Nonlinear Impairment Compensation Using Neural Networks

  • Shinsuke Fujisawa
  • , Fatih Yaman
  • , Hussam G. Batshon
  • , Massaki Tanio
  • , Naoto Ishii
  • , Chaoran Huang
  • , Thomas Ferreira De Lima
  • , Yoshihisa Inada
  • , Paul R. Prucnal
  • , Norifumi Kamiya
  • , Ting Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

Neural networks are attractive for nonlinear impairment compensation applications in communication systems. In this paper, several approaches to reduce computational complexity of the neural network-based algorithms are presented.

Original languageEnglish (US)
Title of host publication2021 Optical Fiber Communications Conference and Exhibition, OFC 2021 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781943580866
StatePublished - Jun 2021
Event2021 Optical Fiber Communications Conference and Exhibition, OFC 2021 - San Francisco, United States
Duration: Jun 6 2021Jun 11 2021

Publication series

Name2021 Optical Fiber Communications Conference and Exhibition, OFC 2021 - Proceedings

Conference

Conference2021 Optical Fiber Communications Conference and Exhibition, OFC 2021
Country/TerritoryUnited States
CitySan Francisco
Period6/6/216/11/21

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Hardware and Architecture
  • Signal Processing
  • Electronic, Optical and Magnetic Materials
  • Instrumentation
  • Atomic and Molecular Physics, and Optics

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