Approximate ML Detection with the Best Channel Matrix Selection for MIMO Systems

Abstract

In this paper, a best channel matrix selection scheme (BCMS) is proposed to approximate maximum likelihood (ML) detection for a multiple-input multiple-output system. For a one stage BCMS scheme, one of the transmitted symbols is selected to perform ML detection and the other symbols are detected by zero forcing (ZF). To increase the diversity of the symbols that are detected by ZF, multi-stage BCMS detection scheme is used to further improve the system performance. Simulation results show that the performance of the proposed BCMS scheme can approach that of ML detection with a significant reduction in complexity.