16-QAM probabilistic constellation shaping by learning the distribution of transmitted symbols from the training sequence

A. Fallahpour, F. Alishahi, A. Minoofar, K. Zou, A. Almaiman, P. Liao, H. Zhou, M. Tur, A. E. Willner

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A technique for probabilistic constellation shaping based on distribution learning from a training sequence is investigated. In this approach, the probability distribution is optimized such that it can maximize the mutual information. The effectiveness of this approach is verified by shaping 10 Gbaud 16QAM in simulation and experiment.

Original languageEnglish
Title of host publicationOptical Fiber Communication Conference, OFC 2020
PublisherOSA - The Optical Society
ISBN (Print)9781943580712
StatePublished - 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

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