Constant modulus blind equalization based on fractional lower-order statistics

摘要

The presence of non-Gaussian ambient channel noise in wireless systems can degrade the performance of existing equalizers and signal detectors. In this paper, we investigate the problem of blind equalization in noisy communication channels by addressing the negative effects of heavy-tailed noise to the original constant modulus algorithm (CMA). We propose a new CM criterion employing fractional lower-order statistics (FLOS) of the equalizer input. The associated FLOS-CM blind equalizer, based on a stochastic gradient descent algorithm, is able to mitigate impulsive channel noise while restoring the constant modulus character of the transmitted communication signal. We perform an analytic study of the lock and capture properties of the proposed adaptive filter and we illustrate its improved convergence behavior and lower bit error rate through computer simulations with various types of noise environments that include the Gaussian and the alpha-stable.