A modified IPNLMS algorithm using system sparseness

Channels with sparse impulse response appear in echo path, such as network echo and acoustic echo. A proportionate adaptive algorithm has been proposed to accelerate convergence speed than the normalized least mean square (NLMS) algorithm in the sparse system. In general, the weight of the proportionate term in improved proportionate NLMS (IPNLMS) algorithm is set to a large value when the system is sparse. However, the relationship between the weight of the proportional term and the system sparseness is not clear. We reveal the relationship that the weight increases with an increase of system sparseness by computer simulations. And we propose a variable weight of the proportional term in IPNLMS algorithm using the system sparseness. Computer simulations demonstrate that the proposed algorithm provides faster convergence than the conventional NLMS and IPNLMS algorithms on sparse systems.