An efficient and effective variable step size NLMS algorithm

Using the least-mean-square (LMS) and the normalized LMS (NLMS) algorithms, the adaptive filter usually results in a trade-off between the convergence speed and adaptation precision. Recently, in order to resolve this problem, several variable step size NLMS (VSS-NLMS) algorithms that provide faster convergence than the LMS and NLMS have been proposed. This paper presents a new VSS-NLMS algorithm that is simple, but possesses, good characteristics. In the proposed algorithm, the input power and error signals are used to design the step size parameter at each iteration. Simulation results demonstrate that in the scenario of channel equalization, the proposed algorithm accomplishes faster start-up and gives better precision than the conventional algorithms.