Abstract
Automatic modulation classification has significant commercial and military applications and is one of the most challenging problems of the cognitive radio. To demodulate a captured signal, it is necessary to know the parameters of the signals and the preliminary information about the type of modulation. However, in most cases, the signal has no prior knowledge of the modulation type. Even more, there may not be a modulation pool available for possible modulation types. Cyclostationary-based features can be employed to blindly identify the unknown modulation type. In this study, a detailed theoretical analysis of the first order cyclostationarity was performed on FSK and AM signals, which are known to be first-order cyclostationary. Theoretical relationship between the threshold and the constant false alarm rate detector is derived for the first order cyclostationarity test. Theoretical analyses are validated by simulation results.