A nonparametric variable step-size subband adaptive filtering algorithm for acoustic echo cancellation

Acoustic echo cancellation is often applied in communication and video call system to reduce unnecessary echoes generated between speakers and microphones. In these systems, the speech input signal of the adaptive filter is often colored and unstable, which decays the convergence rate of the adaptive filter if the NLMS algorithm is used. In this paper, an improved nonparametric variable step-size subband (NPVSS-NSAF) algorithm is proposed to address the problem. The variable step-size is derived by minimizing the sum of the square Euclidean norm of the difference between the optimal weight vectors to be updated and the past estimated weight vectors. Then the parameters are eliminated by using the power of subband signal noise equal to the power of subband posteriori error. The performance of the proposed algorithm is simulated in the aspects of misalignment and return loss enhancement. Experiment results show a fast convergence rate and low misalignment of the proposed algorithm in system identification.