Modulation Recognition Based on SVM In Fading Channels

In this paper the method of recognizing signals modulated by QPSK, 16QAM, 64QAM and OFDM is presented based on the support vector machine(SVM) algorithm with the characteristic parameter of forth order cumulants. SVM maps the feature values of classification into high dimension space, in which the optimal separating hyperplane is constructsed to realize the separation of the signals with targeted modulation method. The influence of AWGN channel, Rayleigh and Nakagami fading channels on the characteristic parameter is analyzed respectively, and the explicit expression of the characteristic parameter is further derived. The recognition method based on SVM can resolve the nonseparable problem in low dimension space. The simulation results show that the performance of the SVM-based method is much better than that of the decision tree method when SNR is lower than 10dB. With SNR larger than 0db, the successful recognition rates of the four types of signals are all above 90%.