Adaptive electrical signal post-processing with varying representations in optical communication systems

Stephen Hunt; Yi Sun; Alex Shafarenko; Rod Adams; Neil Davey; Brendan Slater; Ranjeet Bhamber; Sonia Boscolo; Sergei K. Turitsyn

doi:10.1007/978-3-642-03969-0_22

Adaptive electrical signal post-processing with varying representations in optical communication systems

Stephen Hunt^*, Yi Sun, Alex Shafarenko, Rod Adams, Neil Davey, Brendan Slater, Ranjeet Bhamber, Sonia Boscolo, Sergei K. Turitsyn

^*Corresponding author for this work

Research output: Chapter in Book/Published conference output › Conference publication

Abstract

Improving bit error rates in optical communication systems is a difficult and important problem. Error detection and correction must take place at high speed, and be extremely accurate. Also, different communication channels have different characteristics, and those characteristics may change over time. We show the feasibility of using simple artificial neural networks to address these problems, and examine the effect of using different representations of signal waveforms on the accuracy of error correction. The results we have obtained lead us to the conclusion that a machine learning system based on these principles can improve on the performance of existing error correction hardware at the speed required, whilst being able to adapt to suit the characteristics of different communication channels.

Original language	English
Title of host publication	Engineering Applications of Neural Networks : 11th International Conference, EANN 2009, London, UK, August 27-29, 2009. Proceedings
Place of Publication	Berlin (DE)
Publisher	Springer
Pages	235-245
Number of pages	11
ISBN (Electronic)	978-3-642-03969-0
ISBN (Print)	3-642-03968-5, 978-3-642-03968-3
DOIs	https://doi.org/10.1007/978-3-642-03969-0_22
Publication status	Published - 2009
Event	11th International Conference on Engineering Applications of Neural Networks, EANN 2009 - London, United Kingdom Duration: 27 Aug 2009 → 29 Aug 2009

Publication series

Name	Communications in Computer and Information Science
Publisher	Springer
Volume	43
ISSN (Print)	1865-0929

Conference

Conference	11th International Conference on Engineering Applications of Neural Networks, EANN 2009
Country/Territory	United Kingdom
City	London
Period	27/08/09 → 29/08/09

Keywords

adaptive signal processing
classification
Error correction
optical communication

Access to Document

10.1007/978-3-642-03969-0_22

Cite this

Hunt, S., Sun, Y., Shafarenko, A., Adams, R., Davey, N., Slater, B., Bhamber, R., Boscolo, S., & Turitsyn, S. K. (2009). Adaptive electrical signal post-processing with varying representations in optical communication systems. In Engineering Applications of Neural Networks : 11th International Conference, EANN 2009, London, UK, August 27-29, 2009. Proceedings (pp. 235-245). (Communications in Computer and Information Science; Vol. 43). Springer. https://doi.org/10.1007/978-3-642-03969-0_22

Hunt, Stephen ; Sun, Yi ; Shafarenko, Alex et al. / Adaptive electrical signal post-processing with varying representations in optical communication systems. Engineering Applications of Neural Networks : 11th International Conference, EANN 2009, London, UK, August 27-29, 2009. Proceedings. Berlin (DE) : Springer, 2009. pp. 235-245 (Communications in Computer and Information Science).

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title = "Adaptive electrical signal post-processing with varying representations in optical communication systems",

abstract = "Improving bit error rates in optical communication systems is a difficult and important problem. Error detection and correction must take place at high speed, and be extremely accurate. Also, different communication channels have different characteristics, and those characteristics may change over time. We show the feasibility of using simple artificial neural networks to address these problems, and examine the effect of using different representations of signal waveforms on the accuracy of error correction. The results we have obtained lead us to the conclusion that a machine learning system based on these principles can improve on the performance of existing error correction hardware at the speed required, whilst being able to adapt to suit the characteristics of different communication channels.",

keywords = "adaptive signal processing, classification, Error correction, optical communication",

author = "Stephen Hunt and Yi Sun and Alex Shafarenko and Rod Adams and Neil Davey and Brendan Slater and Ranjeet Bhamber and Sonia Boscolo and Turitsyn, {Sergei K.}",

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address = "Germany",

note = "11th International Conference on Engineering Applications of Neural Networks, EANN 2009 ; Conference date: 27-08-2009 Through 29-08-2009",

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Hunt, S, Sun, Y, Shafarenko, A, Adams, R, Davey, N, Slater, B, Bhamber, R, Boscolo, S & Turitsyn, SK 2009, Adaptive electrical signal post-processing with varying representations in optical communication systems. in Engineering Applications of Neural Networks : 11th International Conference, EANN 2009, London, UK, August 27-29, 2009. Proceedings. Communications in Computer and Information Science, vol. 43, Springer, Berlin (DE), pp. 235-245, 11th International Conference on Engineering Applications of Neural Networks, EANN 2009, London, United Kingdom, 27/08/09. https://doi.org/10.1007/978-3-642-03969-0_22

Adaptive electrical signal post-processing with varying representations in optical communication systems. / Hunt, Stephen; Sun, Yi; Shafarenko, Alex et al.
Engineering Applications of Neural Networks : 11th International Conference, EANN 2009, London, UK, August 27-29, 2009. Proceedings. Berlin (DE): Springer, 2009. p. 235-245 (Communications in Computer and Information Science; Vol. 43).

Research output: Chapter in Book/Published conference output › Conference publication

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T1 - Adaptive electrical signal post-processing with varying representations in optical communication systems

AU - Hunt, Stephen

AU - Sun, Yi

AU - Shafarenko, Alex

AU - Adams, Rod

AU - Davey, Neil

AU - Slater, Brendan

AU - Bhamber, Ranjeet

AU - Boscolo, Sonia

AU - Turitsyn, Sergei K.

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N2 - Improving bit error rates in optical communication systems is a difficult and important problem. Error detection and correction must take place at high speed, and be extremely accurate. Also, different communication channels have different characteristics, and those characteristics may change over time. We show the feasibility of using simple artificial neural networks to address these problems, and examine the effect of using different representations of signal waveforms on the accuracy of error correction. The results we have obtained lead us to the conclusion that a machine learning system based on these principles can improve on the performance of existing error correction hardware at the speed required, whilst being able to adapt to suit the characteristics of different communication channels.

AB - Improving bit error rates in optical communication systems is a difficult and important problem. Error detection and correction must take place at high speed, and be extremely accurate. Also, different communication channels have different characteristics, and those characteristics may change over time. We show the feasibility of using simple artificial neural networks to address these problems, and examine the effect of using different representations of signal waveforms on the accuracy of error correction. The results we have obtained lead us to the conclusion that a machine learning system based on these principles can improve on the performance of existing error correction hardware at the speed required, whilst being able to adapt to suit the characteristics of different communication channels.

KW - adaptive signal processing

KW - classification

KW - Error correction

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Hunt S, Sun Y, Shafarenko A, Adams R, Davey N, Slater B et al. Adaptive electrical signal post-processing with varying representations in optical communication systems. In Engineering Applications of Neural Networks : 11th International Conference, EANN 2009, London, UK, August 27-29, 2009. Proceedings. Berlin (DE): Springer. 2009. p. 235-245. (Communications in Computer and Information Science). doi: 10.1007/978-3-642-03969-0_22

Adaptive electrical signal post-processing with varying representations in optical communication systems

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