Research Of Dynamic Spectrum Allocation Algorithms In Cognitive Wireless Network Based On Game Theory

In the age of wireless communication technology rapid developing and the shortage andwaste of resources, Cognitive wireless network is considered as a key technology. Tocoordinate the relationship between the authorized users and unauthorized users and improvethe condition of spectrum resource scarcity and the low utilization rate of authorized spectrum,the new spectrum management idea and management rules need to be put forward, so as tomeet the needs of users and adapt to the development of wireless communication technology.Game theory is considered to be a tool to effectively manage dynamic spectrum. It canprovide a good theoretical analysis framework for modeling scene where many users competespectrum resources each other and participate in network collaboration. so, this article appliesgame theory to study the spectrum resource allocation mechanism in the cognitive wirelessnetwork，taking in account the present status of low utilization rate of spectrum resource andthe profit among operators. The main work includes the following two aspects:In the first part, through researching current spectrum sharing algorithm and dynamicspectrum allocation algorithm, we introduce a spectrum allocation algorithm based on biddingauction by using auction mechanism in the economy. In this algorithm, we design effectiveauction allocation rules to allocate discontinuous and continuous spectrum resource.Cognitive users adjust their bidding game strategy according to income function. Simulationresults show that the algorithm improves the spectral efficiency, and satisfy the user’s highbandwidth business requirements.In the second part, we research the adaptive power control algorithm. In order to reducethe user communication power consumption, considering the network load, we put forward akind of power adjustment algorithm based on network load. In this algorithm, on the limitedcondition of interference strength, cognitive users adjust the transmit power and save thehistorical power values in the local database. Simulation results show that the algorithm canspeed up the iteration convergence speed of power adjustment and reduce power consumptionmore effectively.