@inproceedings{9d9a4825af34446ca91efc80e7c219da,
title = "The research of probabilistic shaping signal transmission scheme based on neural network LLR calculation",
abstract = "In order to improve the decoding accuracy and the BER performance of probabilistic shaping optical fiber transmission system, a scheme of probabilistic shaping signal transmission utilizing neural network based LLR calculation is proposed in this paper. Compared with the traditional transmission scheme based on the maximum logarithmic approximation LLR (ALLR) calculation, the mean square error ratio of LLR between the proposed transmission scheme and the scheme based on the exact LLR (ELLR) is reduced by about 100 times. And the BER of the system is improved by at least 0.1dB. In addition, the computational complexity of the proposed scheme is significantly lower than that of the transmission scheme based on the exact LLR computation method (ELLR).",
keywords = "Decode, High order modulation, LDPC, Optical communications, neural networks",
author = "Pandi Pang and Huan Chang and Qi Zhang and Xiangjun Xin and Ran Gao and Feng Tian and Qinghua Tian and Yongjun Wang and Dong Guo",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 19th International Conference on Optical Communications and Networks, ICOCN 2021 ; Conference date: 23-08-2021 Through 27-08-2021",
year = "2021",
doi = "10.1109/ICOCN53177.2021.9563893",
language = "English",
series = "2021 19th International Conference on Optical Communications and Networks, ICOCN 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2021 19th International Conference on Optical Communications and Networks, ICOCN 2021",
address = "United States",
}