57 citations · 163 across the 45 of their papers we have counts for
24 papers · 1 filter
Green Federated Learning Over Cloud-RAN with Limited Fronthual Capacity and Quantized Neural Networks
Jiali Wang, Yijie Mao, Ting Wang +1
In this paper, we propose an energy-efficient federated learning (FL) framework for the energy-constrained devices over cloud radio access network (Cloud-RAN), where each device ad…
Features Disentangled Semantic Broadcast Communication Networks
Shuai Ma, Weining Qiao, Youlong Wu +6
Single-user semantic communications have attracted extensive research recently, but multi-user semantic broadcast communication (BC) is still in its infancy. In this paper, we prop…
Task-oriented Explainable Semantic Communications
Shuai Ma, Weining Qiao, Youlong Wu +6
Semantic communications utilize the transceiver computing resources to alleviate scarce transmission resources, such as bandwidth and energy. Although the conventional deep learnin…
Federated Learning via Unmanned Aerial Vehicle
Min Fu, Yuanming Shi, Yong Zhou
To enable communication-efficient federated learning (FL), this paper studies an unmanned aerial vehicle (UAV)-enabled FL system, where the UAV coordinates distributed ground devic…
Differentially Private Federated Learning via Reconfigurable Intelligent Surface
Yuhan Yang, Yong Zhou, Youlong Wu +1
Federated learning (FL), as a disruptive machine learning paradigm, enables the collaborative training of a global model over decentralized local datasets without sharing them. It…
Wireless Federated Learning over MIMO Networks: Joint Device Scheduling and Beamforming Design
Shaoming Huang, Pengfei Zhang, Yijie Mao +2
Federated learning (FL) is recognized as a key enabling technology to support distributed artificial intelligence (AI) services in future 6G. By supporting decentralized data train…