On the Generalization of Machine-Learning-aided QoT Estimation in Optical Networks
- Resource Type
- Conference
- Authors
- Gao, Hanyu; Zhang, Liang; Zhang, Bin; Chen, Xiaoliang; Li, Zhaohui
- Source
- 2023 32nd Wireless and Optical Communications Conference (WOCC) Wireless and Optical Communications Conference (WOCC), 2023 32nd. :1-4 May, 2023
- Subject
- Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Fields, Waves and Electromagnetics
Photonics and Electrooptics
Signal Processing and Analysis
Measurement
Wireless communication
Estimation
Machine learning
Optical fiber networks
- Language
- ISSN
- 2379-1276
This paper presents a composable machine learning method for generalizing the quality-of-transmission (QoT) metric estimation in optical networks. The composable machine learning approach characterizes this metric for lightpaths of arbitrary lengths by compositions of launch, propagation and readout modules. Results verify the feasibility of the design and show its successful application in facilitating autonomous lightpath provisioning.