基于深度学习的CSI压缩反馈方案研究

In this paper, we propose a channel status information (CSI) compression feedback network named MLP-Transformer. Starting from the shortcomings of existing algorithms, based on the lightweight design criteria of encoder module and the application of Transformer self-attention mechanism, this scheme realizes a network model of CSI high-precision recovery. The simulation results show that the CSI compression feedback scheme of deep self encoder based on MLP- Transformer has high CSI reconstruction accuracy under different compression ratios of Frequency Division Duplex (FDD) downlink massive Multiple Input Multiple Output (MIMO) system scenarios, and the lightweight design of its encoder module has lower encoder complexity than other schemes.