Accurate and efficient anomaly detection is a key enabler for the cognitive management of optical networks, but traditional anomaly detection algorithms are computationally complex and do not scale well with the amount of monitoring data. Therefore, this dataset enables research on new optical spectrum anomaly detection schemes that exploit computer vision and deep unsupervised learning to perform optical network monitoring relying only on constellation diagrams of received signals.
The dataset contains a set of folders, each one representing one normal/anomalous case.
Within each folder, a number of .mat files contain the raw data collected from VPITransmissionMaker. The images folder contains the rendered constellation diagrams.
To render your own constellation diagrams, check the "generate_plots.m" file in the root folder.
More information on how to use in the GitHub repository.
The dataset is a collection of the simulated and measured data acquired in the process of design, analysis and measurement of the millimeter wave multibeam waveguide lens antenna. A data matrix of the colected data is presented in .mat format with Matlab compatibility.