A Complex-valued Neural Network for Fiber Nonlinearity Mitigation

Pinjing He, Aiying Yang*, Peng Guo, Yaojun Qiao, Xiangjun Xin

*Corresponding author for this work

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

2 Citations (Scopus)

Abstract

A complex-valued triplet-input neural network for fiber nonlinearity compensation is proposed. Numerical results show 0.2 dB Q factor improvement and 25% computational complexity reduction, compared with the real-valued triplet-input neural network.

Original languageEnglish
Title of host publication2021 Opto-Electronics and Communications Conference, OECC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781943580927
Publication statusPublished - 2021
Event2021 Opto-Electronics and Communications Conference, OECC 2021 - Hong Kong, Hong Kong
Duration: 3 Jul 20217 Jul 2021

Publication series

Name2021 Opto-Electronics and Communications Conference, OECC 2021

Conference

Conference2021 Opto-Electronics and Communications Conference, OECC 2021
Country/TerritoryHong Kong
CityHong Kong
Period3/07/217/07/21

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