Minimization of Hamming Distance in FIR Filters by using Steepest Descent Method and Evolutionary Programming

Abstract

Abstract With the explosive growth of wireless communication system and portable devices, the power reduction has become a major problem. In applications, such as personal communication systems, and portable storage devices, low power dissipation, hence longer battery lifetime is a must. With the rapid growth of internet and information on demand, handheld wireless terminals are becoming increasingly popular. Many of the communication systems today utilize digital signal processors (DSP) to resolve the transmitted information. Finite Impulse Response (FIR) filters have been and continue to be important building blocks in many digital signal processing (DSP) systems. Signal switching activity is the major component of power dissipation in CMOS circuits. Hamming distance is a measure of switching activity corresponding to the number of energy consuming transitions in multiplier and accumulate (MAC) of FIR filter while implementing on Digital Signal Processor (DSP).The transition densities of multiplier inputs depend on the Hamming distance between successive filter coefficient values. For a multiplier the power is directly dependent on the transition densities and the probabilities of multiplier inputs. The Hamming distance between consecutive coefficient values and the number of signal toggling in opposite directions thus forms the measure of bus power dissipation. In this thesis the Hamming distance in FIR filters is minimized by minimizing the switching activity using ‘Steepest Decent’ and ‘Evolutionary Programming’ optimization techniques to reduce the power dissipation and to increase the battery life of portable multimedia devices.