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 publication2020 Optical Fiber Communications Conference and Exhibition, OFC 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781943580712
StatePublished - Mar 2020
Externally publishedYes
Event2020 Optical Fiber Communications Conference and Exhibition, OFC 2020 - San Diego, United States
Duration: 8 Mar 202012 Mar 2020

Publication series

Name2020 Optical Fiber Communications Conference and Exhibition, OFC 2020 - Proceedings

Conference

Conference2020 Optical Fiber Communications Conference and Exhibition, OFC 2020
Country/TerritoryUnited States
CitySan Diego
Period8/03/2012/03/20

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