Learning and decision making with negative externality for opportunistic spectrum access
In cognitive radio networks, secondary users (SUs) are allowed to opportunistically exploit the licensed channels by sensing primary users' (PUs) activities. Once finding the spectrum holes, SUs generally need to share the available licensed channels. Therefore, one of the critical challenges for fully utilizing the spectrum resources is how the SUs obtain accurate information about the PUs' activities and make right decisions of accessing channels to avoid competition from other SUs. In this paper, we formulate SUs' learning and decision making process as a Chinese Restaurant Game by considering the scenario where SUs sense channels simultaneously and make access decisions sequentially. In the proposed game, SUs build the knowledge of the PUs' activities by their own sensing and learning the information from other SUs. They also predict their subsequent SUs' decisions to maximize their own utilities. We analyze the interactions among SUs in the proposed game and study specifically the impact of SUs' prior belief and sensing accuracy on their decisions. We also derive the theoretic results for the two-user two-channel case. Finally, we demonstrate the effectiveness and efficiency of the proposed scheme through simulations.