A decision feedback recurrent neural equalizer for digital communication

Sunghwan Ong; Sooyong Choi; Cheolwoo You; Daesik Hong

doi:10.1109/ICNN.1997.611653

A decision feedback recurrent neural equalizer for digital communication

Sunghwan Ong, Sooyong Choi, Cheolwoo You, Daesik Hong

Department of Electrical and Electronic Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

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 language	English
Title of host publication	1997 IEEE International Conference on Neural Networks, ICNN 1997
Pages	142-147
Number of pages	6
DOIs	https://doi.org/10.1109/ICNN.1997.611653
Publication status	Published - 1997
Event	1997 IEEE International Conference on Neural Networks, ICNN 1997 - Houston, TX, United States Duration: 1997 Jun 9 → 1997 Jun 12

Publication series

Name	IEEE International Conference on Neural Networks - Conference Proceedings
Volume	1
ISSN (Print)	1098-7576

Other

Other	1997 IEEE International Conference on Neural Networks, ICNN 1997
Country/Territory	United States
City	Houston, TX
Period	97/6/9 → 97/6/12

All Science Journal Classification (ASJC) codes

Software

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10.1109/ICNN.1997.611653

Cite this

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title = "A decision feedback recurrent neural equalizer for digital communication",

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.",

author = "Sunghwan Ong and Sooyong Choi and Cheolwoo You and Daesik Hong",

year = "1997",

doi = "10.1109/ICNN.1997.611653",

language = "English",

isbn = "0780341228",

series = "IEEE International Conference on Neural Networks - Conference Proceedings",

pages = "142--147",

booktitle = "1997 IEEE International Conference on Neural Networks, ICNN 1997",

note = "1997 IEEE International Conference on Neural Networks, ICNN 1997 ; Conference date: 09-06-1997 Through 12-06-1997",

}

Ong, S, Choi, S, You, C & Hong, D 1997, A decision feedback recurrent neural equalizer for digital communication. in 1997 IEEE International Conference on Neural Networks, ICNN 1997., 611653, IEEE International Conference on Neural Networks - Conference Proceedings, vol. 1, pp. 142-147, 1997 IEEE International Conference on Neural Networks, ICNN 1997, Houston, TX, United States, 97/6/9. https://doi.org/10.1109/ICNN.1997.611653

A decision feedback recurrent neural equalizer for digital communication. / Ong, Sunghwan; Choi, Sooyong; You, Cheolwoo et al.

1997 IEEE International Conference on Neural Networks, ICNN 1997. 1997. p. 142-147 611653 (IEEE International Conference on Neural Networks - Conference Proceedings; Vol. 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Ong, Sunghwan

AU - Choi, Sooyong

AU - You, Cheolwoo

AU - Hong, Daesik

PY - 1997

Y1 - 1997

N2 - 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.

AB - 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.

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DO - 10.1109/ICNN.1997.611653

M3 - Conference contribution

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T3 - IEEE International Conference on Neural Networks - Conference Proceedings

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BT - 1997 IEEE International Conference on Neural Networks, ICNN 1997

T2 - 1997 IEEE International Conference on Neural Networks, ICNN 1997

Y2 - 9 June 1997 through 12 June 1997

ER -

A decision feedback recurrent neural equalizer for digital communication

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