An Improved Method for the Automatic Digital Modulation Classification

In this paper, a new method for the automatic modulation classification of an unknown signal, working without any knowledge about the modulation parameters, is proposed. The method has been developed in two different versions, such that it can be implemented on both waveform digitizers and vector signal analyzers. The developed method is able to recognize classical single carrier modulations such as M-ary phase-shift keying (PSK), M-ary frequency shift keying (FSK), M-ary amplitude shift keying (ASK), and M-ary quadrature amplitude modulation (QAM), as well as orthogonal drequency division multiplexing modulations (OFDM) such as the discrete multitone (DMT). Both the versions of the new developed method are able to work with limited-bandwidth signals, too. After the identification of the modulation type, the method automatically estimates some parameters characterizing the modulation. In order to evaluate the method performance, several experimental tests, with simulated and actual signals, have been carried out in different operating conditions by varying the Signal to Noise Ratio and other parameters characterizing the modulation, such as the carrier frequency and the symbol rate.