关键词: 联邦学习, 混合波束赋形, 智能反射面

Abstract:

A convolutional neural network training algorithm based on federated learning is proposed for the hybrid beamforming for intelligent reflecting surface assisted communication in millimeter wave massive multiple input multiple output system. In multi-user communication system, the analog beamforming matrix and intelligent reflection matrix with the maximum sum rate are researched by exhaustive search algorithm, which is set codebooks are designed, and the exhaustive search algorithm is used to search the analog beamforming matrix and intelligent reflection matrix with the maximum sum rate are researched by exhaustive search algorithm, which is set as the training data label. Then, based on the federated learning framework, the convolutional neural network is used for local training to map channel matrix to analog beamforming and intelligent reflection matrixes. The simulation results verity the feasibility of convolutional neural network training based on federated learning. Meanwhile, by comparing the communication scene with or without or randomly intelligent reflection matrix, the proposed algorithm.

Key words:

federated learning;hybrid beamforming, intelligent reflecting surface