Affine Projection Versoria Algorithm for Robust Adaptive Echo Cancellation in Hands-Free Voice Communications

In vehicle hands-free communication systems and video teleconferencing systems, echoes are typically encountered. Adaptive filters are usually employed to remove the echoes in these applications. However, large outliers and highly correlated speech input signals are two key factors that limit the performance of the adaptive filters. In this paper, we propose an affine projection Versoria (APV) algorithm, which is obtained by maximizing the summation of Versoria-cost reusing with a constraint on the square of the L
₂
-norm of the filter weight vector difference. In this way, the features of the Versoria-cost maximization and data reusing are combined and, consequently, the proposed APV algorithm obtains robustness to the large outliers and accelerates the convergence rate for the correlated input signals. The complexity of the proposed APV algorithm is analyzed and then a fast recursive filtering technique is introduced to reduce its complexity. A stability analysis proves that the proposed APV algorithm is convergent. In addition, an analytical expression of the steady-state excess mean-square error for the proposed APV algorithm has been derived and simulated results are in agreement with the theoretical analysis result. Simulations on echo channel estimation and echo cancellation show that the proposed APV algorithm performs much better than the maximum Versoria criterion, affine projection sign, and affine projection algorithms.