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

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.