Power Control Algorithm For Distributed Cognitive Radio Networks Based On Game Theory

The demand for radio spectrum industry has been increased dramatically in mobile communication in the last decade. In order to overcome the constraint of the traditional static spectrum allocation on the wireless network performance, meet the needs for broadband in future wireless communications network, achieve the flexible, anti-survivability and convenient target in network forming, distributed cognitive radio (CR, Cognitive Radio) networks have been paid more and more attention. An important means to improve the spectrum efficiency of cognitive radio system is that the primary users can share spectrum with cognitive users. In order not to affect the normal communication of the primary user, the primary user usually requires interference caused by cognitive users is lower than the interference temperature threshold, the cognitive user’s transmit power must be effectively controlled.The power control problem in distributed cognitive radio network is generally a multi-objective optimization problem. In distributed cognitive radio network, the cognitive users must compete for the limited spectrum resources because of lacking central node (central controller), so this problem can be solved by the competitive optimization method, which is based on the game theory. Currently most literatures model the power control problem to a non-cooperative game, which improves the spectral efficiency of the distributed cognitive radio system to some extent, but it is not global optimal and can not control the interference to primary users effectively. At the same time, the convergence speed of algorithm and system fairness can not be guaranteed, thus the competitive market model in game theory is used to solve the power control problem in the cognitive radio network in our paper.The equilibrium solution of this non-cooperative game based on competitive market model is the competitive equilibrium (CE). We first prove the existence and the uniqueness of CE for the proposed competitive market model and present the sufficient conditions for this. Secondly, a distributed algorithm is proposed through which all the secondary users’power allocation can converge to the unique CE while the interference temperature constraints of primary system are satisfied. To make the algorithm applicable to a more realistic wireless environment, we study the performance of the algorithm in Rayleigh fading channel conditions. Finally, we propose a distributed social fairness aware FCPAA algorithm (SFAF) in consideration of the system fairness, and this algorithm balances the users’personal efficiency and system fairness.