Vasu Chakravarthy (Committee Member), Yao Ma (Committee Member), Zhiqiang Wu (Advisor)
Master of Science in Engineering (MSEgr)
This research develops and evaluates several different methods for multi-user signal classification via cyclic spectral analysis. The first method uses the spectral correlation function (SCF) through temporal smoothing with the use of higher order cyclic statistics (HOCS) to allow for modulation classification. The second method uses the cyclic temporal cumulant function (CTCF) and the spectral coherence function (SOF) through frequency smoothing. Using a feature-based pattern recognition technique with the SOF can not only determine the number of signals present in the received signal, but can also give signal parameter estimation and group classification performance. The last method conducts further modulation classification by using second and fourth order Cyclic Cumulants. Cyclostationary processing is the foundation of this research and requires no a priori information about the incoming signal parameters; including but not limited to symbol rate, carrier frequency and phase offset. Monte Carlo simulations completed in MATLAB and performance results are given for all aforementioned methods.
Department or Program
Department of Electrical Engineering
Year Degree Awarded
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