A Cyclostationarity-Based Spectrum Sensing Scheme for Dynamic Traffic Circumstances

In this paper, we propose a cyclostationarity-based spectrum sensing scheme for dynamic traffic circumstances. First, we model the spectrum sensing problem in dynamic traffic circumstances as a binary hypothesis testing problem where primary users (PUs) might randomly depart or arrive during the sensing period. Then, we develop a generalized likelihood ratio (GLR) and derive a test statistic via the GLR, which is based on the cyclostationarity of the PU signals. Numerical results confirm that the proposed scheme offers a better spectrum sensing performance than the conventional scheme based on energy detection for dynamic traffic circumstances.