Adaptive filtering using a highly oversampled weighted overlap-add filterbank in an ultra low-power system

Abstract

Filterbank analysis and synthesis strategies prove advantageous in many signal processing areas operating as a divide and conquer strategy tackling difficult problems into an equivalent series of much simpler problems. For example, large convolutional systems encountered in applications such as echo cancellation and feedback cancellation may require a large number of filter taps. Using the filterbank technique, it may equivalently be implemented as a parallel combination of much shorter subband filters. When properly designed, the filterbank subband signals are minimally overlapping in frequency yielding signals that are approximately orthogonal to each other. Lately, digital filterbank techniques, with great precision, have enabled many strategies to be implemented that were difficult or impractical with analog structures. Accordingly, much theory has been developed including the so-called perfect reconstruction filterbank. An oversampled DFT filterbank using WOLA (weighted overlap-add) processing provides an extremely efficient and elegant solution. This paper describes this filterbank within dedicated ASIC and algorithmic procedures for casting many algorithms into a multi-rate framework.