Area and Power Efficient VLSI Architecture of Distributed Arithmetic Based LMS Adaptive Filter - 2018


This paper presents a new area and power efficient VLSI architecture for least-mean-sq. (LMS) adaptive filterusing distributed arithmetic (DA). Conventionally, DA basedLMS adaptive filter needs look-up tables (LUTs) for filteringand weight updating operations. The size of LUTs grows exponentially with filter order. The proposed theme has reducedthe LUT size to half by storing the offset-binary-coding (OBC) combos of filter weights and input samples. To create theadaptive filter a lot of area and power economical, it is not necessary todecompose LUT into two smaller LUTs. Hence, by using the nondecomposed LUT the proposed design achieves vital savingsin space and power over the simplest existing theme. Moreover, the proposed architecture involves comparatively lesser hardwarecomplexity for the same LUT-size. From synthesis results, it isfound that the proposed design with 32nd order filter offers nineteen.eighty three% less area and consumes 20.fifty four p.c less power; utilizes 16.67 %and nineteen.04 p.c less number of LUT and FF respectively over thebest existing scheme.

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