A Novel Automatic Modulation Classification for M-Qam Signals Using Adaptive Fuzzy Clustering Model

Abstract

An automatic modulation classification (AMC)method for M-ary quadrature Amplitude Modulation (M-QAM)signals using adaptive fuzzy clustering model is presented. In the proposed framework, the neighborhood radius of subtractive clustering algorithm is emphatically researched to satisfy different modulation orders. An adaptive construction mechanism of neighborhood radius is designed according to the amplitude component of M-QAM signals. Euclidean distance of the clustering center numbers between test signal and standard signals are utilized to identify the modulation types. Monte Carlo simulation results and theoretical analysis demonstrate that the proposed AMC method can provide promising performance.