基于AI通信的大规模MIMO信道状态信息反馈网络OACSTPCD

In a massive multiple-input multiple-output(MIMO)system,the increase of the number of antennas leads to the increase of the channel state information(CSI)feedback bandwidth overhead.To reduce the feedback overhead,a feedback network based on deep learning(DL)is proposed.The network combines a convolutional attention module with a Fast Iterative Shrinkage Thresholding Algorithm(FISTA).In order to fit the practical application,the noise situation is considered and the threshold sensitivity is analyzed.The simulation results show that the performance and robustness of the network can be further improved in different environments.