Identification of Nonlinear Communication Channel Using an Novel Particle Swarm Optimization Technique

  • Authors:
  • Wang Qiang;Zhang Jiashu;Yang Jing

  • Affiliations:
  • -;-;-

  • Venue:
  • CSSE '08 Proceedings of the 2008 International Conference on Computer Science and Software Engineering - Volume 01
  • Year:
  • 2008

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Abstract

In this paper, we explore the use of particle swarm optimization (PSO) as the key search approach of a methodology for estimating the parameters of the discrete Volterra time-series to model nonlinear communication channels. Neither the system order nor the number of time delays need to be prespecified a priori in the identification process. The proposed approach exhibits excellent anti-noise character employing a small number of sample data points. Simulation results illustrate the effectiveness of the proposed approach as compared to the genetic algorithm (GA) approach in terms of speed and accuracy.