Multi-Objective Genetic Algorithms for computing Fast Fourier Transform for evolving Smart Sensors devices using Field Programmable gate arrays

Abstract

This research explores the use of Fast Fourier Transform (FFT) in the design of smart sensors and various other portable telecommunication devices. Literature reveals that genetic algorithms play an increasingly important role in the computing FFT for the design and implementation of the foresaid devices. In this paper, a multi- objective genetic algorithm for computing Fast Fourier Transform for evolving smart sensor devices has been designed and simulated in software in a field programmable gateway array using Altera Quartus II 13.0. Programmable logic units, ( Luts-representing genes in a chromosome) were designed using schematic /block diagrams and hardware description language and they were encoded into chromosomes and then optimized using field programmable gate arrays (FPGA) to achieve desired goals of portability and low energy consumption. The performance of our design was evaluated using Altera Quartus II Powerplay power analyser tool in terms of core static thermal power dissipation, core dynamic thermal power dissipation and input and output thermal power dissipation. The model was also evaluated in terms of functional correctness and portability. The results show significant improvements in all performance measures.