A Novel Sub-band Filtering Based LMS Adaptive Algorithm for Acoustic Echo Cancellation

In this paper, a sub-band filtering based least mean square (LMS) adaptive algorithm for acoustic echo cancellation is presented. A controlling parameter has been introduced to control the trade off between the convergence rate and the steady state mean square error (MSE). The performance of the proposed algorithm has been compared with some sub-band filtering methods, available in literature, used for acoustic echo cancellation for different values of the controlling parameter. It is observed that the convergence and the steady state MSE is dependent on the value of the controlling parameter. The computational complexity is also computed and it is seen that the proposed algorithm has lower computational complexity compared to the combined error algorithm from the literature.