@inproceedings{5ed1129190de449fbf2c3ae307b4953e,
title = "A CGAN-aided Autoencoder Supporting Joint Geometric Probabilistic Shaping for Optical Fiber Communication System",
abstract = "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.",
keywords = "autoencoder, channel modeling, geometric shaping, probabilistic shaping",
author = "Yuzhe Li and Huan Chang and Qi Zhang and Xiangjun Xin and Ran Gao and Feng Tian and Qinghua Tian and Fu Wang and Zhipei Li",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 Asia Communications and Photonics Conference/2023 International Photonics and Optoelectronics Meetings, ACP/POEM 2023 ; Conference date: 04-11-2023 Through 07-11-2023",
year = "2023",
doi = "10.1109/ACP/POEM59049.2023.10369733",
language = "English",
series = "2023 Asia Communications and Photonics Conference/2023 International Photonics and Optoelectronics Meetings, ACP/POEM 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2023 Asia Communications and Photonics Conference/2023 International Photonics and Optoelectronics Meetings, ACP/POEM 2023",
address = "United States",
}