PFS: A novel modulation classification scheme for mixed signals

Abstract

In practice, signals may be interfered by hostile jamming or illegal transmission and it is a very challenging task to determine the modulation formats of mixed signals. To tackle this problem, we propose a three-step algorithm called PFS algorithm. In the first step, principal component analysis (PCA) is conducted to suppress the noise. In the second step, the mixed signals are separated via fast independent component analysis (FICA), which transforms the received signals into the components that are maximally independent of each other. In the third step, high-order cumulants (HOCs) and support vector machines (SVMs) are adopted to determine the modulation format of the signal. The numerical experiments show that the PFS algorithm has a superior performance compared to other existing methods.