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An optimized MAC based architecture for adaptive digital filter

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Title An optimized MAC based architecture for adaptive digital filter
 
Creator James, Britto Pari
Dhandapani, Vaithiyanathan
Mariammal, Karuthapandian
 
Subject Memory optimisation
Adaptive filter
LMS
FIR
MAC
FPGA
 
Description 906-915
Filter design in signal processing field plays a vital role in achieving low power dissipation, which is essential for portable gadgets. This paper proposes an effective flexible FIR filter structure, which is adaptive and utilizes multiply–accumulate (MAC) core. Most common algorithm for filter coefficient optimization includes least mean square (LMS) and recursive least square (RLS). Though the performance of the recursive least square (RLS) algorithm is superior as compared to the least mean square (LMS); because of higher arithmetic complexity in design, it has not been preferred for real time applications. The fundamental filter has used a LMS based tapped delay line filter, which is practically a feasible choice for adaptive filtering algorithm in order to attain lesser computation. In the proposed work, the adjustable coefficient filters using an optimized LMS approach has been implemented for the utilization of determining the unexplored system. The filter tap considered here is a 32-tap and its analysis and synthesis has been carried out using hardware description language (HDL) programming and synthesized in field programmable gate array (FPGA) devices. The placement and post routing design has offered good performance in terms of utilized resources. The implemented filter architecture requires 80% reduction in resources and has enhanced the clock frequency by about five times when examined with the reported architecture.
 
Date 2020-11-24T08:26:12Z
2020-11-24T08:26:12Z
2020-08
 
Type Article
 
Identifier 0975-1017 (Online); 0971-4588 (Print)
http://nopr.niscair.res.in/handle/123456789/55676
 
Language en_US
 
Rights CC Attribution-Noncommercial-No Derivative Works 2.5 India
 
Publisher NISCAIR-CSIR, India
 
Source IJEMS Vol.27(4) [August 2020]