Evolutionary MPNN for Channel Equalization

Archana Sarangi, Bijay Ketan Panigrahi, Siba Prasada Panigrahi

Department of AEIE, ITER, SOA University, Bhubaneswar, India.
Department of Electrical Engineering, IIT, Delhi, India.
Department of Electrical Engineering, KIST, Bhubaneswar, India.

DOI: 10.4236/jsip.2011.21002                

Abstract

This paper proposes a novel equalizer, termed here as Evolutionary MPNN, where a complex modified probabilistic Neural Networks (MPNN) acts as a filter for the detected signal pattern. The neurons were embedded with optimization algorithms. We have considered two optimization algorithms, Bacteria Foraging Optimization (BFO) and Ant Colony Optimization (ACO). The proposed structure have the ability to process complex signals also can perform for slowly varying channels. Also, Simulation results prove the superior performance of the proposed equalizer over the existing MPNN equalizers.

Keywords

Channel Equalization, Probabilistic Neural Network, Bacteria Foraging, Ant Colony Optimization

Conflicts of Interest

The authors declare no conflicts of interest.

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