Optimization of Control Parameters of Differential Evolution Technique for the Design of FIR Pulse-shaping Filter in QPSK Modulated System

Abstract

Signal Processing in modern era, involves rigorous applications of various evolutionary algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Differential Evolution (DE) for the optimized design of aerodynamic shape, automated mirror, digital filter, computational intelligence etc. DE has been judged to be quite effective in designing different types of digital filter with good convergence behavior. The performance of the DE optimization technique could be improved to a further extent if the values of the two control parameters namely “Weighting Factor” and “Crossover Probability”, be chosen properly. In this paper, the effect of these two control parameters on the design of low pass FIR digital filter has extensively been studied. The impact of these control parameters on the convergence behavior of the DE technique has also been presented. The performance of the DE optimized filter has been adjudicated in terms of its magnitude and impulse responses. In addition, the DE optimized filter has been utilized as a pulse-shaping filter in a Quadrature Phase Shift Keying (QPSK) modulated system and its performance has further been studied in terms of Bit Error Rate (BER). Finally, the optimized values of the ‘’Weighting Factor’’ and “Crossover Probability” for this specific modulated system design problem has been recommended. Experimentally measured Eye diagrams have also confirmed the optimized values.