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End-to-end Learning of a Constellation Shape Robust to Variations in SNR and Laser Linewidth

Signal Processing 2022-04-26 v1
Authors: Ognjen Jovanovic , Metodi P. Yankov , Francesco Da Ros , Darko Zibar
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Abstract

We propose an autoencoder-based geometric shaping that learns a constellation robust to SNR and laser linewidth estimation errors. This constellation maintains shaping gain in mutual information (up to 0.3 bits/symbol) with respect to QAM over various SNR and laser linewidth values.

Keywords

autoencoder geometric shaping constellation design snr robustness laser linewidth mutual information qam

Cite

@article{arxiv.2106.00431,
  title  = {End-to-end Learning of a Constellation Shape Robust to Variations in SNR and Laser Linewidth},
  author = {Ognjen Jovanovic and Metodi P. Yankov and Francesco Da Ros and Darko Zibar},
  journal= {arXiv preprint arXiv:2106.00431},
  year   = {2022}
}

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