Fiber nonlinearity-induced penalty reduction in CO-OFDM by ANN-based nonlinear equalization

Elias Giacoumidis; Son T. Le; Mohammad Ghanbarisabagh; Mary McCarthy; Ivan Aldaya; Sofien Mhatli; Mutsam A. Jarajreh; Paul A. Haigh; Nick J. Doran; Andrew D. Ellis; Benjamin J. Eggleton

doi:10.1364/OL.40.005113

Fiber nonlinearity-induced penalty reduction in CO-OFDM by ANN-based nonlinear equalization

Elias Giacoumidis^*
, Son T. Le
, Mohammad Ghanbarisabagh
, Mary McCarthy
, Ivan Aldaya
, Sofien Mhatli
, Mutsam A. Jarajreh
, Paul A. Haigh
, Nick J. Doran
, Andrew D. Ellis
, Benjamin J. Eggleton

^*Corresponding author for this work

Aston Institute of Photonic Technologies (AiPT)

Macquarie University
University of Sydney
Islamic Azad University
Instituto Tecnologico y de Estudios Superiores de Monterrey
EPT Université de Carthage
Fahad Bin Sultan University
University of Bristol

Research output: Contribution to journal › Article › peer-review

87 Citations (SciVal)

Abstract

We experimentally demonstrate ∼2 dB quality (Q)-factor enhancement in terms of fiber nonlinearity compensation of 40 Gb/s 16 quadrature amplitude modulation coherent optical orthogonal frequency-division multiplexing at 2000 km, using a nonlinear equalizer (NLE) based on artificial neural networks (ANN). Nonlinearity alleviation depends on escalation of the ANN training overhead and the signal bit rate, reporting ∼4 dB Q-factor enhancement at 70 Gb/s, whereas a reduction of the number of ANN neurons annihilates the NLE performance. An enhanced performance by up to ∼2 dB in Q-factor compared to the inverse Volterra-series transfer function NLE leads to a breakthrough in the efficiency of ANN.

Original language	English
Pages (from-to)	5113-5116
Number of pages	4
Journal	Optics Letters
Volume	40
Issue number	21
Early online date	30 Sept 2015
DOIs	https://doi.org/10.1364/OL.40.005113
Publication status	Published - 30 Oct 2015

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title = "Fiber nonlinearity-induced penalty reduction in CO-OFDM by ANN-based nonlinear equalization",

abstract = "We experimentally demonstrate ∼2 dB quality (Q)-factor enhancement in terms of fiber nonlinearity compensation of 40 Gb/s 16 quadrature amplitude modulation coherent optical orthogonal frequency-division multiplexing at 2000 km, using a nonlinear equalizer (NLE) based on artificial neural networks (ANN). Nonlinearity alleviation depends on escalation of the ANN training overhead and the signal bit rate, reporting ∼4 dB Q-factor enhancement at 70 Gb/s, whereas a reduction of the number of ANN neurons annihilates the NLE performance. An enhanced performance by up to ∼2 dB in Q-factor compared to the inverse Volterra-series transfer function NLE leads to a breakthrough in the efficiency of ANN.",

author = "Elias Giacoumidis and Le, \{Son T.\} and Mohammad Ghanbarisabagh and Mary McCarthy and Ivan Aldaya and Sofien Mhatli and Jarajreh, \{Mutsam A.\} and Haigh, \{Paul A.\} and Doran, \{Nick J.\} and Ellis, \{Andrew D.\} and Eggleton, \{Benjamin J.\}",

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doi = "10.1364/OL.40.005113",

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T1 - Fiber nonlinearity-induced penalty reduction in CO-OFDM by ANN-based nonlinear equalization

AU - Giacoumidis, Elias

AU - Le, Son T.

AU - Ghanbarisabagh, Mohammad

AU - McCarthy, Mary

AU - Aldaya, Ivan

AU - Mhatli, Sofien

AU - Jarajreh, Mutsam A.

AU - Haigh, Paul A.

AU - Doran, Nick J.

AU - Ellis, Andrew D.

AU - Eggleton, Benjamin J.

PY - 2015/10/30

Y1 - 2015/10/30

N2 - We experimentally demonstrate ∼2 dB quality (Q)-factor enhancement in terms of fiber nonlinearity compensation of 40 Gb/s 16 quadrature amplitude modulation coherent optical orthogonal frequency-division multiplexing at 2000 km, using a nonlinear equalizer (NLE) based on artificial neural networks (ANN). Nonlinearity alleviation depends on escalation of the ANN training overhead and the signal bit rate, reporting ∼4 dB Q-factor enhancement at 70 Gb/s, whereas a reduction of the number of ANN neurons annihilates the NLE performance. An enhanced performance by up to ∼2 dB in Q-factor compared to the inverse Volterra-series transfer function NLE leads to a breakthrough in the efficiency of ANN.

AB - We experimentally demonstrate ∼2 dB quality (Q)-factor enhancement in terms of fiber nonlinearity compensation of 40 Gb/s 16 quadrature amplitude modulation coherent optical orthogonal frequency-division multiplexing at 2000 km, using a nonlinear equalizer (NLE) based on artificial neural networks (ANN). Nonlinearity alleviation depends on escalation of the ANN training overhead and the signal bit rate, reporting ∼4 dB Q-factor enhancement at 70 Gb/s, whereas a reduction of the number of ANN neurons annihilates the NLE performance. An enhanced performance by up to ∼2 dB in Q-factor compared to the inverse Volterra-series transfer function NLE leads to a breakthrough in the efficiency of ANN.

UR - https://www.scopus.com/pages/publications/84957539304

U2 - 10.1364/OL.40.005113

DO - 10.1364/OL.40.005113

M3 - Article

AN - SCOPUS:84957539304

SN - 0146-9592

VL - 40

SP - 5113

EP - 5116

JO - Optics Letters

JF - Optics Letters

IS - 21

ER -

Fiber nonlinearity-induced penalty reduction in CO-OFDM by ANN-based nonlinear equalization

Abstract

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