A spectrum sensing method based on fractional lower order moments in weakly correlated Laplace noise

In the actual wireless communication systems, non-Gaussian noise often has a negative effect on the signals which cognitive users finally receive. In addition, due to the high frequency of collecting samples, there may be a certain correlation among the noise components. A detection method based on fractional lower order moments (FLOM) is applied in this paper to solve spectrum sensing in weakly correlated Laplace distributed noise environment. Different from the traditional detector, this detector does not require the priori knowledge of the primary user signal, noise and communication channels. By computer simulating, the detection performance versus the signal-to-noise ratio, the scale parameter b, the order p and the correlation parameter τ are studied both in non-fading communication channel and Rayleigh fading communication channel in this paper with the comparison to the traditional energy detector. Simulation results show that, in the weakly correlated Laplace distributed noise environment, the FLOM-based detector has better performance than the traditional energy detector.