Multiagent jamming-resilient control channel game for cognitive radio ad hoc networks

Control channel jamming is a severe security problem in wireless networks. This results from the fact that the attackers can effectively launch the denial of service attacks by jamming the control channels. Traditional approaches to combating this problem such as channel hopping sequences may not be the secure solution against intelligent attackers because the reliability of control channels in cognitive radio ad hoc networks cannot be guaranteed. In this paper, we introduce a jamming-resilient control channel (JRCC) game to model the interactions among cognitive radio users and the attacker under the impact of primary user activity. We propose the JRCC algorithm that enables user cooperation to facilitate control channel allocations and adapts to primary user activity with variable learning rates using the Win-or-Learn-Fast principle for jamming-resilience in hostile environments. It is shown that the optimal strategies converge to a Nash equilibrium or the expected rewards of the strategies converge to that of a Nash equilibrium. The results also show that the JRCC algorithm effectively combats jamming under the impact of primary user activity and sensing errors. Moreover, the control channel allocation policy can be improved by enhancing transmission and sensing capabilities. The proposed algorithm is scalable and can be applied to multiple users.