Optical fiber anomaly detection through SRS-induced spectral tilt in C+L-band transmission systems
Fiber-optic communication systems serve as the backbone of modern data communication networks, with increasing demands on their reliability and robustness in various emerging applications. A key challenge in ensuring reliable fiber-optic transmission lies in addressing fiber anomalies, which can cause signal degradation, service disruptions, and even system failures. However, the current anomaly detection method is too complex to be implemented in deployed networks or consumes too much time during detection. This paper proposes a simple and effective fiber anomaly detection method for C+L-band fiber-optic communication systems, leveraging the spectral tilt induced by the stimulated Raman scattering (SRS) effect. The method reconstructs the spectral tilt along an anomalous fiber link by analyzing the input and output power profile, easily obtainable from optical channel monitors (OCMs), enabling anomaly localization and loss quantification through forward and backward spectral tilt comparison. The performance and robustness of the proposed method are studied and discussed in actual scenarios such as erbium-doped fiber amplifier gain fluctuations, OCM measurement errors, parameter inaccuracies, and modeling inaccuracies. In addition to being able to detect a single anomaly, the process of using the proposed method to achieve multiple anomaly detection links is also discussed according to the chronological order of anomalies. Experimental validation on a multi-span C+L-band transmission system achieves a maximum localization error of 2.06 km and a maximum loss estimation error of 0.14 dB within 2 s. This work underscores the potential of exploiting inherent physical phenomena like SRS for fast anomaly detection in deployed optical networks.
Authors
- Danshi Wang (ORCID: https://orcid.org/0000-0001-9815-4013)
- Jin Li (ORCID: https://orcid.org/0000-0003-1236-4613)
- Meixia Fu (ORCID: https://orcid.org/0000-0001-9725-3116)
- Shengnan Li (ORCID: https://orcid.org/0000-0001-9060-7700)
- Cheng Ju (ORCID: https://orcid.org/0000-0002-2282-6917)
- Xiao Luo (ORCID: https://orcid.org/0000-0001-8764-1334)
- Zihao Cui (ORCID: https://orcid.org/0000-0001-5243-284X)
- Yuchen Song (ORCID: https://orcid.org/0000-0003-3820-4386)
- Jingmao Li
Institutions
- Qingdao University (CN)
- University of Science and Technology Beijing (CN)
Publication Details
- Journal
- Journal of Optical Communications and Networking
- Published
- 2025-05-20
- DOI
- https://doi.org/10.1364/jocn.566245
- Citations
- 2
- Primary Topic
- Advanced Fiber Optic Sensors
- Type
- article
- Field-Weighted Citation Impact
- 1.46