A Method for Digital Modulation Recognition Based on Mixed Signal Features

Abstract

Digital modulation recognition is an important part of signal processing. With inherent anti-noise performance, High-Order Cumulants have natural advantage in recognizing digital modulation pattern, and is widely studied in the past several decades. On the basis of high-order cumulants, combined with peak feature of FFT spectrum and instantaneous signal feature, this paper proposed a new method for digital modulation recognition based on mixed signal features, which took advantage of classical decision-tree classifier. Simulation results showed that the method proposed in this paper can recognize six classical digital modulation pattern efficiently, and achieved satisfactory recognition result even at rather low SNR.