Research on communication signal modulation recognition based on the generalized second-order cyclic statistics

To solve the problem that traditional second-order cyclic statistics significantly degenerate in the Alpha stable distribution noise,the concept of generalized second-order cyclic statistics was proposed.On the basis of studying the generalized second-order cyclic statistics of the selected communication signals,the amplitudes of siganals' generalized second-order cyclic spectrum in specific frequencies and cyclic frequencies were extracted as the feature parameters,and the minimum error criterion was used as a classification algorithm to achieve modulation recognition.Simulation results show that the performance of this method is superior to the method based on traditional second-order cycle statistics in the Alpha stable distribution noise,moreover,this method has good performance in the Gaussian noise.