IEEE Communications Letters最新文献_第7页

Optimizing Smart Helper Placement for Enhanced Cache Efficiency in F-RANs 优化智能助手放置以提高f - ran中的缓存效率

IF 4.4 3区计算机科学

IEEE Communications Letters Pub Date : 2025-06-13 DOI: 10.1109/LCOMM.2025.3579670

Hesameddin Mokhtarzadeh;Mohammed Saif;Md. Jahangir Hossain;Julian Cheng

引用次数: 0

Attitude-Based User Terminal Beam Pointing Using Downlink Data Bursts From Broadband Satellites 利用宽带卫星下行数据爆发的基于姿态的用户终端波束指向

IF 4.4 3区计算机科学

IEEE Communications Letters Pub Date : 2025-06-13 DOI: 10.1109/LCOMM.2025.3579717

Zilan Yu;Xi Chen;Liuguo Yin;Linling Kuang

{"title":"Attitude-Based User Terminal Beam Pointing Using Downlink Data Bursts From Broadband Satellites","authors":"Zilan Yu;Xi Chen;Liuguo Yin;Linling Kuang","doi":"10.1109/LCOMM.2025.3579717","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3579717","url":null,"abstract":"In satellite communications, beam pointing is fundamental for the user terminal to perform stable communications with passing satellites. The traditional energy-based user terminal beam pointing method tracks the energy of received signals, which requires the received signal to have a good enough signal-to-noise ratio (SNR) to search for the energy peak. In this work, an antenna attitude-based beam pointing method using downlink data bursts from broadband satellites is proposed. The proposed method consists of two stages: in the acquisition stage, the user terminal achieves rough beam alignment using a 9-axis inertial measurement unit (IMU) as the conventional method; and in the tracking stage, super-resolution time difference of arrival (TDOA) measurements are obtained from a phased array antenna with multiple subarrays by receiving data bursts from the passing satellite. The TDOA measurements are fused with the triaxial gyroscope and triaxial magnetometer outputs through the proposed factor graph optimization-based fine attitude estimation algorithm to achieve fine attitude estimation results, from which the optimal beam pointing direction is derived. The simulation results show that the proposed method achieves 0.2° beam pointing estimation precision when a 1 ms, 100 MHz 5G non-terrestrial network (NTN) downlink orthogonal frequency division multiplexing (OFDM) signal is available per second.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"29 8","pages":"1914-1918"},"PeriodicalIF":4.4,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144831880","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

Satellite-Based Emitter Geolocation Using Matched Location Processing 基于匹配定位处理的卫星发射器地理定位

IF 4.4 3区计算机科学

IEEE Communications Letters Pub Date : 2025-06-13 DOI: 10.1109/LCOMM.2025.3579652

Caiyong Hao;Xianrong Wan;Feng He;Jianxin Yi

引用次数: 0

New Constructions of Z-Complementary Code Sets Based on Generalized Column Orthogonal Matrices 基于广义列正交矩阵的z互补码集的新构造

IF 4.4 3区计算机科学

IEEE Communications Letters Pub Date : 2025-06-12 DOI: 10.1109/LCOMM.2025.3578954

Fanfei Meng;Kai Liu;Jiapeng Li;Xinyu Shao

引用次数: 0

Cross-Band Optical/RF Networks With Zero-Energy Devices 具有零能量器件的跨带光/射频网络

IF 4.4 3区计算机科学

IEEE Communications Letters Pub Date : 2025-06-11 DOI: 10.1109/LCOMM.2025.3578581

Apostolos A. Tegos;Sotiris A. Tegos;Panagiotis D. Diamantoulakis;George K. Karagiannidis

引用次数: 0

Optimal Power Augmentation of LEO-NA Satellites in Power Inversion Adaptive Arrays 功率反转自适应阵列中LEO-NA卫星的最优功率增强

IF 4.4 3区计算机科学

IEEE Communications Letters Pub Date : 2025-06-11 DOI: 10.1109/LCOMM.2025.3578854

Zhihao Xue;Zukun Lu;Xiaoyu Zhao;Wei Xiao;Chenglong Li;Shaojie Ni

引用次数: 0

IEEE Communications Letters Publication Information IEEE通讯通讯出版信息

IF 3.7 3区计算机科学

IEEE Communications Letters Pub Date : 2025-06-11 DOI: 10.1109/LCOMM.2025.3571325

引用次数: 0

RSMA-Enabled Integrated Sensing, Communication, and Computation for IoT: Joint Transceiver Beamforming and Power Allocation 支持rsma的物联网集成传感、通信和计算：联合收发器波束形成和功率分配

IF 4.4 3区计算机科学

IEEE Communications Letters Pub Date : 2025-06-10 DOI: 10.1109/LCOMM.2025.3578457

Xiaobo Liu;Ziming Zhao;Xinru Wang;Fei Du;Suiyan Geng;Zhenyu Zhou

引用次数: 0

The SINR Meta Distribution in UAV Swarm Networks With Distributed Election Multiple Access 分布式选举多址无人机群网络中SINR元分布

IF 4.4 3区计算机科学

IEEE Communications Letters Pub Date : 2025-06-10 DOI: 10.1109/LCOMM.2025.3578372

Yanan Liang;Xu Li;Mingqiang Yang;Fanyi Meng

引用次数: 0

Online Device Scheduling and Model Partition in Hybrid Asynchronous Split Federated Learning 混合异步分裂联邦学习中的在线设备调度与模型划分

IF 4.4 3区计算机科学

IEEE Communications Letters Pub Date : 2025-06-09 DOI: 10.1109/LCOMM.2025.3577786

Shunfeng Chu;Yiyang Ni;Jun Li;Kang Wei;Jianxin Wang

{"title":"Online Device Scheduling and Model Partition in Hybrid Asynchronous Split Federated Learning","authors":"Shunfeng Chu;Yiyang Ni;Jun Li;Kang Wei;Jianxin Wang","doi":"10.1109/LCOMM.2025.3577786","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3577786","url":null,"abstract":"Federated Learning (FL) has attracted significant attention for its capability to collaboratively train neural network (NN) models across multiple data owners while protecting data privacy. However, FL over wireless networks faces two critical challenges, i.e., constrained resources on the device side and stringent synchronous updates across devices. This letter proposes a Hybrid Asynchronous Split FL (HASFL) framework, which combines the strengths of asynchronous FL and split FL, allowing devices to update the model asynchronously and offload partial training tasks to the server. To further enhance the efficiency of HASFL, we formulate a multi-objective optimization problem with long-term constraints aiming at minimizing latency and energy consumption while maintaining the training performance. Furthermore, we propose a novel online scheduling scheme based on the Linear Upper Confidence Bound (EDC-LinUCB) algorithm, which adaptively selects devices and determines the optimal partition layer of the NN model for training in dynamic environments, with theoretical performance validated by a regret analysis. Numerical simulations demonstrate the effectiveness and superiority of the proposed algorithm.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"29 8","pages":"1869-1873"},"PeriodicalIF":4.4,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144831879","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