A QoT Estimation Method using EGN-assisted Machine Learning for Network Planning Applications

被引：3
|
作者：
Mueller, Jasper [1 ]
Patri, Sai Kireet [1 ,2 ]
Fehenberger, Tobias [1 ]
Mas-Machuca, Carmen [2 ]
Griesser, Helmut [1 ]
Elbers, Joerg-Peter [1 ]
机构：
[1] ADVA, Fraunhoferstr 9a, D-82152 Martinsried, Germany
[2] Tech Univ Munich, Chair Commun Networks, Arcisstr 21, Munich, Germany
来源：
2021 EUROPEAN CONFERENCE ON OPTICAL COMMUNICATION (ECOC) | 2021年
关键词：
PREDICTION; QUALITY;
D O I：
10.1109/ECOC52684.2021.9606064
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
An ML model based on precomputed per-channel SCI is proposed. Due to its superior accuracy over closed-form GN, an average SNR gain of 1.1 dB in an end-to-end link optimization and a 40% reduction in required lightpaths to meet traffic requests in a network planning scenario are shown.
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收藏
页数：4
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