Correlation-based detection of TCM signals for cognitive radios

In this work, the inter-dependency of TCM signals is studied. Using this inter-dependency, correlation-based detectors are proposed for spectrum sensing of TCM signals in white Gaussian noise. In particular, a constant false alarm rate (CFAR) detector is presented and its performance is evaluated using simulations. We also describe an application of our detector for the classification of uncoded modulation systems vs. their TCM counterparts and present numerical results on their performance.