Blind Reduced-Rank Multi-user Detector for DS-CDMA Systems Based on Subspace

Abstract

A blind reduced-rank multi-user detector (MUD) based on a new reduced-rank subspace selection algorithm via variable threshold and an improved dimension estimation algorithm. By using the new reduced-rank subspace selection algorithm, the proper reduced-rank subspace is obtained quickly and the result can be reused. The improved Akaike information criterion (AIC) is adopted to estimate the dimension of the signal subspace in the subspace tracking. The criterion can reduce the computation of dimension estimation on the basis of the same error probability. When the dimension of signal subspace is overestimated, the performance of the blind reduced-rank multi-user detector is analyzed. The simulation results indicate that the reduced-rank subspace selection method based on variable threshold can achieve the desired system performance with the lower computational complexity