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Design Optimisation of Power-Efficient Submarine Line through Machine Learning

Signal Processing 2020-02-26 v1
Authors: Maria Ionescu , Amirhossein Ghazisaeidi , Jérémie Renaudier , Pascal Pecci , Olivier Courtois
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Abstract

An optimised subsea system design for energy-efficient SDM operation is demonstrated using machine learning. The removal of gain-flattening filters employed in submarine optical amplifiers can result in capacity gains at no additional overall repeater cost.

Keywords

machine learning matrix optimization and algorithms wireless communication

Cite

@article{arxiv.2002.11037,
  title  = {Design Optimisation of Power-Efficient Submarine Line through Machine Learning},
  author = {Maria Ionescu and Amirhossein Ghazisaeidi and Jérémie Renaudier and Pascal Pecci and Olivier Courtois},
  journal= {arXiv preprint arXiv:2002.11037},
  year   = {2020}
}

Comments

CLEO 2020

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