Deep Learning of Geometric Constellation Shaping including Fiber Nonlinearities
Jones, Rasmus T., Eriksson, Tobias A., Yankov, Metodi P., Zibar, Darko
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.
May-9-2018