VLSI Implementation of Throughput Efficient Distributed Arithmetic Based LMS Adaptive Filter

Abstract

A new throughput efficient implementation scheme for least mean square (LMS) adaptive filter using distributed arithmetic (DA) is presented for IEEE 802.11b PHY scenarios. It is based on pre-computing and storing the filter partial products in lookup tables (LUTs). In contrast to fixed coefficients filter, an adaptive filter requires each stored partial product to be updated time-to-time. This paper presents a new strategy for DA based adaptive filter using offset binary coding (OBC) technique. The proposed strategy eliminates two oldest sample and allows possible decomposition of LUT into four sub-LUTs. Hence, the proposed approach provides significant improvement in throughput at the cost of few 2-to-1 multiplexers. Synthesis results have shown that the proposed scheme occupies almost similar area and improves the throughput by several fold. For instance, a 32- tap adaptive filter with the proposed implementation produces nearly 1.8 MSPS (million samples per second) more throughput as compared to the best existing scheme.