Probabilities of False Alarm and Detection for the First-Order Cyclostationarity Test: Application to Modulation Classification
Ahmet Serbes, Hüseyin Çukur, Khalid A. Qaraqe · IEEE Communications Letters · 2019
Automatic modulation classification is one of the most challenging problems of cognitive radio and has significant commercial and military application. This letter focuses on blind modulation classification of first-order cyclostationary signals under a Gaussian channel. A detailed theoretical analysis of the first-order cyclostationarity test has been performed. We present the theoretical expressions of the probability of false alarm Pfa and the probability of detection Pd as a function of the selected threshold for the first-order cyclostationarity test based constant false alarm rate detector. The Pd is presented for only AM and M-FSK signals, which are the only signals that possess first-order cyclostationary features. Theoretical formulations presented in this letter are validated by extensive simulation results.