Selective-partial-update proportionate normalized least-mean-squares algorithm for network echo cancellation

A reduced-complexity, fast converging adaptive filtering algorithm is developed for network echo cancellation applications in sparse echo paths. The new algorithm—selective-partial-update proportionate NLMS—is based on the proportionate NLMS (PNLMS) algorithm and selective partial updating of the adaptive filter coefficients. PNLMS exploits the sparseness of the channel to speed up the initial convergence of the NLMS algorithm by weighting the regressor data proportionately with the estimated magnitude of the channel impulse response. Selective partial updating is essentially a data selection method to reduce the computational complexity. The performance of selective-partial-update PNLMS is compared with PNLMS for echo paths specified in ITU-T Recommendation G.168, and selective-partial-update PNLMS is observed to maintain the convergence speed of PNLMS at a reduced computational complexity.