no code implementations • 23 Nov 2018 • Qunbi Zhuge, Xiaobo Zeng, Huazhi Lun, Meng Cai, Xiaomin Liu, Weisheng Hu
In this paper, we present the application of machine learning (ML) in NLI modeling and monitoring.
no code implementations • 24 Nov 2020 • Xiaomin Liu, Huazhi Lun, Ruoxuan Gao, Meng Cai, Lilin Yi, Weisheng Hu, Qunbi Zhuge
For further improving the capacity and reliability of optical networks, a closed-loop autonomous architecture is preferred.
no code implementations • 13 Jun 2022 • Xiaomin Liu, Yuli Chen, Yihao Zhang, Yichen Liu, Lilin Yi, Weisheng Hu, Qunbi Zhuge
We propose a physics-informed EDFA gain model based on the active learning method.
no code implementations • 24 Jun 2022 • Yihao Zhang, Xiaomin Liu, Yichen Liu, Lilin Yi, Weisheng Hu, Qunbi Zhuge
Based on the physical features of Raman amplification, we propose a three-step modelling scheme based on neural networks (NN) and linear regression.
no code implementations • 13 Jul 2023 • Yichen Liu, Xiaomin Liu, Yihao Zhang, Meng Cai, Mengfan Fu, Xueying Zhong, Lilin Yi, Weisheng Hu, Qunbi Zhuge
To enable intelligent and self-driving optical networks, high-accuracy physical layer models are required.
no code implementations • 2 Apr 2024 • Qizhi Qiu, Xiaomin Liu, Yihao Zhang, Lilin Yi, Weisheng Hu, Qunbi Zhuge
We propose a heuristic-based optimization scheme for reliable optical amplifier reconfiguration process in ADON.