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http://dx.doi.org/10.5909/JBE.2014.19.2.195

Digitally Modulated Signal Classification based on Higher Order Statistics of Cyclostationary Process  

Ahn, Woo-Hyun (Department of Electronics Engineering, Chungbuk National University)
Nah, Sun-Phil (Agency for Defense Development)
Seo, Bo-Seok (Department of Electronics Engineering, Chungbuk National University)
Publication Information
Journal of Broadcast Engineering / v.19, no.2, 2014 , pp. 195-204 More about this Journal
Abstract
In this paper, we propose an automatic modulation classification method for ten digitally modulated baseband signals, such as 2-FSK, 4-FSK, 8-FSK, MSK, BPSK, QPSK, 8-PSK, 16-QAM, 32-QAM, and 64-QAM based on higher order statistics of cyclostationary process. The first order cyclic moments and higher order cyclic cumulants of the signal are used as features of the modulation signals. The proposed method consists of two stages. At the first stage, we classify modulation signals as M-FSK and non-FSK using peaks of the first order cyclic moment. At the next step, we apply the Gaussian mixture model-based classifier to classify non-FSK. Simulation results are demonstrated to evaluate the proposed scheme. The results show high probability of classification even in the presence of frequency and phase offsets.
Keywords
Automatic modulation classification; higher order statistics; cyclostationarity; cyclic moments; cyclic cumulnats; Gaussian mixture model (GMM);
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