A flexible near-optimum detector for V-BLAST

V-BLAST is an important multiple input and multiple output (MIMO) space-time architecture for future high data rate wireless communication system. In this paper, a novel computation-efficient metric-guided (MG) algorithm is proposed for V-BLAST signal detection. This algorithm can achieve near maximum likelihood (ML) detection performance with tractable detection complexity which is inherently adaptive to channel signal-noise ratio (SNR). Through adjusting the value oof one parameter, MG algorith offers the flexibility of achieving any in-between performance-complexity tradeoff between an efficient near-ML detection and original nulling/cancelling algorithm for V-BLAST. Simulation results show that proposed algorithm can offer near-ML detection performance with complexity even less than that of the Schnorr-Euchner sphere decoder (M. O. Damen et al., 2003) and stack algorithm (S. Baro et al., 2003).