Multichannel Acoustic Echo Canceler Based on Particle Swarm Optimization

SUMMARY In multichannel acoustic echo cancelers based on linear combination, the uniqueness problem exists, namely, that adaptive filters cannot identify the correct echo paths due to highly cross‐correlated multichannel input signals. Preprocessing of the input signal is good candidates for solving this problem. However, it can have the drawbacks of degrading audio quality as a secondary problem. In this misadjustment problem, a universal solution is not derived in the conventional adaptive filter's optimization. In this paper, we propose a new multichannel adaptive echo canceling algorithm based on particle swarm optimization (PSO) without preprocessing of the input signals. PSO is a stochastic optimization technique inspired by the social behavior of bird flocking or fish schooling, and this is the first attempt to apply it to multichannel acoustic echo cancelers. By performing various simulations, we confirm that the proposed method can estimate correct echo paths with highly cross‐correlated input signals.