Power allocation games for cognitive radio networks with incomplete information

We consider a cognitive radio network in which a set of primary users make opportunistic spectrum access to support cognitive radios within their coverage areas. In cognitive radio networks, all cognitive radios compete for radio resources and can interfere with each other. The conflicting objectives of users make it highly unlikely for any user to gain more profit without harming other users. On the other hand, channel assignment and power control must be carried out in the cognitive radio network so that no excessive interference is caused to users of the primary network. Given this constraint, we are interested in the downlink power allocation problem, with the objective of maximizing the total number of supported cognitive radios. In this paper we propose a new model that the assumption of incomplete information is involved in the Bayesian game. We demonstrate that to solution the radio resource conflicts in multiuser secondary networks. We show that this approach can be use to power allocation problem. By means of simulations we prove that our method can improve the performance of cognitive radio networks.