Alias-free subband adaptive filtering with critical sampling

Abstract

To overcome the limitations of a conventional fullband adaptive filtering, various subband adaptive filtering (SAF) structures have been proposed. Properly designed, an SAF will converge faster at a lower computational cost than a fullband structure. However, its design should consider the following two facts: the interband aliasing introduced by the downsampling process degrades its performance, and the filter bank in the SAF introduces additional computational overhead and system delay. In this paper, to fully exploit the benefits of using an SAF, an almost alias-free SAF structure with critical sampling is proposed. The interband alising is removed from the subband signal by isolating the aliasing using a bandwidth-increased analysis filter. Computer simulations show that the proposed structure converges faster than both an equivalent fullband structure at lower computational complexity and recently proposed SAF structures for a colored input.