Experimental comparisons between machine learning and analytical models for QoT estimations in WDM systems

Qirui Fan, Jianing Lu, Gai Zhou, Derek Zeng, Changjian Guo, Linyue Lu, Jianqiang Li, Chongjin Xie, Chao Lu, Faisal Nadeem Khan, Alan Pak Tao Lau

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

We experimentally compare QoT estimations for WDM systems using Machine Learning(ML) and GN-based analytical models. ML estimates the side channels with better accuracy but is temporally less stable and less generalizable to different link configurations.

Original languageEnglish
Title of host publicationOptical Fiber Communication Conference, OFC 2020
PublisherOSA - The Optical Society
ISBN (Print)9781943580712
Publication statusPublished - Mar 2020
EventOptical Fiber Communication Conference, OFC 2020 - San Diego, United States
Duration: 8 Mar 201712 Mar 2017

Publication series

NameOptics InfoBase Conference Papers
VolumePart F174-OFC 2020

Conference

ConferenceOptical Fiber Communication Conference, OFC 2020
Country/TerritoryUnited States
CitySan Diego
Period8/03/1712/03/17

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Mechanics of Materials

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