A hybrid cooperative spectrum sensing technique for cognitive radio networks using linear classifiers

In this paper, a hybrid cooperative spectrum sensing technique ( HCSST) is proposed merging between energy detection (ED) and cyclostationary feature detection (CFD) such that both low computational complexity as well as the superior detection performance are achieved. In HCSST, individual Cognitive Radio (CR) nodes decide independently on using ED or CFD as their spectrum sensing technique based on the received signal-to-noise ratio at each cognitive end. Cooperative decision about spectrum availability is made using a trained linear classifier (LC) at the fusion center (FC). Results have shown that HCSST provides superior performance over ED and a slightly degraded performance compared to CFD. Further, the computational complexity is reduced noticeably at high SNR regimes.