Power-aided probabilistic shaping parameter optimization for long-haul optical fiber transmission

被引：0
|
作者：
Zhao, Yi [1 ,2 ]
Zhang, Qi [1 ,2 ]
Li, Xinying [3 ]
Xin, Xiangjun [1 ,2 ,3 ]
Wang, Fu [1 ,2 ]
Gao, Ran [3 ]
Tian, Feng [1 ,2 ]
Tian, Qinghua [1 ,2 ]
Wang, Yongjun [1 ,2 ]
Yang, Leijing [1 ,2 ]
Wang, Xishuo [1 ,2 ]
Jiang, Jinkun [1 ,2 ]
机构：
[1] Beijing Univ Posts & Telecommun BUPT, Sch Elect Engn, Xitucheng Rd 10, Beijing 100876, Peoples R China
[2] Beijing Univ Posts & Telecommun BUPT, Beijing Key Lab Space Round Interconnect & Converg, Xitucheng Rd 10, Beijing 100876, Peoples R China
[3] Beijing Inst Technol, Adv Res Inst Multidisciplinary Sci, Beijing 100081, Peoples R China
来源：
APPLIED OPTICS | 2024年 / 63卷 / 27期
基金：
中国国家自然科学基金;
关键词：
SYSTEM;
D O I：
10.1364/AO.536890
中图分类号：
O43 [光学];
学科分类号：
070207 ; 0803 ;
摘要：
A power-aided probabilistic shaping (PS) parameter optimization scheme is proposed to localize the optimal transmitting setup and maximize the transmission capacity in long-haul optical fiber transmission. Using a neural network and genetic algorithm (NNGA), the proposed scheme can select the optimal transmission parameter set, including the launching optical power (LOP) and three PS characteristics. We built a testbed using MATLAB and VPI to validate the proposed scheme. The proposed scheme was demonstrated in a dual-polarization coherent transmission system. The results show that the proposed scheme improves the generalized mutual information (GMI) by 0.3035 bits/symbol/pol and normalized GMI by 0.1022 in a 1000 km G.654E fiber transmission at 420-Gbit/s, compared to a traditional MB-based PS technique. The signal-to-noise ratio (SNR) achieves a gain of 1.003 dB, which validates the outperformance of the proposed scheme. (c) 2024 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.
引用
收藏
页码：7301 / 7310
页数：10
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