Spatial and time diversities for canonical correlation significance test in spectrum sensing

In this paper, we present a new detector for cognitive radio system based on the Canonical Correlation Significance Test (CCST). Unlike existing CCST approaches, which can only be applied on Multi-Antenna System (MAS), our algorithm can be extended for both Single Antenna System (SAS) and MAS. For SAS, the proposed algorithm exploits the time diversity of cyclostationary signals in order to detect the Primary User (PU) signal. Our simulation results shows that our algorithm outperforms well-known cyclostationary algorithm [9]. For MAS, our algorithm uses both spatial and time diversities to apply the CCST. Numerical results are given to illustrate the performance of our algorithm and verify its efficiency for special noise cases (spatially correlated and spatially colored). The simulation results show the superiority of the performance of the proposed detector compared to the recently CCST proposed algorithm [1].