A novel modulation classification for PSK and QAM signals in wireless communication

In this paper, we proposed a new modulation classification algorithm in AWGN channel using fourth order cumulants and improved clustering density spectrum. First, subtractive clustering algorithm is used to classify MPSK and MQAM. Then, a novel algorithm based on the density spectrum of digital signal constellations and cumulants is proposed to internally identify MQAM and MPSK respectively. The peak numbers of in-phase and quadrature density envelope are derived to classify MQAM based on haar wavelet transform. Compared with the existing methods, it is a simple solution with a smaller number of symbols and more modulation types. Simulation results prove the efficiency of the proposed classification algorithm.