Massive MIMO joint precoding algorithm based on SORMI and Chebyshev iteration

Abstract

In the massive MIMO system, due to the huge orders of magnitude of users and base station antennas, the complexity of large-scale matrix inversion is relatively high. How to solve the matrix inversion problem has always been a hot spot in precoding research. In order to solve the problem that the Successive-over relaxation (SOR) iteration cannot directly obtain the inverse of the matrix in the massive MIMO system, and the iteration speed is slow, based on SORMI and Chebyshev iteration, we propose a joint precoding algorithm to speed up iteration and obtain better bit error rate performance. It can be seen from the simulation results that, compared with the RZF-SOR and SORMI algorithms, the joint algorithm has a faster convergence rate, and can obtain better bit error rate performance and matrix inversion accuracy with fewer iterations.