A HOS-Based Blind Spectrum Sensing in Noise Uncertainty

Abstract

Spectrum sensing for cognitive radio is a challenging task since it has to be able to detect the primary signal at a low signal to noise ratio (SNR). At a low SNR, the variance of noise fluctuates due to noise uncertainty. Detection of the primary signal will be difficult especially for blind spectrum sensing methods that rely on the variance of noise for their threshold setting, such as energy detection. Instead of using the energy difference, we propose a spectrum sensing method based on the distribution difference. When the channel is occupied, the distribution of the received signal, which propagates under a wireless fading channel, will have a non-Gaussian distribution. This will be different from the Gaussian noise when the channel is vacant. Kurtosis, a higher order statistic (HOS) of the 4th order, is used as normality test for the test statistic. We measured the detection rate of the proposed method by performing a simulation of the detection process. Our proposed method's performance proved superior in detecting a real digital TV signal in noise uncertainty.