Cognitive Spectrum Sensing Via Statistical Tests in Rice Fading Channels

Spectrum sensing is an important tool for the expansion of cognitive radio. This paper evaluates the use of statistical tests to optimize the spectral detection of available frequency bands for opportunistic occupation. Statistical characteristics of the transmitted signals over a channel subject to Rice fading are selected to achieve better cognitive sensing performance. More precisely, Jarque-Bera, Kurtosis and Skewness statistical tests are compared via simulation in terms of their detection probabilities in non-fading and in Rice fading channels. Simulation results indicate that these statistical tests are useful, and can be effectively applied to cognitive wireless channels subjected to fading.