Signal classification using statistical moments

• Published in: IEEE transactions on communications Vol. 40; no. 5; pp. 908 - 916
• Main Authors: Soliman, S.S., Hsue, S.-Z.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.05.1992; Institute of Electrical and Electronics Engineers
• Subjects: Applied sciences; Binary phase shift keying; Classification algorithms; Data mining; Exact sciences and technology; Information, signal and communications theory; Modulation, demodulation; Pattern classification; Pattern recognition; Phase modulation; Phase shift keying; Signal analysis; Signal and communications theory; Signal processing; Telecommunications and information theory; Testing; Hypothesis test; Phase shift keying; Automatic classification; M ary modulation; Algorithm performance; Statistical moment; Decision rule
• ISSN: 0090-6778; 1558-0857
• DOI: 10.1109/26.141456

An automatic modulation classification algorithm utilizing the statistical moments of the signal phase is developed and used to classify the modulation type of general M-ary PSK signals. It is shown that the nth moment (n even) of the phase of the signal is a monotonic increasing function of M. On the basis of this property, the authors formulate a general hypothesis test, develop a decision rule, and derive an analytic expression for the probability of misclassification. Two examples are given to demonstrate the performance of the algorithm. The algorithm is compared with the quasi-log-likelihood radio (qLLRC), square-law (SLC), and phase-based (PBC) classifiers. The algorithm is outperformed by qLLRC at low CNR but is comparable to SLC and is better than PBC. The qLLRC algorithm is only valid at CNR<0 dB and can be used only to discriminate between BPSK and QPSK signals, whereas the moments algorithm is more general.< >