The Journal of China Universities of Posts and Telecommunications ›› 2022, Vol. 29 ›› Issue (6): 3-17.doi: 10.19682/j.cnki.1005-8885.2022.1024

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Artificial intelligence for optical transport networks: architecture, application and challenges

Li Yajie, Zhang Jie   

  1. State Key Laboratory of Information Photonics and Optical Communications, Beijing University of Posts and Telecommunications, Beijing 100876, China

  • Received:2022-10-21 Revised:2022-11-08 Online:2022-12-30 Published:2022-12-30
  • Supported by:
    This work was supported by the National Natural Science Foundation of China (61901053, 61831003, 62021005), the
    Project of Jiangsu Engineering Research Center of Novel Optical Fiber Technology and Communication Network, Soochow
    University (SDGC2117), the Fundamental Research Funds for the Central Universities (2021RC12).


Optical network plays an important role in telecommunication networks, which supports high-capacity and long-distance transmission of Internet traffic. However, as the scaling and evolving of optical networks, it faces great challenges in terms of network operation, optimization and maintenance. Artificial intelligence ( AI ) has been proved to have superiority on addressing complex problems, by mimicking cognitive skills similar with human mind. In this paper, we provide a comprehensive investigation of AI applications in optical transport network. First, we give a general AI-based control architecture for optical transport networks. Then, we discuss several typical applications of AI model and algorithms in optical networks. Different use cases are considered, including network planning, quality of transmission ( QoT ) estimation, network reconfiguration, traffic prediction, failure management and so on. In addition, we also present some potential technical challenges for AI application in
optical network for the next years.

Key words: artificial intelligence (AI), optical network, control architecture, typical application

CLC Number: