Estimation of channel state information for massive MIMO based on received data using Kalman filter

Channel state information (CSI) estimation is one of the most important topics in massive MIMO which attracts many types of research. in We propose a new method to estimate the channel state information (CSI) based on the detected data and Kalman Filter and prior knowledge of the channel. We assume OFDM system with QPSK modulation. The detected OFDM symbol is processed by a modified Kalman filter to produce channel state information (CSI). This method is less dependent on channel statistics as compared to minimum mean square error CSI estimation. It utilizes the dynamic channel properties and time correlation between successive coherence channel blocks to estimate the channel such that no need to transmit pilot carriers each coherence time. The received data is used by Kalman filter to estimate the channel with low mean square error otherwise, a training sequence phase should be initiated. The results show that the proposed method can be used without loss in achievable rate.