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Model-Based Machine Learning for Joint Digital Backpropagation and PMD Compensation

Signal Processing 2020-01-29 v1 Information Theory Machine Learning math.IT Machine Learning
Authors: Christian Häger , Henry D. Pfister , Rick M. Bütler , Gabriele Liga , Alex Alvarado
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Abstract

We propose a model-based machine-learning approach for polarization-multiplexed systems by parameterizing the split-step method for the Manakov-PMD equation. This approach performs hardware-friendly DBP and distributed PMD compensation with performance close to the PMD-free case.

Keywords

matrix optimization and algorithms

Cite

@article{arxiv.2001.09277,
  title  = {Model-Based Machine Learning for Joint Digital Backpropagation and PMD Compensation},
  author = {Christian Häger and Henry D. Pfister and Rick M. Bütler and Gabriele Liga and Alex Alvarado},
  journal= {arXiv preprint arXiv:2001.09277},
  year   = {2020}
}

Comments

3 pages, 2 figures

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