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RIS-Assisted Over-the-Air Federated Learning in Millimeter Wave MIMO Networks

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Hu Lin 1,2,3   Wang Zhibin 1,2,3   Zhu Hongbin 1   Zhou Yong 1 *  
文摘 In this paper, we propose a reconfigurable intelligent surface(RIS) assisted over-the-air federated learning(FL), where multiple antennas are deployed at each edge device to enable simultaneous multidimensional model transmission over a millimeter wave(mmWave) network. We conduct rigorous convergence analysis for the proposed FL system, taking into account dynamic channel fading and analog transmissions. Inspired by the convergence analysis, we propose to jointly optimize the receive digital and analog beamforming matrices at the access point, the RIS phase-shift matrix, as well as the transmit beamforming matrices at transmitting devices to minimize the transmission distortion. The optimization variable coupling and non-convex constraints make the formulated problem challenging to be solved. To this end, we develop a low-complexity Riemannian conjugate gradient(RCG)-based algorithm to solve the unit modulus constraints and decouple the optimization variables. Simulations show that the proposed RCG algorithm outperforms the successive convex approximation algorithm in terms of the learning performance.
来源 Journal of Communications and Information Networks ,2022,7(2):145-156 【核心库】
DOI 10.23919/JCIN.2022.9815198
关键词 reconfigurable intelligent surface ; federated learning ; Riemannian conjugate gradient ; over-the-air computation
地址

1. School of Information Science and Technology, ShanghaiTech University, Shanghai, 201210  

2. Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, 200050  

3. University of Chinese Academy of Sciences, Beijing, 100049

语种 英文
文献类型 研究性论文
ISSN 2096-1081
学科 电子技术、通信技术
基金 at the IEEE Vehicular Technology Conference,Helsinki, Finland, Jun. 2022[1] ;  supported by the National Natural Science Foundation of China(NSFC)
文献收藏号 CSCD:7317943

参考文献 共 38 共2页

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引证文献 1 篇

1 Wang Jiaping Secrecy Rate Analysis for RIS-Aided Multi-User MISO System over Rician Fading Channel Journal of Communications and Information Networks,2023,8(1):48-56
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