Tree Search based Approximate Maximum Likelihood Detector for Spatial Multiplexing Systems

In a spatial multiplexing system with multiple antennas on both sides of a wireless link, it is preferable to adopt the maximum likelihood (ML) detection to fully extract both multiplexing and diversity gain. In this paper, we present a new tree search based near ML detector that applies a new ordering in conjunction with efficient node exploration strategy. The error performance of the new detector closely approaches that of the ML detector. However, it is far less complex than conventional suboptimal tree detectors and maintains a fixed detection delay.