Efficient Classification of Optical Modulation Formats Based on Singular Value Decomposition and Radon Transformation

Two schemes for blind optical modulation format identification (MFI), based on the singular value decomposition (SVD) and Radon transform (RT) of the constellation diagrams, are proposed. Constellation diagrams are obtained at optical signal-to-noise ratios (OSNRs) ranging from 2 to 30 dB for eight different modulation formats as images. The first scheme depends on the utilization of feature vectors composed of the singular values (SVs) of the obtained images, while the second scheme is based on applying the RT and then getting the SVs. Different classifiers are used and compared for the MFI task. The effect of varying the number of samples on the accuracy of the classifiers is studied for each modulation format. Simulation and experimental setups have been provided to study the efficiency of the two schemes at high bit rates for three dual-polarized modulation formats. A decimation approach for the constellation diagrams is suggested to reduce the SVD complexity, while maintaining high classification accuracy. The obtained results reveal that the proposed schemes can accurately be used to identify the optical modulation format blindly with classification rates up to 100% even at low OSNR values of 10 dBs.