Adaptive Spectrum Detecting Algorithm in Cognitive Radio

Cognitive radio (CR) network can make an opportunistic access of spectrum licensed to a primary user (PU). The CR must perform spectrum sensing to detect active PU, thereby avoiding interfering with it. This chapter focuses on adaptively spectrum sensing, so that negative impacts to the performance of the CR network are minimized when CR users experience both stochastic data arrival and time-varying channel. Since the frequency of the spectrum sensing has a directly impact on system throughput and the probability of collision between the PU and CR user, the PU activity is modeled based on the characteristic analysis of the PU spectrum utilization. Based on that, an efficient adaptive sensing algorithm that takes into account the system stability, collision, and throughput is proposed. The CR users can make a balance between them by utilizing a “periodic control factor” which controls the adaptive adjustment of the spectrum sensing frequency. The simulation results indicate that the proposed algorithm has excellent performance on collision probability and throughput compared with conventional periodic spectrum sensing scheme. Meanwhile, it is shown that the proposed algorithm has low implementation complexity for practical applications.