A cooperative game theory approach to resource allocation in cognitive radio networks

In cognitive networks, the parameters of radios were adapted to achieve end-to-end or network objectives such as spectral or energy efficiency, reliability, or throughput maximization. In these networks, the licensed spectrum and dynamic spectrum sharing based on opportunistic communication play an important role of resource allocation. Since the resource allocation networks always cooperate and coexist in cognitive, Game theory has been employed to analysis that. In really case, the cooperator only have partial or no information concerning in advance to making decision. However, the current game theory models in cognitive radio networks always regard they have enough information. In this paper, we take Incomplete Information into account and propose an algorithm base on game theory to resource allocation. Compare traditional algorithms, this one can improve the in the cognitive radio networks as the simulations showing.