Group Maximum Likelihood Detection Algorithm for a 4×4 V-BLAST System

Maximum likelihood(ML)algorithm not only has optimal performance but also has maximal computational complexity for detection of V-BLAST systems. Classical ordered successive interference cancellation(OSIC)algorithm has much lower complexity. However， it has a numerical value stability problem and has a largish performance gap by comparison to ML algorithm. Therefore， a group maximum likelihood (GML) algorithm is proposed for a 4×4 V-BLAST system in this paper， which is based on tradeoff between detection performance and computational complexity. On the basis of guarantee of preferable detection performance， it divides a four-dimension (4-D) ML detector into two 2-D ML detectors to reduce computational complexity. Moreover， a simplified maximum likelihood (SML) algorithm is also proposed to reduce further complexity by reducing the searching space of each 2-D ML detector from 2-D to 1-D. Simulations show that GML algorithm has about 7dB performance gain compared with OSIC algorithm at symbol error rate equals to 10^-3. After analysis， GML algorithm’s complexity reduces remarkably in large constellation modulation manner in comparison with that of ML-OSIC algorithm. This facilitates the hardware implementation.