A CGAN-aided Autoencoder Supporting Joint Geometric Probabilistic Shaping for Optical Fiber Communication System

An autoencoder supporting joint geometric and probabilistic shaping is proposed that can achieve global optimization of optical fiber communication systems with aid of conditional generative adversarial network. Result shows that bit error rate is reduced by 12% compared to a probabilistic shaping-only signal with the same entropy.