National Ict Australia Limited

Nicta Ipr Pty Limited

Kenneth Paul Clarke

Adam Kowalczyk

Trevor Anderson

Justin Bedo

Sarah Dods

A method of assessing a signal to identify particular signal characteristics comprises application of machine learning to multi-dimensional histograms derived from multi-tap sampling of the signal. The signal is sampled from at least two tap points to retrieve a sample set, and the at least two tap points are adapted to retrieve distinct samples from the signal, such as time spaced samples or spectrally distinct samples. Multiple sample sets are retrieved from the signal over time. The at least two dimensional histogram is built from the joint probability distribution of the plurality of sample sets. A machine learning algorithm then processes the multi-dimensional histogram, and is trained to predict a value of at least one characteristic of the signal.

Method and apparatus for automated identification of signal characteristics

Monitoring an optical signal comprises sampling the optical signal from two or more distinct tap points to retrieve a sample set. Multiple such sample sets are obtained over time. A joint probability distribution or phase portrait of the sample sets is assessed for indications of optical signal quality. The tap distinction can be polarization, for example to determine OSNR, or frequency. The tap distinction can be a time delay, which can enable diagnostic differentiation between multiple impairments, such as OSNR, dispersion, PMD, jitter, Q, and the like. Machine learning algorithms are particularly suitable for such diagnosis, particularly when provided a two dimensional histogram of sample density in the phase portrait.

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Glen Iris, Australia

Kenneth Paul Clarke