Conjugate Gradient Method Based Linear Precoding with Low-Complexity for Massive MIMO Systems

In massive multiple-input multiple-output (MIMO) systems, when the number of base station (BS) antennas is tremendous, regularized zero-forcing (RZF) precoding can achieve the near-optimal performance, but at the cost of high complexity due to the required matrix inversion of large size. To solve this problem, this paper proposes a precoding scheme based on conjugate gradient (CG) method, which avoids the channel matrix inversion in an iterative way. Compared with RZF precoding, this proposed precoding scheme is able to reduce the computational complexity by about one order of magnitude. Furthermore, the computational complexity of the proposed precoding scheme is lower than the previously proposed linear approximate Neumann series expansion (NSE) precoding scheme. Simulation results indicate that the proposed CG-based precoding outperforms the NSE precoding both in BER performance and achievable channel capacity performance. Moreover, it can approach the performance of RZF precoding after few iterations.