Maxwell-Boltzmann PMF Design Using Machine Learning for Reconfigurable Optical Fiber Networks

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Abstract

A neural network is used to predict the optimal Maxwell-Boltzmann probabilistic constellation shaping for a nonlinear channel with inline dispersion-compensation. The network uses only system parameters available at the transmitter and thus requires no feedback.
Original languageEnglish
Title of host publicationProceedings of 2020 CLEO Technical Conference
Number of pages2
PublisherOptical Society of America (OSA)
Publication statusAccepted/In press - 2021
Event2020 CLEO Technical Conference -
Duration: 9 May 202114 May 2021

Conference

Conference2020 CLEO Technical Conference
Period09/05/202114/05/2021

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