A Novel Spectrum Sensing Scheme for Dynamic PU Traffic Environments

Exploiting the cyclostationarity of the primary user (PU) signals, we propose a novel spectrum sensing scheme for cognitive radio (CR) systems in dynamic PU traffic environments where PUs might randomly depart or arrive during the sensing period. First, the spectrum sensing problem is modeled as a binary hypothesis testing problem and the corresponding generalized likelihood ratio (GLR) is developed. Then, a test statistic for spectrum sensing is derived by obtaining an estimate of spectral autocoherence function of the PU signal and then applying it to the GLR. Numerical results show that the proposed cyclostationarity approach provides a significant improvement in spectrum sensing performance over the conventional energy detection approach in dynamic PU traffic environments.