A novel spectrum sensing method in cognitive radio based on suprathreshold stochastic resonance

To tackle the problem of performance degradation of traditional spectrum sensing technique with energy detection under the circumstances of weak signal and non-Gaussian environment in cognitive radio (CR), a novel spectrum sensing method based on suprathreshold stochastic resonance (SSR) is proposed in this paper. Through the resonance between the primary user (PU) signal and noise by introducing nonlinearity of a parallel of quantizers, the signal-to-noise ratio (SNR) of the received signal can be increased when the constraint we develop is satisfied. To obtain a constant false-alarm rate (CFAR), the detection probability of the proposed method is derived. Theoretical analyses and simulation results show that the detection performance is superior to the conventional energy detection method under low SNR circumstances when the a certain range of non-Gaussian noise is input.