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Deep Learning of Geometric Constellation Shaping including Fiber Nonlinearities
May 10, 2018 Β· Declared Dead Β· π European Conference on Optical Communication
"No code URL or promise found in abstract"
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Authors
Rasmus T. Jones, Tobias A. Eriksson, Metodi P. Yankov, Darko Zibar
arXiv ID
1805.03785
Category
cs.IT: Information Theory
Cross-listed
stat.ML
Citations
91
Venue
European Conference on Optical Communication
Last Checked
4 months ago
Abstract
A new geometric shaping method is proposed, leveraging unsupervised machine learning to optimize the constellation design. The learned constellation mitigates nonlinear effects with gains up to 0.13 bit/4D when trained with a simplified fiber channel model.
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