Spectrum Sensing Based on Fractional Lower Order Power Spectral Density in Alpha-Stable Noise Environments

Abstract

In view of the fact that the alpha distribution does not possess two order moment and power spectrum, the detection performance of the traditional detectors, such as energy detector (ED) and power spectral density (PSD) detector, will be degraded or even failed when the background noise be modeled as alpha-stable distribution in CR system. This paper presents a novel spectrum-sensing scheme based on fractional lower order statistics power spectral density (FPSD). The proposed algorithm, combining pseudo-PSD and Fourier transform (FT), calculates the FPSD of the received signal to determine whether primary user (PU) is present or absent. Via the numerous simulations, the performance of the FPSD versus the characteristic exponents α, the moment p, and generalized signal-to-noise (GSNR) of the noise has been studied. Simulations show that the proposed FPSD detector has greater performance than ED and PSD in alpha-stable noise environment. In addition, the new detector, as a blind detector, has high probability detection without the prior knowledge of PU signal and noise.