A Robust Cooperative Spectrum Sensing Method in Cognitive Radio Networks

In real cognitive radio networks, the requirement for spectrum sensing in the case of lacking prior information and dynamically varying noise levels indeed poses a severe challenge. Motivated by these, in this letter, a Cooperative Power spectral density Split Cancelation (CPSC) method is proposed. The CPSC makes full use of the asymptotic normality and independence of a Fourier transform to get the stochastic properties of the power spectral density. We derive an exact closed-form expression of a decision threshold and provide an analysis about computational complexity. Analytical and simulation results show that the CPSC is robust under uncertain noise. Meanwhile, the CPSC benefits from a low computational cost and existing mature intellectual property cores; thus, it can be implemented efficiently.