Pub Date : 2025-12-15DOI: 10.1109/LCOMM.2025.3644395
Thanh V. Pham;Susumu Ishihara
Optical orthogonal frequency-division multiplexing (OFDM) and probabilistic constellation shaping (PCS) have emerged as powerful techniques to enhance the performance of optical wireless communications (OWC) systems. While PCS improves spectral efficiency and adaptability, we show that its integration with optical OFDM can inadvertently increase the peak-to-average power ratio (PAPR) of the signal, exacerbating clipping distortion due to signal clipping. This letter investigates the impact of PCS on the PAPR of direct current-biased optical OFDM (DCO-OFDM) waveforms and proposes an optimization of PCS that maximizes channel capacity, considering clipping distortion. The optimization problem is shown to be complex and non-convex. We thus present a suboptimal yet efficient solving approach based on projected gradient descent to solve the problem. Simulation results demonstrate the superiority of the proposed approach over the conventional uniform signaling, particularly under severe clipping distortion conditions.
{"title":"Optimization of Probabilistic Constellation Shaping for Optical OFDM Systems With Clipping Distortion","authors":"Thanh V. Pham;Susumu Ishihara","doi":"10.1109/LCOMM.2025.3644395","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3644395","url":null,"abstract":"Optical orthogonal frequency-division multiplexing (OFDM) and probabilistic constellation shaping (PCS) have emerged as powerful techniques to enhance the performance of optical wireless communications (OWC) systems. While PCS improves spectral efficiency and adaptability, we show that its integration with optical OFDM can inadvertently increase the peak-to-average power ratio (PAPR) of the signal, exacerbating clipping distortion due to signal clipping. This letter investigates the impact of PCS on the PAPR of direct current-biased optical OFDM (DCO-OFDM) waveforms and proposes an optimization of PCS that maximizes channel capacity, considering clipping distortion. The optimization problem is shown to be complex and non-convex. We thus present a suboptimal yet efficient solving approach based on projected gradient descent to solve the problem. Simulation results demonstrate the superiority of the proposed approach over the conventional uniform signaling, particularly under severe clipping distortion conditions.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"30 ","pages":"562-566"},"PeriodicalIF":4.4,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145830856","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}
Orthogonal Time Frequency Space (OTFS) suffers from high peak-to-average power ratio (PAPR) when the number of Doppler bins is large. To address this issue, a discrete Fourier transform spread OTFS (DFT-s-OTFS) scheme is employed by applying DFT spreading across the Doppler dimension. This letter presents a thorough PAPR analysis of DFT-s-OTFS using different pulse shaping filters and resource allocation strategies. Specifically, we derive a PAPR upper bound of DFT-s-OTFS of interleaved and block Doppler resource allocation schemes. Our analysis reveals that DFT-s-OTFS with interleaved allocation yields a lower PAPR than that of block allocation. Furthermore, we show that interleaved allocation produces a periodic time-domain signal composed of repeated quadrature amplitude modulated (QAM) symbols which simplifies the transmitter design. From our analytical results, the root raised cosine (RRC) pulse generally results in a higher maximum PAPR compared to the rectangular pulse. Simulation results confirm the validity of the derived PAPR upper bounds. Furthermore, we also demonstrate through BER simulation analysis that the DFT-s-OTFS gives the same performance as OTFS without DFT spreading.
{"title":"PAPR of DFT-s-OTFS With Pulse Shaping","authors":"Jialiang Zhu;Sanoopkumar Pungayil Sasindran;Arman Farhang","doi":"10.1109/LCOMM.2025.3643648","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3643648","url":null,"abstract":"Orthogonal Time Frequency Space (OTFS) suffers from high peak-to-average power ratio (PAPR) when the number of Doppler bins is large. To address this issue, a discrete Fourier transform spread OTFS (DFT-s-OTFS) scheme is employed by applying DFT spreading across the Doppler dimension. This letter presents a thorough PAPR analysis of DFT-s-OTFS using different pulse shaping filters and resource allocation strategies. Specifically, we derive a PAPR upper bound of DFT-s-OTFS of interleaved and block Doppler resource allocation schemes. Our analysis reveals that DFT-s-OTFS with interleaved allocation yields a lower PAPR than that of block allocation. Furthermore, we show that interleaved allocation produces a periodic time-domain signal composed of repeated quadrature amplitude modulated (QAM) symbols which simplifies the transmitter design. From our analytical results, the root raised cosine (RRC) pulse generally results in a higher maximum PAPR compared to the rectangular pulse. Simulation results confirm the validity of the derived PAPR upper bounds. Furthermore, we also demonstrate through BER simulation analysis that the DFT-s-OTFS gives the same performance as OTFS without DFT spreading.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"30 ","pages":"512-516"},"PeriodicalIF":4.4,"publicationDate":"2025-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11299050","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145778224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-11DOI: 10.1109/LCOMM.2025.3642810
Li-Hsiang Shen
This letter proposes a novel six-dimensional movable metasurface (6DMM)-assisted downlink non-orthogonal multiple access (NOMA) system, in which a conventional base station (BS) equipped with fixed antennas serves multiple users with the assistance of a reconfigurable intelligent surface (RIS) with six-dimensional spatial configurability. In contrast to traditional RIS with static surface, the proposed 6DMM architecture allows each element to dynamically adjust its position and orient the whole metasurface in yaw-pitch-roll axes, enabling both spatial and electromagnetic controls. We formulate a sum-rate maximization problem that jointly optimizes the BS NOMA-based beamforming, phase-shifts, element positions, and rotation angles of metasurface under constraints of NOMA power levels, unit-modulus of phase-shifts, power budget, inter-element separation and boundaries of element position/orientation. Due to non-convexity and high-dimensionality, we employ a probabilistic cross-entropy optimization (CEO) scheme to iteratively refine the solution distribution based on maximizing likelihood and elite solution sampling. Simulation results show that the proposed CEO-based 6DMM-NOMA architecture achieves substantial rate performance gains compared to 6DMM sub-structures, conventional static RIS, and other multiple access mechanisms. It also highlights the effectiveness of CEO providing probabilistic optimization for solving high-dimensional scalable metasurface.
{"title":"6D Movable Metasurface (6DMM) in Downlink NOMA Transmissions","authors":"Li-Hsiang Shen","doi":"10.1109/LCOMM.2025.3642810","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3642810","url":null,"abstract":"This letter proposes a novel six-dimensional movable metasurface (6DMM)-assisted downlink non-orthogonal multiple access (NOMA) system, in which a conventional base station (BS) equipped with fixed antennas serves multiple users with the assistance of a reconfigurable intelligent surface (RIS) with six-dimensional spatial configurability. In contrast to traditional RIS with static surface, the proposed 6DMM architecture allows each element to dynamically adjust its position and orient the whole metasurface in yaw-pitch-roll axes, enabling both spatial and electromagnetic controls. We formulate a sum-rate maximization problem that jointly optimizes the BS NOMA-based beamforming, phase-shifts, element positions, and rotation angles of metasurface under constraints of NOMA power levels, unit-modulus of phase-shifts, power budget, inter-element separation and boundaries of element position/orientation. Due to non-convexity and high-dimensionality, we employ a probabilistic cross-entropy optimization (CEO) scheme to iteratively refine the solution distribution based on maximizing likelihood and elite solution sampling. Simulation results show that the proposed CEO-based 6DMM-NOMA architecture achieves substantial rate performance gains compared to 6DMM sub-structures, conventional static RIS, and other multiple access mechanisms. It also highlights the effectiveness of CEO providing probabilistic optimization for solving high-dimensional scalable metasurface.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"30 ","pages":"517-521"},"PeriodicalIF":4.4,"publicationDate":"2025-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145778157","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 : 2025-12-11DOI: 10.1109/LCOMM.2025.3639746
Lei Qian;Ang Li;Chenyan Zhang;Wenwen Jiang;Chenguang Zhang;Nuo Huang
The stochastic terminal rotations and random link blockages in visible light communication (VLC) systems can significantly degrade statistical delay performance. To address this, this letter aims to mathematically characterize the statistical delay for VLC systems. First, we propose a Markov-modulated Laplace process (MMLP) service model capturing burstiness from orientation dynamics and blockages. Then, we analytically derive the probability density function of the achievable transmission rate under dynamic channel conditions. Finally, we establish closed-form delay bounds using a unified exponential supermartingale construction. Monte Carlo simulations validate our bounds’ superior accuracy over traditional effective bandwidth/effective capacity methods, particularly in high-burstiness scenarios. Specifically, the proposed bound achieves a delay violation probability from 10-2 to 10-3 at a delay threshold of 1 ms, which meets the stringent requirements of delay-sensitive applications.
{"title":"Statistical Delay Characterization for Visible Light Communication Under Realistic Dynamics","authors":"Lei Qian;Ang Li;Chenyan Zhang;Wenwen Jiang;Chenguang Zhang;Nuo Huang","doi":"10.1109/LCOMM.2025.3639746","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3639746","url":null,"abstract":"The stochastic terminal rotations and random link blockages in visible light communication (VLC) systems can significantly degrade statistical delay performance. To address this, this letter aims to mathematically characterize the statistical delay for VLC systems. First, we propose a Markov-modulated Laplace process (MMLP) service model capturing burstiness from orientation dynamics and blockages. Then, we analytically derive the probability density function of the achievable transmission rate under dynamic channel conditions. Finally, we establish closed-form delay bounds using a unified exponential supermartingale construction. Monte Carlo simulations validate our bounds’ superior accuracy over traditional effective bandwidth/effective capacity methods, particularly in high-burstiness scenarios. Specifically, the proposed bound achieves a delay violation probability from 10-2 to 10-3 at a delay threshold of 1 ms, which meets the stringent requirements of delay-sensitive applications.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"30 ","pages":"502-506"},"PeriodicalIF":4.4,"publicationDate":"2025-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145778266","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}
Current semantic communication methods encode all features uniformly, however, downstream models are far more sensitive to distortions in high-frequency semantic features than in low-frequency ones. To address this issue, we propose an Ordered Hierarchical Encoding (OHE) framework for semantic image transmission. OHE employs a hierarchical encoding scheme that combine cascaded pooling with cross-attention to construct multi-scale semantic representations, effectively decoupling and extracting low-frequency and high-frequency features. Furthermore, an ordered representation mechanism with random prefix masking enforces a natural prioritization of semantic information, enabling progressive reconstruction and supporting simple, flexible rate control. Extensive experiments conducted on various datasets demonstrate that our method outperforms the baselines.
{"title":"Ordered Hierarchical Encoding for Robust Image Semantic Communication","authors":"Huogen Yang;Zhehao Zhou;Zhongmin Yang;Xianchao Zhang;Shuxiao Ye;Changheng Wang;Guangxue Yue","doi":"10.1109/LCOMM.2025.3642888","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3642888","url":null,"abstract":"Current semantic communication methods encode all features uniformly, however, downstream models are far more sensitive to distortions in high-frequency semantic features than in low-frequency ones. To address this issue, we propose an Ordered Hierarchical Encoding (OHE) framework for semantic image transmission. OHE employs a hierarchical encoding scheme that combine cascaded pooling with cross-attention to construct multi-scale semantic representations, effectively decoupling and extracting low-frequency and high-frequency features. Furthermore, an ordered representation mechanism with random prefix masking enforces a natural prioritization of semantic information, enabling progressive reconstruction and supporting simple, flexible rate control. Extensive experiments conducted on various datasets demonstrate that our method outperforms the baselines.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"30 ","pages":"532-536"},"PeriodicalIF":4.4,"publicationDate":"2025-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145830814","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 : 2025-12-10DOI: 10.1109/LCOMM.2025.3642793
Rui Xu;Yuanhang He;Gaolei Li;Chaofeng Zhang;Jianhua Li
Remote embodied intelligence relies on the seamless transmission of rich multi-modal sensory information, particularly vision and touch, to enable intelligent agents to collaboratively perceive, interact with, and manipulate physical environments. However, transmitting such high-dimensional and heterogeneous data over wireless channels in real time poses substantial challenges in terms of bandwidth, latency, and semantic integrity. In this letter, we propose a novel vision-tactile fusion semantic communication (VT-FSC) framework tailored for remote embodied intelligence applications. By leveraging cross-modal feature fusion and attention-guided semantic compression, the proposed system transforms raw visual and tactile data into a unified low-dimensional semantic representation. This compact representation is then robustly transmitted through noisy wireless channels and decoded at the receiver to reconstruct both the visual scene and the tactile signal accurately. To ensure perceptual alignment, encoder and decoder are jointly optimized via human-in-the-loop feedback mechanisms. Experimental results in the multi-model dataset show that our method achieves up to 15% higher ST-SIM and 47% lower RMSE than baselines, validating the effectiveness of our framework in achieving high semantic compression rates and accurate perceptual reconstruction for remote embodied intelligence applications.
{"title":"VT-FSC: Vision-Tactile Fusion Semantic Communication for Remote Embodied Intelligence","authors":"Rui Xu;Yuanhang He;Gaolei Li;Chaofeng Zhang;Jianhua Li","doi":"10.1109/LCOMM.2025.3642793","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3642793","url":null,"abstract":"Remote embodied intelligence relies on the seamless transmission of rich multi-modal sensory information, particularly vision and touch, to enable intelligent agents to collaboratively perceive, interact with, and manipulate physical environments. However, transmitting such high-dimensional and heterogeneous data over wireless channels in real time poses substantial challenges in terms of bandwidth, latency, and semantic integrity. In this letter, we propose a novel vision-tactile fusion semantic communication (VT-FSC) framework tailored for remote embodied intelligence applications. By leveraging cross-modal feature fusion and attention-guided semantic compression, the proposed system transforms raw visual and tactile data into a unified low-dimensional semantic representation. This compact representation is then robustly transmitted through noisy wireless channels and decoded at the receiver to reconstruct both the visual scene and the tactile signal accurately. To ensure perceptual alignment, encoder and decoder are jointly optimized via human-in-the-loop feedback mechanisms. Experimental results in the multi-model dataset show that our method achieves up to 15% higher ST-SIM and 47% lower RMSE than baselines, validating the effectiveness of our framework in achieving high semantic compression rates and accurate perceptual reconstruction for remote embodied intelligence applications.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"30 ","pages":"582-586"},"PeriodicalIF":4.4,"publicationDate":"2025-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145830898","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}
Indoor WIFI localization often suffers from severe signal fluctuations and interference, limiting accuracy and stability in dynamic environments. This letter introduces a dual-model fusion framework that combines Gaussian Process Regression (GPR) and the Log-Distance Path Loss (LDPL) model to construct high-fidelity WiFi fingerprint maps and predict signals in unobserved regions. Building on these maps, we further propose a Bayesian multi-fingerprint localization algorithm that fuses three complementary fingerprints—Received Signal Strength (RSS), Signal Strength Difference (SSD), and Hyperbolic Location Fingerprint (HLF)—to enhance robustness to temporal and spatial variations. Comprehensive experiments in a large multi-floor environment show that our method reduces mean RSS prediction error to 3.09 dBm and achieves up to 20 % lower localization RMSE than state-of-the-art methods, demonstrating superior resilience to environmental dynamics.
{"title":"A Robust WIFI Localization Method for Indoor Dynamic Scenes","authors":"Jian Sun;Wei Sun;Genwei Zhang;Chenjun Tang;Song Li;Xing Zhang","doi":"10.1109/LCOMM.2025.3641829","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3641829","url":null,"abstract":"Indoor WIFI localization often suffers from severe signal fluctuations and interference, limiting accuracy and stability in dynamic environments. This letter introduces a dual-model fusion framework that combines Gaussian Process Regression (GPR) and the Log-Distance Path Loss (LDPL) model to construct high-fidelity WiFi fingerprint maps and predict signals in unobserved regions. Building on these maps, we further propose a Bayesian multi-fingerprint localization algorithm that fuses three complementary fingerprints—Received Signal Strength (RSS), Signal Strength Difference (SSD), and Hyperbolic Location Fingerprint (HLF)—to enhance robustness to temporal and spatial variations. Comprehensive experiments in a large multi-floor environment show that our method reduces mean RSS prediction error to 3.09 dBm and achieves up to 20 % lower localization RMSE than state-of-the-art methods, demonstrating superior resilience to environmental dynamics.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"30 ","pages":"537-541"},"PeriodicalIF":4.4,"publicationDate":"2025-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145830877","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 : 2025-12-04DOI: 10.1109/LCOMM.2025.3640237
Yunfei Chen
This letter studies the effect of near field (NF) propagation on the detection of space shift keying signals when the mobile user either operates in the NF all the time or moves from the far field (FF) to the NF during operation. The performances of the maximum likelihood detectors in the NF, FF and mismatched cases are compared and also analyzed using the union bounds. Numerical results show that the NF case slightly outperforms the FF case due to the extra difference in the large-scale fading and that the mismatched case suffers from significant performance loss due to the change of propagation environment. This performance loss increases when the number of transmitting antennas, the number of receiving antennas or the signal-to-noise ratio increase. More importantly, the user location has a large impact in the mismatched case.
{"title":"Detection and Performance Analysis of Near-Field Space Shift Keying","authors":"Yunfei Chen","doi":"10.1109/LCOMM.2025.3640237","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3640237","url":null,"abstract":"This letter studies the effect of near field (NF) propagation on the detection of space shift keying signals when the mobile user either operates in the NF all the time or moves from the far field (FF) to the NF during operation. The performances of the maximum likelihood detectors in the NF, FF and mismatched cases are compared and also analyzed using the union bounds. Numerical results show that the NF case slightly outperforms the FF case due to the extra difference in the large-scale fading and that the mismatched case suffers from significant performance loss due to the change of propagation environment. This performance loss increases when the number of transmitting antennas, the number of receiving antennas or the signal-to-noise ratio increase. More importantly, the user location has a large impact in the mismatched case.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"30 ","pages":"522-526"},"PeriodicalIF":4.4,"publicationDate":"2025-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145778228","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 : 2025-12-04DOI: 10.1109/LCOMM.2025.3640402
Kaijing Yang;Qiao Xiao;Chaofeng Wang
This study addresses transmission scheduling in underwater acoustic (UWA) networks by optimizing transmission schedule and power allocation according to time availability and channel variations. The objective is to maximize network energy efficiency (EE) while minimizing transmission latency (TL). To capture transmission and interference relationships among links, a spatial-temporal (ST) graph is designed to represent the system state. Transmission scheduling is then formulated as a sequential decision-making process (SDP), where the optimal strategy is adaptively determined based on the graph-based system representation. Network performance is optimized using graph reinforcement learning (GRL), specifically through a graph policy gradient (GPG) approach. Simulation results demonstrate that the proposed method achieves higher EE and lower TL compared to benchmark methods.
{"title":"Graph Reinforcement Learning-Based Transmission Scheduling for Underwater Acoustic Networks","authors":"Kaijing Yang;Qiao Xiao;Chaofeng Wang","doi":"10.1109/LCOMM.2025.3640402","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3640402","url":null,"abstract":"This study addresses transmission scheduling in underwater acoustic (UWA) networks by optimizing transmission schedule and power allocation according to time availability and channel variations. The objective is to maximize network energy efficiency (EE) while minimizing transmission latency (TL). To capture transmission and interference relationships among links, a spatial-temporal (ST) graph is designed to represent the system state. Transmission scheduling is then formulated as a sequential decision-making process (SDP), where the optimal strategy is adaptively determined based on the graph-based system representation. Network performance is optimized using graph reinforcement learning (GRL), specifically through a graph policy gradient (GPG) approach. Simulation results demonstrate that the proposed method achieves higher EE and lower TL compared to benchmark methods.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"30 ","pages":"497-501"},"PeriodicalIF":4.4,"publicationDate":"2025-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145778229","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 : 2025-12-03DOI: 10.1109/LCOMM.2025.3639928
Leandro R. Ximenes;Igor S. C. Rodrigues;Miguel S. Pinheiro
This letter presents a unified framework to achieve space-time-color coding for screen-to-camera (S2C) communication. The novel approach integrates color-shift keying (CSK) modulation, tensor-based S2C modeling, and the visible light communications (VLC) scheme called color-hopping space-time (CHST) scheme to enable high-order, flicker-free video transmission. We further propose the alternating optimization for Khatri-Rao factorization (AO-KRF) algorithm for efficient symbol detection, achieving fast convergence and low complexity. Simulation and experimental results, including real video and real screen–smartphone setups under ambient light, confirm that AO-KRF attains good performance while reducing computational cost, making the framework suitable for real-time and realistic S2C communication scenarios.
{"title":"Space-Time-Color Scheme for Screen-to-Camera Communications","authors":"Leandro R. Ximenes;Igor S. C. Rodrigues;Miguel S. Pinheiro","doi":"10.1109/LCOMM.2025.3639928","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3639928","url":null,"abstract":"This letter presents a unified framework to achieve space-time-color coding for screen-to-camera (S2C) communication. The novel approach integrates color-shift keying (CSK) modulation, tensor-based S2C modeling, and the visible light communications (VLC) scheme called color-hopping space-time (CHST) scheme to enable high-order, flicker-free video transmission. We further propose the alternating optimization for Khatri-Rao factorization (AO-KRF) algorithm for efficient symbol detection, achieving fast convergence and low complexity. Simulation and experimental results, including real video and real screen–smartphone setups under ambient light, confirm that AO-KRF attains good performance while reducing computational cost, making the framework suitable for real-time and realistic S2C communication scenarios.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"30 ","pages":"507-511"},"PeriodicalIF":4.4,"publicationDate":"2025-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11275689","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145778259","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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