires high-latency and unstable-complexity Gaussian elimination (GE), limiting its practicality. In this letter, we propose BP-LCGCD, a GE-free and high-performance decoder that replaces the GE-based OSD with the GE-free LC-GCD. Moreover, in contrast to the original BP-OSD, which adopts a single fixed normalization factor $alpha $ , we further propose a list-parameterized variant, BP-LCGCD+$alpha $ , which performs multiple BP decodings with different $alpha $ to generate diverse posterior LLRs. We present complexity analysis, demonstrating that at low physical error rates, the average decoding complexity of the proposed algorithm approaches that of standard BP. Simulation results demonstrate that BP-LCGCD achieves logical error rates close to BP-OSD, while BP-LCGCD+$alpha $ nearly matches the performance of the BP-OSD. They also show that both proposed decoders significantly outperform standard BP and minimum-weight perfect matching (MWPM) in terms of logical error rate and threshold.
{"title":"BP-LCGCD: A Gaussian-Elimination-Free and High-Performance Decoder for Surface Codes","authors":"Qianfan Wang;Jifan Liang;Lvzhou Li;Linqi Song;Xiao Ma","doi":"10.1109/LCOMM.2025.3646724","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3646724","url":null,"abstract":"Belief propagation (BP) combined with ordered statistics decoding (OSD) can achieve near-optimal logical error rates for surface codes. However, OSD requires high-latency and unstable-complexity Gaussian elimination (GE), limiting its practicality. In this letter, we propose BP-LCGCD, a GE-free and high-performance decoder that replaces the GE-based OSD with the GE-free LC-GCD. Moreover, in contrast to the original BP-OSD, which adopts a single fixed normalization factor <inline-formula> <tex-math>$alpha $ </tex-math></inline-formula>, we further propose a list-parameterized variant, BP-LCGCD+<inline-formula> <tex-math>$alpha $ </tex-math></inline-formula>, which performs multiple BP decodings with different <inline-formula> <tex-math>$alpha $ </tex-math></inline-formula> to generate diverse posterior LLRs. We present complexity analysis, demonstrating that at low physical error rates, the average decoding complexity of the proposed algorithm approaches that of standard BP. Simulation results demonstrate that BP-LCGCD achieves logical error rates close to BP-OSD, while BP-LCGCD+<inline-formula> <tex-math>$alpha $ </tex-math></inline-formula> nearly matches the performance of the BP-OSD. They also show that both proposed decoders significantly outperform standard BP and minimum-weight perfect matching (MWPM) in terms of logical error rate and threshold.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"30 ","pages":"782-786"},"PeriodicalIF":4.4,"publicationDate":"2025-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145929521","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}
This letter investigates a two-tier Uncrewed Aerial Vehicle (UAV) assisted Cellular Internet of Things (IoT) architecture inspired by a practical LoRa/NB-IoT deployment, where the fronthaul consists of IoT devices accessing a UAV-mounted LoRa gateway via slotted ALOHA with multi-packet reception (MPR), and the backhaul relays decoded packets to a terrestrial base station (BS) over a coded NB-IoT link. We develop an analytical framework that jointly models fronthaul contention with MPR and coded short-packet transmission over a realistic backhaul channel. The results reveal system configurations that maximize end-to-end throughput while maintaining efficient backhaul utilization across varying UAV–BS distances.
{"title":"Two-Tier UAV-Assisted CIoT Networks: Joint Fronthaul and Backhaul Throughput Analysis","authors":"Srdjan Sobot;Milica Petkovic;Marko Beko;Dejan Vukobratovic","doi":"10.1109/LCOMM.2025.3646026","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3646026","url":null,"abstract":"This letter investigates a two-tier Uncrewed Aerial Vehicle (UAV) assisted Cellular Internet of Things (IoT) architecture inspired by a practical LoRa/NB-IoT deployment, where the fronthaul consists of IoT devices accessing a UAV-mounted LoRa gateway via slotted ALOHA with multi-packet reception (MPR), and the backhaul relays decoded packets to a terrestrial base station (BS) over a coded NB-IoT link. We develop an analytical framework that jointly models fronthaul contention with MPR and coded short-packet transmission over a realistic backhaul channel. The results reveal system configurations that maximize end-to-end throughput while maintaining efficient backhaul utilization across varying UAV–BS distances.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"30 ","pages":"592-596"},"PeriodicalIF":4.4,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145830797","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 : 2025-12-18DOI: 10.1109/LCOMM.2025.3645846
Xiaojing Yan;Saeed Razavikia;Carlo Fischione
Recently, over-the-air computation (AirComp) leverages the superposition property of wireless channels to enable efficient function computation over a multiple access channel (MAC). However, existing digital AirComp methods either rely on single-symbol modulation, which limits flexibility and robustness, or on multi-symbol extensions that suffer from high complexity or approximation errors. To overcome these limitations, we propose a new multi-symbol modulation framework, termed sequential modulation for AirComp (SeMAC), which encodes each input into a sequence of symbols with distinct constellation diagrams across multiple time slots. This approach increases design flexibility and robustness against channel noise. Specifically, the modulation design is formulated as a non-convex optimization problem and efficiently solved through a successive convex approximation (SCA) combined with stochastic subgradient descent (SSD). For fixed modulation formats, we further develop SeMAC with power adaptation (SeMAC-PA) to adjusts transmit power and phase while preserving the modulation structure. Notably, numerical results show that SeMAC improves computation accuracy by up to 14 dB compared to the existing methods for computing nonlinear functions such as the product function.
{"title":"Multi-Symbol Digital AirComp via Modulation Design and Power Adaptation","authors":"Xiaojing Yan;Saeed Razavikia;Carlo Fischione","doi":"10.1109/LCOMM.2025.3645846","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3645846","url":null,"abstract":"Recently, over-the-air computation (AirComp) leverages the superposition property of wireless channels to enable efficient function computation over a multiple access channel (MAC). However, existing digital AirComp methods either rely on single-symbol modulation, which limits flexibility and robustness, or on multi-symbol extensions that suffer from high complexity or approximation errors. To overcome these limitations, we propose a new multi-symbol modulation framework, termed sequential modulation for AirComp (SeMAC), which encodes each input into a sequence of symbols with distinct constellation diagrams across multiple time slots. This approach increases design flexibility and robustness against channel noise. Specifically, the modulation design is formulated as a non-convex optimization problem and efficiently solved through a successive convex approximation (SCA) combined with stochastic subgradient descent (SSD). For fixed modulation formats, we further develop SeMAC with power adaptation (SeMAC-PA) to adjusts transmit power and phase while preserving the modulation structure. Notably, numerical results show that SeMAC improves computation accuracy by up to 14 dB compared to the existing methods for computing nonlinear functions such as the product function.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"30 ","pages":"602-606"},"PeriodicalIF":4.4,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145830812","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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