Machine Learning for Optical Performance Monitoring from Directly Detected PDM-QAM Signals

J. Wass, Jakob Thrane, Molly Piels, Júlio César Medeiros Diniz, Rasmus Jones, Darko Zibar

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

    Abstract

    Supervised machine learning methods are applied and demonstrated experimentally for inband OSNR estimation and modulation format classification in optical communication systems. The proposed methods accurately evaluate coherent signals up to 64QAM using only intensity information.
    Original languageEnglish
    Title of host publicationProceedings of the 42nd European Conference and Exhibition on Optical Communications (ECOC 2016)
    Number of pages3
    PublisherVDE Verlag
    Publication date2016
    Pages1082-1084
    ISBN (Electronic)978-3-8007-4274-5
    Publication statusPublished - 2016
    Event42nd European Conference on Optical Communication - Dusseldorf, Germany
    Duration: 18 Sept 201622 Sept 2016

    Conference

    Conference42nd European Conference on Optical Communication
    Country/TerritoryGermany
    CityDusseldorf
    Period18/09/201622/09/2016

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