Truth reveling opportunistic scheduling in cognitive radio systems

The conventional opportunistic scheduling algorithm in cognitive radio networks among secondary users is based on the reported state values to the central controller. However, with the increasing programmability of network users, a malicious user can strategically declare a false state in order to gain an unfair share of resources. How to ensure all the users revel their true information becomes an important issue in the system design. 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.