A Low Complexity Channel Estimation Algorithm For Massive Mimo System

An improved minimum mean square error (MMSE) channel method with low complexity is proposed for the massive multiple input multiple output (MIMO) system. In the method, the covariance matrix in the MMSE method is firstly approximately estimated by the received signal, where the optimal approximated weight is given, and then the Sherman-Morrison theorem is employed to transform the matrix inversion into the product of the matrix and vector. The simulation results show that the proposed method can greatly reduce the computational complexity of the MMSE method and only has a little performance loss. Moreover, compared with the available methods, the proposed method has a better performance and lower complexity.