A Low Complexity Detector for Massive MIMO Uplink Systems

Abstract

Fifth generation wireless communication system is implemented by several mobile companies where important technologies are employed such as the massive multiple-input multiple-output (MIMO). Although it improves the spectrum and energy efficiencies, it is not a trivial to propose an efficient detector for massive MIMO systems because a large number of antennas increases the computational complexity. In this paper, approximate message passing (AMP) is exploited in the massive MIMO uplink (UL) data detection. Although the AMP method is suffering from a considerable performance in special cases, an efficient selection of the initial solution affects greatly the convergence rate, the bit-error-rate performance, and the computational complexity. In this paper, three efficient initialization methods of the AMP-based massive MIMO UL detector are proposed based on iterative methods, namely, the successive overrelaxation, the Gauss–Seidel, and the Jacobi. In addition, a stair matrix is exploited to achieve high convergence rate. Numerical results show that the proposed detector achieved a considerable performance improvement and complexity reduction in comparison with the traditional AMP-based detector.