Partial-LUT Designs for Low-Complexity Realization of DA-Based BLMS Adaptive Filter

Abstract

This brief presents two-optimized partial look-up table (LUT) designs for low-complexity realization of distributed arithmetic (DA) based block least-mean-square (BLMS) adaptive filter (ADF). These are based on the partial add-store (PAS) and partial store-add (PSA) methods. A novel optimization scheme is presented which exploits the redundancies between the partial inner-products with sliding-window of input-block. It is found that the PAS method provides shorter critical-path-delay than the PSA method. A case study on echo-cancellation is demonstrated for architectural trade-off between the proposed designs. Synthesis results show that the proposed PSA based BLMS ADF for 64 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sup> order offers 41.04% lesser area and 39.38% lesser power, while the PAS based BLMS ADF provides 52.08% lesser area and 50.05% lesser power as compared to the best existing work.