Field Trial of Failure Localization in a Backbone Optical Network

Delezoide, Camille; Ramantanis, Pétros; Gifre, Lluis; Boitier, Fabien; Layec, Patricia

doi:10.1109/ecoc52684.2021.9606152

Cited by 5 publications

(2 citation statements)

References 17 publications

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“…[9] . Note that this problem is different from the problem of choosing a set of ligthpath that allows performing fault localization on any link of the network (as in, e.g., [10], [11] ), that may involve selecting multiple LPs traversing the same link. The OMP algorithm is illustrated in Fig.…”

Section: Resource Allocation Problemmentioning

confidence: 99%

Cost and power-consumption analysis for power profile monitoring in optical networks

Zhang,

Layec,

Morea

et al. 2023

IET Conf. Proc.

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Section: Resource Allocation Problemmentioning

confidence: 99%

Cost and power-consumption analysis for power profile monitoring in optical networks

Zhang,

Layec,

Morea

et al. 2023

IET Conf. Proc.

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“…If available, components can also be characterized in the lab before deployment by fitting a physical model or learning a model from data, as shown for erbium-doped fiber amplifiers (EDFAs) by [25,[31][32][33][34][35] and also in our previous work [36,37]. For operational networks, methods leveraging monitoring data have been proposed in [38,39]. With an accurate QoT estimate in place, techniques to optimize the channel input powers to a link are of interest.…”

Section: Introductionmentioning

confidence: 99%

Spectral power profile optimization of a field-deployed wavelength-division multiplexing network enabled by remote EDFA modeling

Jones¹,

Bottrill²,

Taengnoi³

et al. 2023

J. Opt. Commun. Netw.

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We propose a technique for modeling erbium-doped fiber amplifiers (EDFAs) in optical fiber networks, where the amplifier unit is located at a distant node outside the laboratory. We collect data on an optical point-to-point link with the amplifier as the only amplification stage. Different amplifier operating points are modeled using probe signals and by adjusting the settings of the amplifier through a control network. The data are used to train a machine learning algorithm integrated within a physical EDFA model. The obtained mathematical model for the amplifier is used to model all amplifiers of a network and links with multiple amplification stages. To confirm the modeling accuracy, we thereafter predict and optimize launch power profiles of two selected links in the network of 439.4 km and 592.4 km lengths. Maximum/average channel optical signal-to-noise ratio prediction errors of 1.41/0.68 dB and 1.62/0.83 dB are achieved for the two multi-span systems, respectively, using the EDFA model trained on the single span system with margin-optimized launch power profiles. Up to 2.2 dB of margin improvements are obtained with respect to unoptimized transmission.

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Cluster-Based Method for Eavesdropping Identification and Localization in Optical Links

Song,

Lin,

Sgambelluri

et al. 2023

2023 Asia Communications and Photonics Conference/2023 International Photonics and Optoelectronics Meetings (ACP/POEM)

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Field Trial of Failure Localization in a Backbone Optical Network

Cited by 5 publications

References 17 publications

Cost and power-consumption analysis for power profile monitoring in optical networks

Cost and power-consumption analysis for power profile monitoring in optical networks

Spectral power profile optimization of a field-deployed wavelength-division multiplexing network enabled by remote EDFA modeling

Cluster-Based Method for Eavesdropping Identification and Localization in Optical Links

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