A Digital Twin is a virtual model that accurately simulates and represents the physical characteristics and behaviors of a partially disaggregated optical network. By creating this digital representation, the control architecture can predict how changes in the network affect its operation and enable the system to autonomously adjust the working points of amplifiers. This capability enhances the network’s resilience by mitigating soft failures, thereby ensuring consistent and reliable performance.
GNPy advancements enable accurate and efficient modeling of multiband optical networks for digital twin applications. The developed solvers for Kerr nonlinearity and SRS have been validated through simulation and experimentally in C+L transmission, supporting real-world network planning, design, and performance optimization across disaggregated optical infrastructures.
We propose building a spectrally resolved QoT Digital Twin for optical network domains where models and telemetry are unavailable, by probing transmission on a singlespectral slot, using GNPy, and demonstrating accurate experimental results.
A control architecture for a partially disaggregated optical network is proposed using a GNPy-based digital twin for QoT estimation. The proposed implementation enables soft failure mitigation by autonomously adjusting the amplifier working points.
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