Intelligent Reflecting Surface-Assisted Low-Latency Federated Learning Over Wireless Networks

Author:

Mao Sun1ORCID,Liu Lei2ORCID,Zhang Ning3ORCID,Hu Jie4ORCID,Yang Kun4ORCID,Yu F. Richard5ORCID,Leung Victor C. M.6ORCID

Affiliation:

1. College of Computer Science, Sichuan Normal University, Chengdu, China

2. State Key Laboratory of Integrated Service Networks, Xidian University, Xi’an, China

3. Department of Electrical and Computer Engineering, University of Windsor, Windsor, Canada

4. School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China

5. Department of Systems and Computer Engineering, Carleton University, Ottawa, Canada

6. College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China

Funder

Natural Science Foundation of China

Natural Science Foundation of Sichuan Province

Sichuan Science and Technology Program

Sichuan Major Research and Development Project

Basic and Applied Basic Research Foundation of Guangdong Province

China Postdoctoral Science Foundation

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Signal Processing

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3. Reconfigurable Intelligent Surface-Assisted Multisatellite Cooperative Downlink Beamforming;IEEE Internet of Things Journal;2024-07-01

4. Delay Minimization for NOMA-Assisted Federated Learning;2024 IEEE Wireless Communications and Networking Conference (WCNC);2024-04-21

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