Spectrum sensing via statistic tests in Rayleigh fading channels

Cognitive radio applications are limited by the scarcity of available frequency bands for telecommunication services. The improvement of the spectrum sensing to enable a better sharing of the frequency spectrum among different users is a major challenge in wireless communications based on cognitive radio. This paper evaluates the use of statistic tests to optimize the non-cooperative cognitive spectrum sensing. Statistical characteristics of the transmitted signals are selected to achieve better cognitive sensing performance. More precisely, Jarque-Bera, Kurtosis and Skewness statistic tests are compared in Rayleigh fading channel and non-fading scenarios. Simulation results indicate that these statistic tests can be effectively applied to cognitive wireless channels that are subjected to fading.