IEEE Communications Letters最新文献_第4页

Two-Path Serial Inter-Symbol-Interference Cancellation for Air-to-Ground Communication 空对地通信的双路串行符号间干扰消除

IF 3.7 3区计算机科学

IEEE Communications Letters Pub Date : 2024-11-19 DOI: 10.1109/LCOMM.2024.3502152

Zonglong Chen;Songkang Huang;Ming Jiang

引用次数: 0

Optimizing Multi-User Semantic Communication via Transfer Learning and Knowledge Distillation 基于迁移学习和知识蒸馏的多用户语义通信优化

IF 3.7 3区计算机科学

IEEE Communications Letters Pub Date : 2024-11-18 DOI: 10.1109/LCOMM.2024.3499956

Loc X. Nguyen;Kitae Kim;Ye Lin Tun;Sheikh Salman Hassan;Yan Kyaw Tun;Zhu Han;Choong Seon Hong

引用次数: 0

Dynamic Offloading in Mobile Edge Computing With Traffic-Aware Network Slicing and Adaptive TD3 Strategy 基于流量感知网络切片和自适应TD3策略的移动边缘计算动态卸载

IF 3.7 3区计算机科学

IEEE Communications Letters Pub Date : 2024-11-18 DOI: 10.1109/LCOMM.2024.3501956

Amin Mohajer;Javad Hajipour;Victor C. M. Leung

引用次数: 0

Diffusion Model Based Resource Allocation Strategy in Ultra-Reliable Wireless Networked Control Systems 基于扩散模型的超可靠无线网络控制系统资源分配策略

IF 3.7 3区计算机科学

IEEE Communications Letters Pub Date : 2024-11-15 DOI: 10.1109/LCOMM.2024.3499745

Amirhassan Babazadeh Darabi;Sinem Coleri

{"title":"Diffusion Model Based Resource Allocation Strategy in Ultra-Reliable Wireless Networked Control Systems","authors":"Amirhassan Babazadeh Darabi;Sinem Coleri","doi":"10.1109/LCOMM.2024.3499745","DOIUrl":"https://doi.org/10.1109/LCOMM.2024.3499745","url":null,"abstract":"Diffusion models offer a promising alternative to Deep Reinforcement Learning (DRL) for resource allocation in wireless networks due to their capability to model complex data distributions with greater accuracy, yet their potential remains largely unexplored. This letter proposes a diffusion model-based approach for Wireless Networked Control Systems (WNCSs) to minimize power consumption by optimizing the sampling period, blocklength, and packet error probability within the finite blocklength regime. The problem is simplified to optimizing blocklength through optimality conditions, and a dataset of channel gains and optimal blocklengths is generated via an optimization theory-based solution. The Denoising Diffusion Probabilistic Model (DDPM) is employed to generate optimal blocklength values, conditioned on channel state information (CSI). The core idea is to train the diffusion model to generate blocklength values from noise, essentially replicating the process by which the optimization solution is derived. Extensive simulations reveal that the proposed approach surpasses existing DRL-based methods, achieving near-optimal performance in terms of total power consumption. Additionally, the proposed method reduces critical constraint violations by up to eighteen times, further highlighting the enhanced accuracy of the solution.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"29 1","pages":"85-89"},"PeriodicalIF":3.7,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142940870","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}

引用次数: 0

IEEE Communications Letters Publication Information IEEE Communications Letters 出版信息

IF 3.7 3区计算机科学

IEEE Communications Letters Pub Date : 2024-11-12 DOI: 10.1109/LCOMM.2024.3484891

引用次数: 0

Joint Edge Computing and Semantic Communication in UAV-Enabled Networks 无人机支持网络中的联合边缘计算和语义通信

IF 3.7 3区计算机科学

IEEE Communications Letters Pub Date : 2024-11-12 DOI: 10.1109/LCOMM.2024.3496534

Nguyen Tien Hoa;Can Thi Thanh Hai;Hoang Le Hung;Nguyen Cong Luong;Dusit Niyato

{"title":"Joint Edge Computing and Semantic Communication in UAV-Enabled Networks","authors":"Nguyen Tien Hoa;Can Thi Thanh Hai;Hoang Le Hung;Nguyen Cong Luong;Dusit Niyato","doi":"10.1109/LCOMM.2024.3496534","DOIUrl":"https://doi.org/10.1109/LCOMM.2024.3496534","url":null,"abstract":"In this letter, we investigate a joint edge computing and semantic communication in the UAV-enabled network. Therein, a UAV executes tasks offloaded from ground user equipments (UEs). Meanwhile, it acts as an IoT device to provide image data to a Metaverse platform through a ground base station (BS). A semantic communication (SemCom) technique is implemented at the UAV to extract scene graphs from captured images. The UAV then transmits the scene graphs (rather than the orignal images) to the BS. The small size of the scene graphs allows the UAV to transmit multiple images to the BS within a short duration. However, the scene graph extraction consumes computing resource, which may reduce the performance of the task offloading of the UEs. Therefore, we aim to optimize the UAV’s computing resource allocation and the fractions of the tasks offloaded from the UEs to achieve the min-max between i) the total latency of image collection, scene graph extraction, and scene graph communication, and ii) the computation offloading latency over the ground UEs. Given the dynamics and uncertainty of the wireless channels, the distances between the UAV and UEs, and the computing resources of the UEs, we leverage the Advantage Actor-Critic (A2C) and Proximal Policy Optimization (PPO) to solve it.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"29 1","pages":"80-84"},"PeriodicalIF":3.7,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142940941","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}

引用次数: 0

IEEE Communications Society Information IEEE 通信学会信息

IF 3.7 3区计算机科学

IEEE Communications Letters Pub Date : 2024-11-12 DOI: 10.1109/LCOMM.2024.3484889

引用次数: 0

Semi-Blind Channel Estimation for Massive MIMO LEO Satellite Communications 大规模MIMO LEO卫星通信的半盲信道估计

IF 3.7 3区计算机科学

IEEE Communications Letters Pub Date : 2024-11-11 DOI: 10.1109/LCOMM.2024.3495998

Abdollah Masoud Darya;Saeed Abdallah

引用次数: 0

Enhancing Fairness-Aware Massive Wireless Powered IoT Connectivity by IRS 通过IRS增强公平意识的大规模无线供电物联网连接

IF 3.7 3区计算机科学

IEEE Communications Letters Pub Date : 2024-11-08 DOI: 10.1109/LCOMM.2024.3494030

Yi Wang;Junlei Zhi;Shaochuan Yang;Zheng Chu;Baofeng Ji;Hui Guo;Meng Hua;Chunguo Li

{"title":"Enhancing Fairness-Aware Massive Wireless Powered IoT Connectivity by IRS","authors":"Yi Wang;Junlei Zhi;Shaochuan Yang;Zheng Chu;Baofeng Ji;Hui Guo;Meng Hua;Chunguo Li","doi":"10.1109/LCOMM.2024.3494030","DOIUrl":"https://doi.org/10.1109/LCOMM.2024.3494030","url":null,"abstract":"This letter explores an intelligent reflecting surface (IRS) enhanced wireless powered Internet of Things (WP-IoT) network, wherein massive IoT nodes are wirelessly charged by radio frequency signals and then transmit information by means of an IRS to promote the system performance. To evaluate the network performance, we aim at maximizing the total throughput while adhering to constraints pertaining to fairness-aware individual signal-to-noise ratio (SNR), the time allocations (TAs) as well as the unit-modulus IRS phase shifts. However, the intricate coupling of these variables renders the optimization problem nonconvex, thus posing a challenge for direct solution. To deal with this dilemma, we first resort to employing the Lagrange dual method and Karush-Kuhn–Tucker (KKT) conditions to transform the sum of logarithmic objective function into sum of fractional counterpart, and further derive the analytical solutions of TAs for downlink wireless energy transfer (WET) and uplink wireless information transfer (WIT). Then, the Riemannian manifold optimization (RMO) is utilized to iteratively derive the IRS phase shifts in term of semi-closed-form expression. Lastly, numerical simulations are conducted to examine the efficacy of the proposed algorithm in enhancing performance in comparison to the existing benchmark schemes.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"29 1","pages":"65-69"},"PeriodicalIF":3.7,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142940913","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}

引用次数: 0

A Multi-Agent DRL Method for Distributed Energy-Efficient Association and Hybrid Precoding in mmWave Cell-Free Massive MIMO Systems 毫米波无小区大规模MIMO系统中分布式节能关联和混合预编码的多智能体DRL方法

IF 3.7 3区计算机科学

IEEE Communications Letters Pub Date : 2024-11-08 DOI: 10.1109/LCOMM.2024.3494537

Huiting Li;Yanxiang Jiang;Yige Huang;Fu-Chun Zheng;Gang Wu

引用次数: 0