Automatic Modulation Recognition of PSK signals using nonuniform compressive samples based on high order statistics

The N^th Power Nonlinear Transformation (NPT) is a common method for automatic modulation classification, especially for PSK signals. However, greater than Nyquist rate sampling is essential for features extraction in NPT. In this paper, introducing the compressive sensing (CS) theory, we propose a novel Automatic Modulation Recognition (AMR) method based on the frequency spectrum of the N^th power nonlinear transformation of PSK type signals, from nonuniform compressive samples. Here, analysis of frequency spectrum reconstruction of the N^th power nonlinear transformation of PSK signals is presented, which can be further used for AMR and rough estimations of unknown carrier frequency and symbol rate.