计算机科学
可靠性(半导体)
钥匙(锁)
复制品
物理层
数据传输
传输(电信)
图层(电子)
计算机体系结构
人机交互
电信
计算机网络
计算机安全
艺术
功率(物理)
化学
物理
有机化学
量子力学
视觉艺术
无线
作者
Qunbi Zhuge,Xiaomin Liu,Yihao Zhang,meng cai,Yichen Liu,Qizhi Qiu,Xueying Zhong,Jiaping Wu,Ruoxuan Gao,Lilin Yi,Weisheng Hu
摘要
To support the development of intelligent optical networks, accurate modeling of the physical layer is crucial. Digital twin (DT) modeling, which relies on continuous learning with real-time data, provides a new paradigm to build a virtual replica of the physical layer with a significant improvement in accuracy and reliability. In addition, DT models will be able to forecast future change by analyzing historical data. In this tutorial, we introduce and discuss three key technologies, including modeling, telemetry, and self-learning, to build a DT for optical networks. The principles and progress of these technologies on major impairments that affect the quality of transmission are presented, and a discussion on the remaining challenges and future research directions is provided.
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