Optical Fiber Communication Conference · 2017 · 18 citations · 1 references
ComputingComputer ScienceElectrical EngineeringComputer NetworksOptoelectronicsPhotonicsCommunication NetworksLoss FunctionNetwork Performance AnalysisNetwork ReliabilityOptical Communication SystemsLayer AbstractionOptical Channel ModelingOptical Performance MetricsTraffic ModelingTransmission Loss PredictionTransmission Modelling
We propose a dynamically configurable optical impairment model for a physical layer abstraction enabling physical parameters learning in multi-vendor networks. We experimentally demonstrate quality of transmission prediction in mesh networks with 0.6 dB Q-factor accuracy.
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