A class of sparseness-controlled algorithms for echo cancellation

Authors:
Pradeep Loganathan;Andy W. H. Khong;Patrick A. Naylor
Affiliations:
Department of Electrical and Electronic Engineering, Imperial College London, London, U.K.;School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore;Department of Electrical and Electronic Engineering, Imperial College London, London, U.K.
Venue:
IEEE Transactions on Audio, Speech, and Language Processing
Year:
2009

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Abstract

In the context of acoustic echo cancellation (AEC), it is shown that the level of sparseness in acoustic impulse responses can vary greatly in a mobile environment. When the response is strongly sparse, convergence of conventional approaches is poor. Drawing on techniques originally developed for network echo cancellation (NEC), we propose a class of AEC algorithms that can not only work well in both sparse and dispersive circumstances, but also adapt dynamically to the level of sparseness using a new sparseness-controlled approach. Simulation results, using white Gaussian noise (WGN) and speech input signals, show improved performance over existing methods. The proposed algorithms achieve these improvement with only a modest increase in computational complexity.