A decision feedback recurrent neural equalizer for digital communication

Sunghwan Ong, Sooyong Choi, Cheolwoo You, Daesik Hong

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we introduce an adaptive decision feedback recurrent neural equalizer (DFRNE) whose small size and high performance makes it suitable for high-speed channel equalization. By evaluating its performance through computer simulations for various channels, the DFRNE has comparable performance with traditional equalizers when the channel interferences are mild; it outperforms them when the channel's transfer function has spectral null or when severe nonlinear distortion is present. In addition, the DFRNE, being essentially an IIR filter, is shown to outperform multilayer perceptron equalizers in linear and nonlinear channel equalization cases.

Original languageEnglish
Title of host publication1997 IEEE International Conference on Neural Networks, ICNN 1997
Pages142-147
Number of pages6
DOIs
Publication statusPublished - 1997
Event1997 IEEE International Conference on Neural Networks, ICNN 1997 - Houston, TX, United States
Duration: 1997 Jun 91997 Jun 12

Publication series

NameIEEE International Conference on Neural Networks - Conference Proceedings
Volume1
ISSN (Print)1098-7576

Other

Other1997 IEEE International Conference on Neural Networks, ICNN 1997
CountryUnited States
CityHouston, TX
Period97/6/997/6/12

All Science Journal Classification (ASJC) codes

  • Software

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