8 citations · 21 across the 7 of their papers we have counts for
7 papers
Data Heterogeneity-Aware Client Selection for Federated Learning in Wireless Networks
Yanbing Yang, Huiling Zhu, Wenchi Cheng +3
Federated Learning (FL) enables mobile edge devices, functioning as clients, to collaboratively train a decentralized model while ensuring local data privacy. However, the efficien…
Anti-Byzantine Attacks Enabled Vehicle Selection for Asynchronous Federated Learning in Vehicular Edge Computing
Cui Zhang, Xiao Xu, Qiong Wu +4
In vehicle edge computing (VEC), asynchronous federated learning (AFL) is used, where the edge receives a local model and updates the global model, effectively reducing the global…
Spectral Efficiency Maximization for Active RIS-aided Cell-Free Massive MIMO Systems with Imperfect CSI
Mahdi Eskandari, Huiling Zhu, Jiangzhou Wang
A cell-free network merged with active reconfigurable reflecting surfaces (RIS) is investigated in this paper. Based on the imperfect channel state information (CSI), the aggregate…
Vehicle Selection for C-V2X Mode 4 Based Federated Edge Learning Systems
Qiong Wu, Xiaobo Wang, Pingyi Fan +3
Federated learning (FL) is a promising technology for vehicular networks to protect vehicles' privacy in Internet of Vehicles (IoV). Vehicles with limited computation capacity may…
RIS-Aided Near-Field Localization and Channel Estimation for the Sub-Terahertz System
Yijin Pan, Cunhua Pan, Shi Jin +1
The low hardware cost makes ultra-large (XL) reconfigurable intelligent surface (RIS) an attractive solution for the performance enhancement of localization and communication syste…
Bandit Inspired Beam Searching Scheme for mmWave High-Speed Train Communications
Jun-Bo Wang, Ming Cheng, Jin-Yuan Wang +4
High-speed trains (HSTs) are being widely deployed around the world. To meet the high-rate data transmission requirements on HSTs, millimeter wave (mmWave) HST communications have…
A Machine Learning Framework for Resource Allocation Assisted by Cloud Computing
Jun-Bo Wang, Junyuan Wang, Yongpeng Wu +4
Conventionally, the resource allocation is formulated as an optimization problem and solved online with instantaneous scenario information. Since most resource allocation problems…