Convergence evaluation of variable step-size NLMS algorithm in adaptive channel equalization

The use of two simple and robust variable step-size approaches in the adaptation process of the Normalized Least Mean Square (NLMS) algorithm (VSS-NLMS) in the adaptive channel equalization is investigated. The NLMS algorithm with a fixed step-size (FSS-NLMS) usually results in a trade-off between the residual error and the convergence speed of the algorithm. It is proved by computer simulation that the VSS-NLMS algorithms presented here eliminate much of this trade-off. In this paper the Mean-Square Error (MSE) performance of using the VSS-NLMS algorithms in the adaptation process of adaptive channel equalization is investigated. The step-size variation makes it possible for the VSS-NLMS algorithm to converge faster and to a lower steady state error than in the FSS-NLMS case.