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cs.ITOct 17, 2017
1
citations (OpenAlex)
authors
  • Christian Häger
  • Henry D. Pfister
institutions
  • Chalmers University of Technology
  • Duke University
arXiv abstractPDF
paper

Nonlinear Interference Mitigation via Deep Neural Networks

arXiv:1710.06234

Abstract

A neural-network-based approach is presented to efficiently implement digital backpropagation (DBP). For a 32x100 km fiber-optic link, the resulting "learned" DBP significantly reduces the complexity compared to conventional DBP implementations.

arXiv comment3 pages, 2 figures

Cited by in corpus (1)

  • Wiener-Hammerstein model and its learning for nonlinear digital pre-distortion of optical transmitters
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