Low Complexity WSSOR-based Linear Precoding for Massive MIMO Systems

For Massive MIMO system with hundreds of antennas at the base station and serve a lot of users, regularized zero forcing (RZF) precoding can achieve the high performance, but suffer from high complexity due to the required matrix inversion of large size. To solve this question, we propose a precoding based on weighted symmetric successive over relaxation (WSSOR) method to approximate the matrix inversion. The proposed method can reduce the computational complexity by about one order of magnitude and it can approach the RZF precoding. Besides we propose a simple way to choose the optional relaxation parameter in massive MIMO systems. And we choose weighting factor is only related to the system configuration parameters. Simulation results prove that the proposed WSSOR-based precoding can approach the near-optional performance of RZF precoding with small number of iterations.