Cognitive spectrum sensing based on statistical tests in fading channels

The cognitive radio concept is fostered by the scarcity of frequency bands for wireless communication. Several new techniques and algorithms are being proposed to deal with the spectrum occupancy in cognitive channels. The goal is to enable a better sharing of the frequency spectrum among different users. This paper evaluates the performance of statistical tests to optimize the spectrum sensing for fading channels. Statistical characteristics of the transmitted signals can be used to achieve better cognitive sensing performance. Jarque-Bera, Kurtosis and Skewness statistical tests are evaluated when subject to fading effects. Rayleigh, Nakagami-m, Rice and Lognormal fading channels are simulated. Results indicate that these statistical tests can be applied to cognitive wireless channels even when subject to fading.