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A New adaptive functional-link neural-network-based DFE overcoming co-channel interference

  • Amir Hussain*
  • , John J. Soraghan
  • , Tariq S. Durrani
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

49 Scopus citations

Abstract

A new approach for the decision feedback equalizer (DFE) based on the functional-link neural network is described. The structure is applied to the problem of adaptive equalization in the presence of intersymbol interference (ISI), additive white Gaussian noise, and co-channel interference (CCI). It is shown through simulation results for a severe amplitude distorted co-channel system that the decision feedback functional-link equalizer (DFFLE) provides significantly superior bit-error rate (BER) performance characteristics compared to the conventional DFE, the linear transversal equalizer (LTE), the nonlinear radial basis function (RBF) neural-network-based structures and the feed-forward functional-link equalizer (FFLE)-based structures. The DFFLE is also shown to have a significantly simpler computational requirement relative to the RBF and the FFLE.

Original languageEnglish
Pages (from-to)1358-1362
Number of pages5
JournalIEEE Transactions on Communications
Volume45
Issue number11
DOIs
StatePublished - 1997
Externally publishedYes

Keywords

  • Co-channel interference suppression
  • Decision feedback equalizers
  • Neural networks

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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