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In this Letter, we develop the Stokes space-based method for modulation format identification by combing power spectral density and a cluster analysis to identify quadrature amplitude modulation(QAM) and phase-shift keying(PSK) signals. Fuzzy c-means and hierarchical clustering algorithms are used for the cluster analysis.Simulations are conducted for binary PSK, quadrature PSK, 8PSK, 16-QAM, and 32-QAM signals. The results demonstrate that the proposed technique can effectively classify all these modulation formats, and that the method is superior in lowering the threshold of the optical signal-to-noise ratio. Meanwhile, the proposed method is insensitive to phase offset and laser phase noise.
In this Letter, we develop the Stokes space-based method for modulation format identification by combing power spectral density and a cluster analysis to identify quadrature amplitude modulation (QAM) and phase-shift keying (PSK) signals. Fuzzy c-means and hierarchical clustering algorithms are used for the cluster analysis. Simulations are conducted for binary PSK, quadrature PSK, 8PSK, 16-QAM, and 32-QAM signals. The results demonstrate that the proposed technique can effectively classify all these modulation formats, and that the method is superior in lowering the threshold of the optical signal-to-noise ratio. Meanwhile, the proposed method is insensitive to phase offset and laser phase noise.