Multiple antenna spectrum sensing using statistical a-priori information in cognitive radios

In this study, the authors consider the problem of multiple antenna spectrum sensing by exploiting the prior information about unknown parameters. Under assumption that additional statistical side information is available about unknown parameters, a novel framework and some detectors are proposed, which are optimal for finite number of received samples. locally most powerful, average likelihood ratio and the novel generalised likelihood ratio detectors are calculated for the different practical conditions in wireless channels. In addition, the analytical performance evaluation for proposed detectors is provided whenever possible. The simulation and analytical results show that the a-priori information can be used for better spectrum sensing using finite number of samples.