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
Publication date2021
Number of pages2
Publication statusPublished - 2021
Event2020 Conference on Lasers and Electro-Optics Pacific Rim - Sydney, Australia
Duration: 3 Aug 20205 Aug 2020
https://ieeexplore.ieee.org/xpl/conhome/9255848/proceeding

Conference

Conference2020 Conference on Lasers and Electro-Optics Pacific Rim
Country/TerritoryAustralia
CitySydney
Period03/08/202005/08/2020
Internet address

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