An improved mu-law proportionate NLMS algorithm

In this paper, we propose an algorithm to improve the performance of the MU-LAW PNLMS algorithm (MPNLMS) for non-sparse impulse responses. Although the existing MPNLMS algorithm was recently proposed to achieve optimal proportionate step size for both large and small tap weights, it converges even slower than conventional NLMS algorithm for dispersive channels. The proposed approach adaptively estimates the sparsity of the impulse response to be identified. Then the estimation of this sparsity is incorporated into the IPNLMS algorithm to accordingly adjust its parameters. Simulation results verify the effectiveness of the proposed algorithm.