Intelligent CSI feedback method for fast time-varying FDD massive MIMO system - Yong LIAO; Shuai WANG; Ning SUN (Tongxin xuebao)
In the frequency division duplexing (FDD) massive multiple-input multiple-output (MIMO) system, the channel state information (CSI) matrix existed noise caused by the wireless channel interference and the time correlation caused by Doppler shift.Because of these effects, the communication system couldn’t guarantee the requirements of reliability and low delay.An intelligent CSI feedback method was adopted.The convolutional neural network (CNN) and batch normalization (BN) network was used to extract the noise in the CSI matrix and learned the spatial structure of the channel.The time correlation between the CSI matrices through the attention mechanism was extracted to improve the accuracy of CSI reconstruction.The data was generated by the standard fast time-varying channel model simulation to train the network offline.System simulation and analysis show that the proposed method can effectively suppress the influence of noise and extract the time correlation caused by Doppler.Compared with the traditional CSI compression feedback algorithm and CsiNet algorithm, the proposed method has better NMSE and cosine similarity performance.