End-to-end Learning for GMI Optimized Geometric Constellation Shape

Jones, Rasmus T., Yankov, Metodi P., Zibar, Darko

arXiv.org Machine Learning 

Autoencoder-based geometric shaping is proposed that includes optimizing bit mappings. Up to 0.2 bits/QAM symbol gain in GMI is achieved for a variety of data rates and in the presence of transceiver impairments. The gains can be harvested with standard binary FEC at no cost w.r.t.

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