Building a digital twin for intelligent optical networks [Invited Tutorial]

Author:

Zhuge Qunbi1ORCID,Liu Xiaomin,Zhang Yihao,Cai Meng,Liu Yichen,Qiu Qizhi,Zhong Xueying,Wu Jiaping,Gao Ruoxuan,Yi LilinORCID,Hu Weisheng1ORCID

Affiliation:

1. Peng Cheng Laboratory

Abstract

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.

Funder

Shanghai Pilot Program for Basic Research-Shanghai Jiao Tong University

National Natural Science Foundation of China

Publisher

Optica Publishing Group

Subject

Computer Networks and Communications

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