Deep Learning of Geometric Constellation Shaping including Fiber Nonlinearities

2018/05/10 by Jones, Rasmus T., Eriksson, Tobias A., Yankov, Metodi P. +1
#FOS: Computer and information sciences #Information Theory (cs.IT) #Machine Learning (stat.ML)

paper · doi:10.48550/arxiv.1805.03785

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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