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Machine learning for fiber nonlinearity mitigation in long-haul coherent optical transmission systems
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Liu, Yifan, Yang, Bowei and Xu, Tianhua (2020) Machine learning for fiber nonlinearity mitigation in long-haul coherent optical transmission systems. In: 11th International Conference on Advanced Infocomm Technology (ICAIT), Jinan, China, 18-20 Oct 2019. Published in: IEEE International Conference on Advanced Infocomm Technology (ICAIT) ISBN 9781728147789. doi:10.1109/ICAIT.2019.8935891
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WRAP-machine-learning-fiber-nonlinearity-mitigation-long-haul-coherent-optical-transmission-systems-Xu-2020.pdf - Accepted Version - Requires a PDF viewer. Download (2639Kb) | Preview |
Official URL: http://doi.org/10.1109/ICAIT.2019.8935891
Abstract
Fiber nonlinearities from Kerr effect are considered as major constraints for enhancing the transmission capacity in current optical transmission systems. Digital nonlinearity compensation techniques such as digital backpropagation can perform well but require high computing resources. Machine learning can provide a low complexity capability especially for high-dimensional classification problems. Recently several supervised and unsupervised machine learning techniques have been investigated in the field of fiber nonlinearity mitigation. This paper offers a brief review of the principles, performance and complexity of these machine learning approaches in the application of nonlinearity mitigation.
Item Type: | Conference Item (Paper) | |||||||||
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Subjects: | Q Science > Q Science (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering |
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Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering | |||||||||
Library of Congress Subject Headings (LCSH): | Machine learning , Optical fiber communication, Neural networks (Computer science) | |||||||||
Journal or Publication Title: | IEEE International Conference on Advanced Infocomm Technology (ICAIT) | |||||||||
Publisher: | IEEE | |||||||||
ISBN: | 9781728147789 | |||||||||
Official Date: | 19 December 2020 | |||||||||
Dates: |
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DOI: | 10.1109/ICAIT.2019.8935891 | |||||||||
Status: | Peer Reviewed | |||||||||
Publication Status: | Published | |||||||||
Reuse Statement (publisher, data, author rights): | © 2019 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: | 10 January 2020 | |||||||||
Date of first compliant Open Access: | 20 January 2020 | |||||||||
RIOXX Funder/Project Grant: |
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Conference Paper Type: | Paper | |||||||||
Title of Event: | 11th International Conference on Advanced Infocomm Technology (ICAIT) | |||||||||
Type of Event: | Conference | |||||||||
Location of Event: | Jinan, China | |||||||||
Date(s) of Event: | 18-20 Oct 2019 | |||||||||
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