On the Value of Prediction in Opportunistic Radio Systems

In opportunistic spectrum access, radios sense their environment and adapt communication to utilize unused licensed spectrum without interfering with licensed users. A true cognitive radio, however, should do more than only access spectrum opportunistically. It should autonomously acquire and learn helpful new wireless information and use patterns. In this paper, we construct an algorithm, based on the use patterns in the licensed bands. It finds the optimal trade-off between buffering packets and switching channels, while guaranteeing delay demands. This algorithm is shown to outperform the benchmark solution by up to 50%.