Robust adaptive equalization using the filtered-X LMS algorithm

Abstract

The filtered-X LMS algorithm is currently the most popular method for adaptive filter design when there exists a transfer function in the error path. We introduce and modify this concept in the application of adaptive equalization for communication channels. A computer experiment was conducted on the equalization of a time-varying communication channel using both conventional LMS and modified filtered-X LMS algorithms. Monte Carlo simulation results demonstrate that the filtered-X has a better robust performance than that of the conventional LMS.