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A new geometric shaping method is proposed, leveraging unsupervised machinelearning to optimize the constellation design. The learned constellationmitigates nonlinear effects with gains up to 0.13 bit/4D when trained with asimplified fiber channel model.

Deep Learning of Geometric Constellation Shaping including Fiber Nonlinearities