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Adaptive Channel Equalization Using Decision Directed and Dispersion Minimizing Equalizers Trained by Variable Step Size Firefly Algorithm

  • Archana Sarangi
  • Shubhendu Kumar Sarangi
  • Siba Prasada Panigrahi
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 695)

Abstract

This paper signifies to present a design methodology for equalization of nonlinear channels for weights adaptation. Adaptive algorithms such as PSO, FFA, and VSFFA-based channel equalizer aimed to minimize inter-symbol interference associated with broadcast channel. In this paper, we implemented various channel equalizers such as decision directed equalizer, dispersion minimizing equalizer using PSO, FFA, and VSFFA which are principally derivative-free optimization tools. These algorithms are appropriately used to update weights of equalizers. Accomplishment of proposed diverse channel equalizers are evaluated in terms of mean square error (MSE) and BER plots and assessments are made using evolutionary algorithms applied to equalizers. It is observed that proposed equalizer-based adaptive algorithms, mostly VSFFA trained equalizers, offer improved performance so far as accurateness of reception is taken into account.

Keywords

Particle swarm optimization Adaptive channel equalizer Firefly algorithm Variable step size firefly algorithm Decision directed equalizer Dispersion minimizing equalizer 

References

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Archana Sarangi
    • 1
  • Shubhendu Kumar Sarangi
    • 1
  • Siba Prasada Panigrahi
    • 2
  1. 1.ITER, Siksha ‘O’ Anusandhan UniversityBhubaneswarIndia
  2. 2.Department of Electrical EngineeringVSSUTBurlaIndia

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