Deep Neural Network-enabled Fast and Large-Scale QoT Estimation for Dynamic C plus L-Band Mesh Networks

被引：0
|
作者：
Zhang, Yao [1 ]
Song, Yuchen [1 ]
Shi, Yan [2 ]
Li, Jin [1 ]
Zhang, Chuanbiao [3 ]
Tang, Yu [3 ]
Zhang, Min [1 ]
Wang, Danshi [1 ]
机构：
[1] Beijing Univ Posts & Telecommun BUPT, State Key Lab Informat Photon & Opt Commun, Beijing, Peoples R China
[2] China Unicom Res Inst, Beijing, Peoples R China
[3] China United Network Commun Grp Co Ltd, Beijing, Peoples R China
来源：
2023 OPTICAL FIBER COMMUNICATIONS CONFERENCE AND EXHIBITION, OFC | 2023年
基金：
中国国家自然科学基金;
关键词：
D O I：
10.1364/OFC.2023.Tu2F.4
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
A fast and accurate QoT estimation scheme using deep neural network is proposed for dynamic C+L-band large-scale mesh networks. The calculation time is decreased dramatically and it is applied to measure the fiber broken case.
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页数：3
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