Efficient QRM-MAP detector for spatial multiplexing MIMO systems

In this paper, we propose an efficient soft-detector for spatial multiplexing multiple-input multiple-output systems. Maximum a posteriori probability detection employing QR decomposition with M algorithm (QRM-MAP) achieves improved performance by adopting unbiased minimum-mean-square error (UMMSE) preprocessing. The efficiency of QRM-MAP can be further improved by using statistical information obtained from MMSE detection. Based on this information, the proposed detector orders tree branches and excludes insignificant branches in advance. To achieve low-and-fixed complexity, the node enumeration pattern that considers the greedy nature of the M algorithm is predetermined according to the node order. In addition, the soft information from MMSE can be used to compensate for the inherent performance loss caused by an insufficient number of candidates. Simulation results show that the proposed scheme provides an enhanced performance-complexity tradeoff as compared to the conventional schemes.