A Novel Time-Shared and LUT-Less Pipelined Architecture for LMS Adaptive Filter

Abstract

This article presents a novel time-shared and lookup table (LUT)-less pipelined architecture for a least-mean-square (LMS) adaptive filter (ADF). The proposed approach first employs a time-shared architecture for the pipelined LMS ADF to compute each filter partial product and coefficient increment term using a single multiplier. Critical path analysis of this architecture is carried out to determine the pipeline requirements. Next, a novel LUT-less multiplier is suggested by exploiting the symmetries between the odd-multiples. Due to the symmetries between the odd-multiples, offset terms are added using an adder tree. For higher wordlength coefficients, only a few adders are required to generate the odd-multiples, and only one offset adder tree is required. Finally, a novel super-latch is developed to pipeline the LUT-less multiplier with adaptation delays of the pipelined LMS ADF. From the implementation results, it is found that the proposed design for the 32nd-order filter occupies 60.32% less area, consumes 61.93% less power, and utilizes 58.83% less sliced LUTs and 63.28% fewer flip-flops over the best existing design.