Load Aware Raman Gain Profile Prediction in Dynamic Multi-Band Optical Networks

A. Margareth Rosa Brusin, Uiara C. De Moura, Andrea D'Amico, Vittorio Curri, Darko Zibar, Andrea Carena

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

    Abstract

    We introduce a load aware machine learning method for prediction of Raman gain profiles. It enables future network controllers to manage seamless upgrades toward multi-band optical line systems with dynamic loads.

    Original languageEnglish
    Title of host publicationProceedings of 2020 Optical Fiber Communications Conference and Exhibition
    Number of pages3
    PublisherIEEE
    Publication dateMar 2020
    Article numberT4B.3
    ISBN (Electronic)9781943580712
    DOIs
    Publication statusPublished - Mar 2020
    EventOptical Fiber Communication Conference 2020 - San Diego Convention Center, San Diego, United States
    Duration: 8 Mar 202012 Mar 2020

    Conference

    ConferenceOptical Fiber Communication Conference 2020
    LocationSan Diego Convention Center
    Country/TerritoryUnited States
    CitySan Diego
    Period08/03/202012/03/2020
    SponsorAcacia Communications Inc., AC Photonics, Inc., Alibaba Group, Ciena Corporation, Cisco Systems

    Bibliographical note

    From the session: Machine Learning for Fiber Amplifier and Sensors (T4B)

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