paper

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

arXiv:1907.08535

Abstract

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. conventional BICM.

submitted to ECOC 2019

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