A new modified particle swarm optimization algorithm for adaptive equalization

In this paper, we present a novel modification to the standard particle swarm optimization (PSO) technique and illustrate the superiority of the proposed modified technique over other PSO-based techniques, with an application to the important area of adaptive channel equalization. Different published versions of the original PSO algorithms are first reviewed and the new proposed technique discussed in the context of the design of adaptive channel equalizers. An exhaustive simulation-based sensitivity analysis of the proposed PSO algorithm, with respect to its underpinning parameters, is carried out here so as to select the “best” (or near optimal) values of these parameters. The performance of various PSO algorithms, including our proposed algorithm, is compared in the context of adaptive channel equalization to that of the LMS algorithm through extensive simulations. This detailed comparison revealed the superior performance of our proposed PSO-based adaptive channel equalizer over both its LMS-based counterpart and other adaptive equalizers based on the published PSO algorithms. This superior performance was exhibited on both linear and nonlinear channels.