Implementation of LMS-ALE Filter Using Vedic Algorithm
- *Corresponding Author:
- Joseph Jintu K
VLSI & Embedded systems
PESIT Bangalore, India
Tel: 080661 86610
E-mail: [email protected]
Received Date: July 20, 2015; Accepted Date: August 19, 2016; Published Date: August 26, 2016
Citation: Joseph Jintu K, Purushotham U (2016) Implementation of LMS-ALE Filter Using Vedic Algorithm. J Electr Electron Syst 5:192. doi: 10.4172/2332-0796.1000192
Copyright: © 2016 Joseph Jintu K, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
ALE or adaptive line Enhancers are special kinds of adaptive filters widely used in noise cancellation circuits. In circuits where we don’t have any prior knowledge of signal and noise, fixed filters unit never works good. Among adaptive filter ring algorithms LMS algorithm is very common, in our work also we use LMS algorithm. LMS-ALE filters removes the sinusoidal noise signals present in the channel by calculating the filter coefficients in every iteration. LMSALE filter has large number of multiplier units. FFT or Fast Fourier Transform blocks present in LMS algorithm again consist of large array of multiplier units. Optimization of LMS-ALE filter lies must start from optimization of multiplier blocks. Here we use Vedic “Vertical and crosswise algorithm” for multiplier design. When compared to conventional booth multiplier based LMS-ALE filter units, Vedic multipliers gives more performance in areas like resource utilization, power requirement, delay etc. The work includes designing Vedic multipliers, complex Vedic multipliers, redesigning Radix-8 FFT using Vedic multipliers, redesigning LMS block using Vedic FFT, redesigning LMS ALE filter using Vedic multipliers and Vedic LMS blocks. Major part of design is done in verilog using Xilinx ISE design suite. ADC block present in LMS-ALE filter is done in Matlab version 2013.