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The paper presents a new algorithm of digital modulation signals based on high order cumulants (HOC) and support vector machines (SVM). The parameters which are picked up from the signals' fourth order and sixth order cumulants are used as the classification feature vectors. Using SVM based on binary tree as classifiers, recognition of the 2ASK, 4ASK, QPSK, 2FSK and 4FSK signals is efficient. The computer simulation results justify that the success rate is over 97.5% at SNR=10 dB.

A new algorithm based on high order cumulants(HOC) and support vector machines(SVM) for modulation and recognition of digital communication signals is proposed. The new method can identify six digital modulation signals: 2ASK, 4ASK, 8ASK, 4PSK, 8PSK and 16QAM digital signals using fourth and sixth order cumulants of the signals as vectors and SVM based on binary tree as classifiers. The method uses new class distance as rules of constructing binary tree, which separates the furthest class from others first, so that the method can maintain high generalization ability. The computer simulation results justify the method's validity.