Application of Mechanism Design in Opportunistic Scheduling under Cognitive Radio Systems

Abstract

The conventional opportunistic scheduling algorithm in cognitive radio networks does the scheduling among the secondary users based on the reported state values. However, such opportunistic scheduling algorithm can be challenged in a system where each secondary user belongs to a different independent agent and the users work in competitive way. In order to optimize his own utility, a selfish user can choose not to reveal his true information to the central scheduler. In this paper, we proposed a pricing mechanism which combines the mechanism design with the opportunistic scheduling algorithm and ensures that each rational selfish user maximizes his own utility function, at the same time optimizing the overall system utility. The proposed pricing mechanism is based on the classic Vickrey-Clark-Groves (VCG) mechanism and had several desirable economic properties. A mechanism learning algorithm is then provided for users to learn the mechanism and to obtain the Nash equilibrium. A numerical example shows the Nash equilibrium of such algorithm achieves system optimality.