Design of a Discrete Adaptive Equalizer for Noisy Channel using Quantum Behaved Particle Swarm Optimization Technique

Objectives: In this paper, we propose to develop a discrete adaptive equalizer based on Quantum behaved Particle Swarm Optimization (QPSO) technique for noisy channel. Methods/Statistical Analysis: Equalizers have to deal with harder and more complicated problems today due to crowded communication channels and increasing interference level. Findings: This work is an effort to counterbalance Inter-Symbol Interference (ISI) and other nonlinear impairments occurring in real world channels due to nonlinear devices installed in transceivers, cross talk, presence of impulsive noise, multipath propagation and the nature of physical medium itself. A simple, yet efficient optimization algorithm QPSO which belongs to a class of bare-bones PSO family is employed for this purpose. The performance of the proposed equalizer is compared with Least Mean Square (LMS) and other popular variations of PSO, namely Constant Weight Inertia (CWI-PSO) and Linear Decay Inertia (LDI-PSO) algorithms in order to investigate its efficacy. Application/Improvements: Mean Square Error (MSE) and Bit Error Rate (BER) are evaluated for each algorithm and a comparative study of the results reveal that QPSO enjoys an improved performance over other considered algorithms. The proposed discrete equalizer model can be widely used in communication system, especially mobile and satellite communication due to its effectiveness in noisy environment.