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Journal ArticleDOI

A High-Performance Energy-Efficient Architecture for FIR Adaptive Filter Based on New Distributed Arithmetic Formulation of Block LMS Algorithm

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TLDR
An efficient distributed-arithmetic formulation for the implementation of block least mean square (BLMS) algorithm using a novel look-up table (LUT)-sharing technique for the computation of filter outputs and weight-increment terms of BLMS algorithm, which offers significant saving of adders which constitute a major component of DA-based structures.
Abstract
In this paper, we present an efficient distributed-arithmetic (DA) formulation for the implementation of block least mean square (BLMS) algorithm. The proposed DA-based design uses a novel look-up table (LUT)-sharing technique for the computation of filter outputs and weight-increment terms of BLMS algorithm. Besides, it offers significant saving of adders which constitute a major component of DA-based structures. Also, we have suggested a novel LUT-based weight updating scheme for BLMS algorithm, where only one set of LUTs out of M sets need to be modified in every iteration, where N=ML, N, and L are, respectively, the filter length and input block-size. Based on the proposed DA formulation, we have derived a parallel architecture for the implementation of BLMS adaptive digital filter (ADF). Compared with the best of the existing DA-based LMS structures, proposed one involves nearly L/6 times adders and L times LUT words, and offers nearly L times throughput of the other. It requires nearly 25% more flip-flops and does not involve variable shifters like those of existing structures. It involves less LUT access per output (LAPO) than the existing structure for block-size higher than 4. For block-size 8 and filter length 64, the proposed structure involves 2.47 times more adders, 15% more flip-flops, 43% less LAPO than the best of existing structures, and offers 5.22 times higher throughput. The number of adders of the proposed structure does not increase proportionately with block size; and the number of flip-flops is independent of block-size. This is a major advantage of the proposed structure for reducing its area delay product (ADP); particularly, when a large order ADF is implemented for higher block-sizes. ASIC synthesis result shows that, the proposed structure for filter length 64, has almost 14% and 30% less ADP and 25% and 37% less EPO than the best of the existing structures for block size 4 and 8, respectively.

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Citations
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Journal ArticleDOI

LMS Adaptive Filters for Noise Cancellation: A Review

TL;DR: Algorithms such as LMS and RLS proves to be vital in the noise cancellation are reviewed including principle and recent modifications to increase the convergence rate and reduce the computational complexity for future implementation.
Journal ArticleDOI

A High-Performance FIR Filter Architecture for Fixed and Reconfigurable Applications

TL;DR: A general multiplier-based architecture for the proposed transpose form block filter for reconfigurable applications is derived and a low-complexity design using the MCM scheme is also presented for the block implementation of fixed FIR filters.
Journal ArticleDOI

A High-Performance and Energy-Efficient FIR Adaptive Filter Using Approximate Distributed Arithmetic Circuits

TL;DR: The radix-8 Booth algorithm is used to reduce the number of partial products in the DA architecture, although no multiplication is explicitly performed, and the proposed design achieves 45%–61% lower EPO compared with the DLMS design.
Journal ArticleDOI

Optimal Complexity Architectures for Pipelined Distributed Arithmetic-Based LMS Adaptive Filter

TL;DR: Three optimal-complexity structures (I, II, III) for pipelined distributed arithmetic (DA) based least-mean-square (LMS) adaptive filter show significant hardware savings, Structure-I has least critical-path and Structure-II, III offer superior convergence performance.
Journal ArticleDOI

A high-performance VLSI architecture for reconfigurable FIR using distributed arithmetic

TL;DR: It is found that direct-form structure involves significantly less registers than the transpose- form structure, and it allows register reuse in parallel implementation, which is a major advantage for area-delay and energy efficient high-throughput implementation of reconfigurable FIR filters of higher block-sizes.
References
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Book

Vlsi Digital Signal Processing Systems: Design And Implementation

TL;DR: This book discusses Digital Signal Processing Systems, Pipelining and Parallel Processing, Synchronous, Wave, and Asynchronous Pipelines, and Bit-Level Arithmetic Architectures.
Journal ArticleDOI

Applications of distributed arithmetic to digital signal processing: a tutorial review

TL;DR: DA is applied to a biquadratic digital filter, providing an example of vector dot-product and vector-matrix-product mechanization and it is seen that DA is a very efficient means to mechanize computations that are dominated by inner products.
Book

Least-mean-square adaptive filters

TL;DR: This paper presents a meta-modelling framework for estimating the energy conservation and the learning ability of LMS Adaptive Filters using a number of simple and scalable algorithms.
Journal ArticleDOI

Block implementation of adaptive digital filters

TL;DR: In this paper, a block adaptive filtering procedure is proposed in which the filter coefficients are adjusted once per each output block in accordance with a generalized least mean-square (LMS) algorithm.
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