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Optical Performance Monitoring Using Artificial Neural Networks Trained With Eye-Diagram Parameters

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3 Author(s)
Jargon, J.A. ; Nat. Inst. of Stand. & Technol., Boulder, CO ; Xiaoxia Wu ; Willner, A.E.

We developed artificial neural network models to simultaneously identify three separate impairments that can degrade optical channels, namely optical signal-to-noise ratio, chromatic dispersion, and polarization-mode dispersion. The neural networks were trained with parameters derived from eye diagrams to create models that can predict levels of concurrent impairments. This method provides a means of monitoring optical performance with diagnostic capabilities.

Published in:

Photonics Technology Letters, IEEE  (Volume:21 ,  Issue: 1 )