Rectangle blocking matrices based unitary multistage Wiener reduced-rank joint detection algorithm for multiple input multiple output systems

Abstract

Traditional equalization algorithms for multiple input multiple output (MIMO) systems suffer from high complexity and low convergence rate. So an improved adaptive reduced-rank joint detection algorithm of multistage Wiener filter (MSWF) based on rectangle blocking matrices is proposed. The MSWF is implemented by the correlation subtraction algorithm (CSA) structure and is called unitary multistage Wiener filter (UMSWF). The new scheme adopts rectangle submatrix as blocking matrix, which is chosen from the square blocking matrix for UMSWF. The proposed algorithm can reduce the size of the observation data vectors step by step in the forward recursion decomposition of UMSWF. Thus, the computational complexity is reduced and the convergence rate is increased. Theoretical analysis and simulation results show that this improved adaptive reduced-rank joint detection algorithm of UMSWF based on rectangle blocking matrix has better performance such as lower complexity and faster convergence rate. In particular, simulations are conducted in the vertical-Bell Labs layered space-time (V-BLAST) system which adopts BPSK modulation, where 4 and 8 antennas are equipped at the transmitter and receiver, respectively. Compared with traditional equalization algorithm based on UMSWF, our new method can achieve the same BER performance at high SNR with only 0.5 times that of computational complexity.