Survey of modulation classficiation methods for QAM signals

Classification of the modulation type of a signal is a rapidly evolving research area with interests in both civilian and military applications. Quadrature Amplitude Modulation (QAM) is a modulation scheme where both the amplitude and phase of the signal is shifted in accordance with the message. Because of its bandwidth efficiency QAM has become more frequently used especially in high capacity radio communications. Since there is a recent increase of QAM signals, methods for classifying such signals are of great importance. This report is a result of a study performed to survey existing methods for QAM classification. Both pattern recognition and decision theoretic methods based on for example higher order statistics, wavelets and maximumlikelihood, are presented. The proposed methods are discussed and fundamental advantages and drawbacks are identified. In general, the approaches to QAM classification are only at its first stage towards practical implementation since ideal conditions, i.e. additive white Gaussian noise and perfect signal parameter recovery, are assumed and current analysis of the considered methods lacks studies in robustness.