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Conferences > CLEO_SI > 2022 > SW4E > SW4E.5

Model-Based Deep Learning of Joint Probabilistic and Geometric Shaping for Optical Communication

Vladislav Neskorniuk, Andrea Carnio, Domenico Marsella, Sergei K. Turitsyn, Jaroslaw E. Prilepsky, and Vahid Aref

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Abstract

Autoencoder-based deep learning is applied to jointly optimize geometric and probabilistic constellation shaping for optical coherent communication. The optimized constellation shaping outperforms the 256 QAM Maxwell-Boltzmann probabilistic distribution with extra 0.05 bits/4D-symbol mutual information for 64 GBd transmission over 170 km SMF link.

© 2022 The Author(s)

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