EM-based joint estimation and detection for multiple antenna cognitive radios

In this paper, we present an iterative spectrum sensing scheme for multiantenna assisted cognitive radio (CR) using the expectation-maximization (EM) algorithm. Considering a wideband frequency spectrum, the secondary user (SU) performs an EM-based joint estimation and detection (JED), where the channel coefficients and noise variance are estimated jointly with the primary user (PU) signal variance. We also provide a semi-analytical evaluation of the proposed scheme using the Neyman-Pearson criterion. Compared with the conventional Generalized Likelihood Ratio detector (GLRD), the EM-based JED scheme enhances the detection process of the multiple antenna CR with few iterations and modest complexity.