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Experimental Evaluation of Computational Complexity for Different Neural Network Equalizers in Optical Communications

Signal Processing 2021-09-21 v1 Machine Learning
Authors: Pedro J. Freire , Yevhenii Osadchuk , Antonio Napoli , Bernhard Spinnler , Wolfgang Schairer , Nelson Costa , Jaroslaw E. Prilepsky , Sergei K. Turitsyn
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Abstract

Addressing the neural network-based optical channel equalizers, we quantify the trade-off between their performance and complexity by carrying out the comparative analysis of several neural network architectures, presenting the results for TWC and SSMF set-ups.

Cite

@article{arxiv.2109.08711,
  title  = {Experimental Evaluation of Computational Complexity for Different Neural Network Equalizers in Optical Communications},
  author = {Pedro J. Freire and Yevhenii Osadchuk and Antonio Napoli and Bernhard Spinnler and Wolfgang Schairer and Nelson Costa and Jaroslaw E. Prilepsky and Sergei K. Turitsyn},
  journal= {arXiv preprint arXiv:2109.08711},
  year   = {2021}
}

Comments

ORAL presentation at the Asia Communications and Photonics Conference (ACP 2021)

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