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Intra-channel nonlinearity mitigation in optical fiber transmission systems using perturbation-based neural network

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Ding, Jiazheng, Liu, Tiegen, Xu, Tongyang, Hu, Wenxiu, Popov, Sergei, Leeson, Mark S., Zhao, Jian and Xu, Tianhua (2022) Intra-channel nonlinearity mitigation in optical fiber transmission systems using perturbation-based neural network. IEEE Journal of Lightwave Technology, 40 (21). pp. 7106-7116. doi:10.1109/JLT.2022.3200827 ISSN 0733-8724.

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Official URL: https://doi.org/10.1109/JLT.2022.3200827

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Abstract

In this work, a perturbation-based neural network (P-NN) scheme with an embedded bidirectional long short-term memory (biLSTM) layer is investigated to compensate for the Kerr fiber nonlinearity in optical fiber communication systems. Numerical simulations have been carried out in a 32-Gbaud dual-polarization 16-ary quadrature amplitude modulation (DP-16QAM) transmission system. It is shown that this P-NN equalizer can achieve signal-to-noise ratio improvements of ~1.37 dB and ~0.80 dB, compared to the use of a linear equalizer and a single step per span (StPS) digital back propagation (DBP) scheme, respectively. The P-NN equalizer requires lower computational complexity and can effectively compensate for intra-channel nonlinearity. Meanwhile, the performance of P-NN is more robust to the distortion caused by equalization enhanced phase noise (EEPN). Furthermore, it is also found that there exists a tradeoff between the choice of modulation format and the nonlinear equalization schemes for a given transmission distance.

Item Type: Journal Article
Subjects: Q Science > QA Mathematics
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Science, Engineering and Medicine > Engineering > Engineering
Library of Congress Subject Headings (LCSH): Optical fiber communication, Neural networks (Computer science), Equalizers (Electronics)
Journal or Publication Title: IEEE Journal of Lightwave Technology
Publisher: IEEE
ISSN: 0733-8724
Official Date: 22 August 2022
Dates:
DateEvent
22 August 2022Published
18 August 2022Accepted
Volume: 40
Number: 21
Page Range: pp. 7106-7116
DOI: 10.1109/JLT.2022.3200827
Status: Peer Reviewed
Publication Status: Published
Reuse Statement (publisher, data, author rights): © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Access rights to Published version: Restricted or Subscription Access
Date of first compliant deposit: 22 August 2022
Date of first compliant Open Access: 25 August 2022
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
101008280[ERC] Horizon 2020 Framework Programmehttp://dx.doi.org/10.13039/100010661
EP/S028455/1[EPSRC] Engineering and Physical Sciences Research Councilhttp://dx.doi.org/10.13039/501100000266
2019-05197Vetenskapsrådethttp://dx.doi.org/10.13039/501100004359
UNSPECIFIEDRISE SKhttps://therisefund.com/
2022YFE0202100Key Technologies Research and Development Programhttp://dx.doi.org/10.13039/501100012165

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