A distributed arithmetic based approach for the implementation of the Sign-LMS adaptive filter

Abstract

A Distributed Arithmetic (DA) based scheme for the implementation of Sign-LMS adaptive filter is presented. DA is an efficient technique for the computation of the dot product of two vectors. This is done by storing the pre-computed partial-products in memories which are then shift-accumulated for the computation of the output. DA can be used for the realization of the finite impulse response (FIR) filters, however, for the realization of the adaptive filters, the partial-products have to be updated from time to time. This is achieved by using a memory which stores the partial-products of the set of recent input samples. The proposed scheme has a convergence performance similar to that of the multiply-and-accumulate (MAC) based implementation. Results show that the throughput of the DA based implementation is better than the MAC based implementation. Further, it is observed that the throughput is almost a constant with respect to the filter order which makes it more suitable for implementing large filters.