Experimental comparison of artificial neural network and volterra based nonlinear equalization for CO-OFDM

Elias Giacoumidis, Son T. Le, Ivan Aldaya, Jinlong Wei, Mary McCarthy, Nick Doran, Benjamin Eggleton

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

Abstract

A novel artificial neural network (ANN)-based nonlinear equalizer (NLE) of low complexity is demonstrated for 40-Gb/s CO-OFDM at 2000 km, revealing ∼1.5 dB enhancement in Q-factor compared to inverse Volterra-series transfer function based NLE.

Original languageEnglish
Title of host publicationOptical Fiber Communication Conference 2016
PublisherOptical Society of America
ISBN (Print)978-1-943580-07-1
DOIs
Publication statusPublished - 22 Mar 2016
EventOptical Fiber Communication Conference 2016 - Anaheim, CA, United States
Duration: 20 Mar 201622 Mar 2016

Conference

ConferenceOptical Fiber Communication Conference 2016
CountryUnited States
CityAnaheim, CA
Period20/03/1622/03/16

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Bibliographical note

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Cite this

Giacoumidis, E., Le, S. T., Aldaya, I., Wei, J., McCarthy, M., Doran, N., & Eggleton, B. (2016). Experimental comparison of artificial neural network and volterra based nonlinear equalization for CO-OFDM. In Optical Fiber Communication Conference 2016 [paper W3A.4] Optical Society of America. https://doi.org/10.1364/OFC.2016.W3A.4