5 papers
Wireless Decentralized Federated Learning via Device Clustering and Inter-Cluster Link Enhancement
William Weijia Zheng, Hang Liu, Ying-Jun Angela Zhang
Decentralized federated learning (DFL) dispenses with the central server of classical FL by utilizing peer-to-peer model exchanges among edge devices. This server-free architecture…
Toward Reliable Semantic Communication: Beyond Average Performance
Boyuan Li, Mingze Gong, Shuoyao Wang +3
Semantic communication has emerged as a promising paradigm for improving transmission efficiency by conveying task-relevant semantics rather than raw data. Although recent studies…
Enabling Safety-Critical Wireless Communications via Safe Reinforcement Learning
Haoran Peng, Tong Wu, Hang Liu +3
Ensuring strict safety guarantees is the paramount challenge for emerging 5G/6G wireless systems, particularly as they increasingly govern mission-critical applications ranging fro…
Communication-Learning Co-Design for Differentially Private Over-the-Air Federated Distillation
Zihao Hu, Jia Yan, Ying-Jun Angela Zhang
The ever-growing learning model size nowadays challenges the communication efficiency and privacy preservation of the traditional federated learning (FL). In this paper, we propose…
Optimal Transceiver Design in Over-the-Air Federated Distillation
Zihao Hu, Jia Yan, Ying-Jun Angela Zhang +2
The rapid proliferation and growth of artificial intelligence (AI) has led to the development of federated learning (FL). FL allows wireless devices (WDs) to cooperatively learn by…