IEEE Transactions on Communications最新文献_第6页

Sparse-Mask Harmonic Union-GLRT for Hovering UAV Detection in TDD-ISAC Systems TDD-ISAC系统中悬停无人机的稀疏掩模谐波联合glrt检测

IF 8.3 2区计算机科学

IEEE Transactions on Communications Pub Date : 2026-09-16 DOI: 10.1109/tcomm.2026.3734320

Jiachen Wei, Dingyou Ma, Haotian Liu, Qixun Zhang, Kan Yu, Zongqi Mo, Zheng Jiang, Xingwang Li, Zhiyong Feng

引用次数: 0

SOLOS: Soft-Output List Ordered Statistics Decoding for Product Codes SOLOS：产品代码的软输出列表有序统计解码

IF 8.3 2区计算机科学

IEEE Transactions on Communications Pub Date : 2026-09-03 DOI: 10.1109/tcomm.2026.3720337

Zongyao Li, Yifei Shen, Huayi Zhou, Jian Zheng, Xiaosi Tan, Ming Jiang, Yongming Huang, Xiaohu You, Chuan Zhang

引用次数: 0

Integrating Probabilistic Shaping into Entropy Coding: A Recursive Node Partitioning Huffman Coding Approach 将概率整形整合到熵编码中：递归节点划分霍夫曼编码方法

IF 8.3 2区计算机科学

IEEE Transactions on Communications Pub Date : 2026-08-18 DOI: 10.1109/tcomm.2026.3725119

Yanan Luo, Jiamin Li, Qun Chen, Shufeng Li

引用次数: 0

Holographic Surface Enabled Integrated Sensing and Communications 全息表面集成传感和通信

IF 8.3 2区计算机科学

IEEE Transactions on Communications Pub Date : 2026-07-27 DOI: 10.1109/tcomm.2026.3717011

Haobo Zhang, Shuhao Zeng, Xinyuan Hu, Shupei Zhang, Boya Di, Hongliang Zhang, Lianlin Li, Lin Chang, Wei Xiang Jiang, Shaohui Sun, Zhu Han, Yonina C. Eldar, Rui Zhang, Merouane Debbah, Lingyang Song

引用次数: 0

Joint Extremum Compression and Detection of a Time-Delayed Signal for Distributed Sensing 面向分布式传感的延时信号联合极值压缩与检测

IF 8.3 2区计算机科学

IEEE Transactions on Communications Pub Date : 2026-07-16 DOI: 10.1109/tcomm.2026.3714349

Amir Weiss

引用次数: 0

Start-of-Packet Detection Using Machine Learning 使用机器学习的数据包开始检测

IF 8.3 2区计算机科学

IEEE Transactions on Communications Pub Date : 2026-03-02 DOI: 10.1109/TCOMM.2026.3669492

Simrandeep Kaur;Arhum Ahmad;Satyam Agarwal

引用次数: 0

UAV-Based Jamming Detection for Large Language Model-Enabled Wireless Networks 基于无人机的大型语言模型无线网络干扰检测

IF 8.3 2区计算机科学

IEEE Transactions on Communications Pub Date : 2026-03-02 DOI: 10.1109/TCOMM.2026.3669447

Qiaoxin Chen;Liang Xiao;Pengcheng Wang;Jieling Li;Haoyu Chen;Hongbin Jin;Ying-Jun Angela Zhang

{"title":"UAV-Based Jamming Detection for Large Language Model-Enabled Wireless Networks","authors":"Qiaoxin Chen;Liang Xiao;Pengcheng Wang;Jieling Li;Haoyu Chen;Hongbin Jin;Ying-Jun Angela Zhang","doi":"10.1109/TCOMM.2026.3669447","DOIUrl":"10.1109/TCOMM.2026.3669447","url":null,"abstract":"Reinforcement learning (RL) has been used for uncrewed aerial vehicle (UAV)-based jamming detection by selecting hypothesis-test thresholds on received signal strength (RSS) to safeguard large language model (LLM) inference over wireless links. However, existing methods struggle against smart jammers with dynamic jamming probability. In this paper, we propose a UAV-based jamming detection scheme for LLM-enabled wireless networks to detect smart jamming. The proposed scheme augments traditional wireless features with an LLM-inferred communication environment indicator derived from multimodal sensing (e.g., images/videos from mobile devices), improving accuracy beyond RSS alone. Our approach jointly optimizes the test threshold and the UAV’s sniffer channel assignment, even with a limited number of antennas. We achieve this via a RL policy that leverages UAV imagery, e.g., suspicious radio devices and measuring relative distances, to accelerate detection speed. We implement the proposed scheme on a UAV equipped with a universal software radio peripheral to alert on jamming attacks in a wireless network integrated with a 7-billion-parameter vision-language multimodal LLM. Experiments with a UAV at 3 m detecting a smart jammer during image–text LLM inference across three mobile devices and an edge server demonstrate improvements in both detection accuracy and speed.","PeriodicalId":13041,"journal":{"name":"IEEE Transactions on Communications","volume":"74 ","pages":"5833-5848"},"PeriodicalIF":8.3,"publicationDate":"2026-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147350851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

PAPR Reduction in OFDM With Hybrid Beamforming—A Less Explored Problem 混合波束形成OFDM中PAPR的降低——一个研究较少的问题

IF 8.3 2区计算机科学

IEEE Transactions on Communications Pub Date : 2026-02-27 DOI: 10.1109/TCOMM.2026.3668157

Abdur Rahman Mohamed Ismail;Mamoun Guenach;André Bourdoux;Heidi Steendam

引用次数: 0

RIS-Based Beam Steering for Visible Light Communication: Channel Model and Optimization 基于ris的可见光通信光束控制：信道模型与优化

IF 8.3 2区计算机科学

IEEE Transactions on Communications Pub Date : 2026-02-26 DOI: 10.1109/TCOMM.2026.3668152

S. M. Matin Alemohammad;Mohammad Hadi;Mohammad Reza Pakravan

{"title":"RIS-Based Beam Steering for Visible Light Communication: Channel Model and Optimization","authors":"S. M. Matin Alemohammad;Mohammad Hadi;Mohammad Reza Pakravan","doi":"10.1109/TCOMM.2026.3668152","DOIUrl":"10.1109/TCOMM.2026.3668152","url":null,"abstract":"The performance of visible light communication (VLC), as a key technology for next-generation wireless communication networks, can be significantly enhanced in terms of data rate, delay, and fairness, through the integration of optical reconfigurable intelligent surfaces (RISs). This paper introduces a novel channel model for a VLC system incorporating RIS-equipped transmitters, where the RIS is directly integrated with the VLC transmitter. This new design is shown to effectively provide beam steering (BS), enabling the concentration of optical power at desired directions with a typical 9.2dB power gain compared to a scenario without BS capability. To further illustrate the BS capability of the modeled RIS-equipped transmitter, a traffic-aware resource allocation scheme is formulated and efficiently solved using a tailored fractional programming (FP) approach with an affordable computation complexity. This approach allows to jointly optimize user association and power control by decoupling the interference interactions caused by BS. Simulation results reveal that BS-capable VLC through the proposed channel model and optimization scheme, can enhance data rate and fairness considerably while keeping delay within acceptable levels.","PeriodicalId":13041,"journal":{"name":"IEEE Transactions on Communications","volume":"74 ","pages":"5546-5559"},"PeriodicalIF":8.3,"publicationDate":"2026-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147319638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

UAV-RHS-Enabled Full-Duplex ISAC Covert System: Robust Beamforming and Trajectory Optimization 支持无人机- rhs的全双工ISAC隐蔽系统：鲁棒波束形成和轨迹优化

IF 8.3 2区计算机科学

IEEE Transactions on Communications Pub Date : 2026-02-26 DOI: 10.1109/TCOMM.2026.3668166

Yu Yao;Wenqi Xiao;Pu Miao;Gaojie Chen;Haitao Yang;Chan-Byoung Chae;Kai-Kit Wong

{"title":"UAV-RHS-Enabled Full-Duplex ISAC Covert System: Robust Beamforming and Trajectory Optimization","authors":"Yu Yao;Wenqi Xiao;Pu Miao;Gaojie Chen;Haitao Yang;Chan-Byoung Chae;Kai-Kit Wong","doi":"10.1109/TCOMM.2026.3668166","DOIUrl":"10.1109/TCOMM.2026.3668166","url":null,"abstract":"This paper proposes a novel covert transmission framework for an uncrewed aerial vehicle (UAV)-reconfigurable holographic surface (RHS)-aided full-duplex (FD) integrated sensing and communication (ISAC) system, where the aerial access point (AP) simultaneously performs target sensing and downlink covert communication. We jointly design the AP’s downlink transmit signal and uplink receive beamformers, the RHS weights, the users’ uplink transmit powers, and the UAV’s trajectory, considering imperfect knowledge of the warden’s channel state information (CSI). An optimization problem is formulated to maximize the minimum covert transmission rate (CTR) among all downlink covert users (DCUs), subject to constraints on required sensing and uplink transmission capabilities, covertness, and total power budget. To tackle the intractable non-convex problem, we leverage the Bernstein-type inequality, majorization-minimization (MM), and successive convex approximation (SCA), and propose a secure optimization framework that efficiently updates all variables using convex optimization techniques. To further understand the proposed algorithm, its convergence behavior and computational complexity are discussed. Simulation results demonstrate that integrating RHS and UAV techniques into the optimization design enhances the covert transmission performance of FD-ISAC systems while ensuring a certain level of sensing capability.","PeriodicalId":13041,"journal":{"name":"IEEE Transactions on Communications","volume":"74 ","pages":"5637-5653"},"PeriodicalIF":8.3,"publicationDate":"2026-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147319628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0