A Blind Equalization Algorithm Based on Minimization of Normalized Variance for DS/CDMA Communications

摘要

This paper proposes a blind equalizer that pursues the maximization of a novel objective function. It consists of the ratio between the square of the mean signal power and the variance of the signal power. In this paper, important prepositions are first mathematically stated. The devised equalizer is asymptotically equivalent to the well-known constant-modulus algorithm (CMA) and the Kurtosis maximization algorithm (KMA) because they pursue the same ldquoRicianityrdquo criterion already employed in the ldquoRayleigh-nessrdquo test for spread-spectrum code acquisition. The performance of the addressed equalizers is then investigated by focusing on direct-sequence code-division multiple-access (DS/CDMA) communication environments in a downlink scenario. In particular, we have evidenced the effectiveness of the presented equalizer in the numerical examples in terms of robustness against the effect of interference, as well as in terms of convergence rate, in spite of a small amount of extra processing.