GAN Based Soft Failure Detection and Identification for Long-haul Coherent Transmission Systems

Huazhi Lun; Xiaomin Liu; Meng Cai; Yiwen Wu; Mengfan Fu; Lilin Yi; Weisheng Hu; Qunbi Zhuge

doi:10.1364/OFC.2021.Th4J.2

Optical Fiber Communication Conference (OFC) 2021
OSA Technical Digest (Optica Publishing Group, 2021),
paper Th4J.2
•https://doi.org/10.1364/OFC.2021.Th4J.2

GAN Based Soft Failure Detection and Identification for Long-haul Coherent Transmission Systems

Huazhi Lun, Xiaomin Liu, Meng Cai, Yiwen Wu, Mengfan Fu, Lilin Yi, Weisheng Hu, and Qunbi Zhuge

Optical Fiber Communication Conference 2021

Washington, DC United States
6–11 June 2021
ISBN: 978-1-943580-86-6

From the session
Machine Learning for Failure Management and Performance Estimation / Prediction (Th4J)

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H. Lun, X. Liu, M. Cai, Y. Wu, M. Fu, L. Yi, W. Hu, and Q. Zhuge, "GAN Based Soft Failure Detection and Identification for Long-haul Coherent Transmission Systems," in Optical Fiber Communication Conference (OFC) 2021, P. Dong, J. Kani, C. Xie, R. Casellas, C. Cole, and M. Li, eds., OSA Technical Digest (Optica Publishing Group, 2021), paper Th4J.2.

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Abstract

We propose a GAN based soft failure detection and identification algorithm. For the training, the detection and identification only need normal samples and very few soft failure samples, respectively. 95% accuracy is achieved in experiment.

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