Dynamically optimized spatiotemporal prioritization for spectrum sensing in cooperative cognitive radio.

In this paper, an enhanced cooperative, statistics-driven spectrum sensing algorithm, called Dynamically Optimized Spatiotemporal Prioritization (DOSP), is developed for improving spectrum sensing efficiency in the media access control (MAC) layer of cognitive radio (CR) systems. The target of the DOSP algorithm is to improve spectrum sensing efficiency and achieve better spectrum access opportunities by prioritizing channels for fine sensing. The sensing priority is determined dynamically and intelligently based on an optimal statistical fusion that jointly considers both the local statistics obtained by the individual cognitive radios as well as the long-term spatiotemporal statistics obtained by other cognitive radios in the network. As such, the individual cognitive radio peers work together to get the most out of available spectrum opportunities. Numerical results demonstrate that the proposed DOSP algorithm is capable of achieving better performance compared with recently reported cooperative spectrum sensing methods in terms of overhead and percentage of missed spectrum opportunities. Furthermore, results show that the DOSP algorithm is more robust to the environment of low cognitive radio densities than that by using other state-of-the-art cooperative spectrum sensing methods.