Novel recognition method for digital modulation signals with Alpha stable noise

The traditional methods for digital modulation signals recognition with Alpha stable distribution noise have the problem of poor performance. In this paper, a novel recognition method for digital modulation signals based on the generalized cumulant and generalized instantaneous phase is proposed to solve this problem. This method extracts the characteristic parameters which are the generalized cumulant and maximum of normalization and center generalized instantaneous phase spectral density based on fractional Fourier transform. And then the minimum mean square error classifier and the threshold are used to achieve modulation recognition of digital modulation signals with Alpha stable distribution noise. Simulation results show that the proposed method has not only better performance but also lower computation complexity than the traditional recognition methods in an Alpha stable distribution noise environment.