Mobile Reconfigurable Intelligent Surfaces for NOMA Networks: Federated Learning Approaches-Reference-Cited by-同舟云学术

Mobile Reconfigurable Intelligent Surfaces for NOMA Networks: Federated Learning Approaches

Published:2022-11 Issue:11 Volume:21 Page:10020-10034
ISSN:1536-1276
Container-title:IEEE Transactions on Wireless Communications
language:
Short-container-title:IEEE Trans. Wireless Commun.

Author:

Zhong Ruikang¹^ORCID,Liu Xiao¹^ORCID,Liu Yuanwei¹^ORCID,Chen Yue¹,Han Zhu²^ORCID

Affiliation:

1. School of Electronic Engineering and Computer Science (EECS), Queen Mary University of London, London, U.K.

2. Department of Electrical and Computer Engineering, University of Houston, Houston, TX, USA

Funder

NSF

China Scholarship Council

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Electrical and Electronic Engineering,Computer Science Applications

Link

http://xplorestaging.ieee.org/ielx7/7693/9944944/09798759.pdf?arnumber=9798759

Reference58 articles.

1. Energy Efficient Federated Learning Over Wireless Communication Networks

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3. Joint trajectory and passive beamforming design for intelligent reflecting surface-aided UAV communications: A deep reinforcement learning approach;wang;arXiv 2007 08380,2020

4. Intelligent Reflecting Surface Assisted Anti-Jamming Communications: A Fast Reinforcement Learning Approach

5. Federated learning for channel estimation in conventional and RIS-assisted massive MIMO;elbir;IEEE Trans Wireless Commun,2021

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