Intra and inter-channel nonlinearity compensation in WDM coherent optical OFDM using artificial neural network based nonlinear equalization

Elias Giacoumidis*, Sofien Mhatli, Jinlong Wei, Son T. Le, Ivan Aldaya, Marc F.C. Stephens, Mary E. McCarthy, Andrew D. Ellis, Nick J. Doran, Benjamin Eggleton

*Corresponding author for this work

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

Abstract

Nonlinear effects are experimentally tackled, for the first time, in WDM-CO-OFDM by an artificial neural network (ANN)-based equalizer at 3200 km. For the middle 20-Gb/s channel ANN outperforms to Volterra-based equalization by ~2-dB in Q-factor.

Original languageEnglish
Title of host publication2017 Optical Fiber Communications Conference and Exhibition (OFC 2017), proceedings
PublisherOptical Society of America
Number of pages3
ISBN (Print)978-1-943580-23-1
DOIs
Publication statusPublished - 23 Mar 2017
EventOptical Fiber Communication Conference, OFC 2017 - Los Angeles, United States
Duration: 19 Mar 201723 Mar 2017

Conference

ConferenceOptical Fiber Communication Conference, OFC 2017
CountryUnited States
CityLos Angeles
Period19/03/1723/03/17

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Bibliographical note

-Funding: Centre of Eccellence, Laureate Fellowship, EPSRC and FPESP.

Cite this

Giacoumidis, E., Mhatli, S., Wei, J., Le, S. T., Aldaya, I., Stephens, M. F. C., ... Eggleton, B. (2017). Intra and inter-channel nonlinearity compensation in WDM coherent optical OFDM using artificial neural network based nonlinear equalization. In 2017 Optical Fiber Communications Conference and Exhibition (OFC 2017), proceedings [paper Th2A.62] Optical Society of America. https://doi.org/10.1364/OFC.2017.Th2A.62