The Power Control Algorithm Based On Noncooperative Game In Cognitive Radio

In recent years, with the rapid development of communication technology, the fixed spectrum allocation resulted in a shortage of spectrum resources. A large number of licensed wireless spectrum to be idle, and can not be effectively used. Cognitive radio technology uses spectrum sharing technology to make licensed users and cognitive users use the same licensed band to complete communication, which enhance spectrum utilization and ease the spectrum resource scarcity. Because the transmit power from cognitive users will influence licensed users, and interference degree directly affect the quality of licensed users'communication, so we must stringent power control on cognitive user.This paper research the cognitive radio power control algorithm based on the non-cooperative game theory. This paper first analysis the non-cooperative game cognitive radio power control model NPG and the non-cooperative game cognitive radio power control with the cost function model NPGP. Because cognitive users of NPGP model can't fairly share the spectrum resources, therefore this paper puts forward an improved non-cooperative game power control model NPGP-PG-NL, which based on link gain and nonlinear cost function. The improved game model NPGP-PG-NL has some improvement in the transmit power and utility than the original model NPGP.Finally, this paper puts forward a new non-cooperative game power control algorithm which based on the interference threshold of primary user. This new algorithm considers the interference for primary user. The utility function and the capacity are relevant with the transmit power. The design of the cost function not only add the corresponding interference limit for primary user, also consider the fairness between secondary users. The simulation results show this non-cooperative game power control algorithm which based on the interference threshold is able to reduce the transmit power, at the same time improve the secondary users'utility and the algorithm convergence speed.