Cyclostationarity-Based Detection of Randomly Arriving or Departing Signals

This paper addresses the problem of detection of randomly arriving or departing primary user (PU) signals in cognitive radio systems. The detection problem of the dynamic PU signal is modeled as a binary hypothesis testing problem where the PU signal might randomly depart or arrive during the sensing period. Then, we detect the cyclostationarity of the PU signal using a test statistic derived from the spectral autocoherence function in dynamic PU signal environments. Numerical results show that the proposed scheme offers an improved spectrum sensing performance than the conventional energy detector for dynamic PU environments.