A Two-Stage Spectrum Sensing Technique in Cognitive Radio Systems Based on Combining Energy Detection and One-Order Cyclostationary Feature Detection

In cognitive radio systems, the main requirement of cognitive radio architectures is the ability to detect the presence of the primary user with fast speed and precise accuracy. To achieve that, we suggest a possible two-stage spectrum sensing approach. More specifically, a fast spectrum sensing algorithm based on the energy detection is introduced focusing on the coarse detection. A complementary fine spectrum sensing algorithm adopts oneorder cyclostationary properties of primary user’s signals in time domain. This feature detection technique in time domain realizes simple and low computational complexity compared to spectral feature detection methods. Also, it drastically reduces hardware burdens and power consumption as opposed to two-order feature detection. The sensing performance of the proposed method is studied and the analytical performance results are given. The results indicate that better performance can be achieved in proposed two-stage sensing detection compared to the conventional energy detector.