Energy Efficient Blind Automatic Modulation Classification

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Spectral correlation function of overlapped BPSK, QPSK, and MSK
Higher order modulation classifier architecture

Modulation classification is becoming an increasingly important subject in military applications and more recently in the context of cognitive radio to detect the type of the licensed primary user. Furthermore, future public safety systems require modulation classification to distinguish between different types of early responders and coordinate communication in a better way. With that in mind, we are exploring blind cyclostationary-based energy efficient algorithms for modulation classification that would help unlicensed users in the detection of the primary user. We are investigating the classification of overlapped signals using a single receive antenna for a low hardware complexity system (see Spectral Correlation Function for overlapped BPSK, QPSK, and MSK signals). Given that this method doesn't differentiate among different levels of the same modulation class, we propose a hierarchical classifier which first estimates the modulation class, and then finds the modulation level.

In the same spirit, we are also investigating highly energy efficient algorithms for accurate modulation classification that distinguish among higher-order modulations. The novel techniques utilize different statistical distribution distance tests such as the Kuiper test and the Kolmogorov-Smirnov test with the goal of improving the performance of current techniques based on cumulants.

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Selected publications