Research On Dynamic Spectrum Access Algorithm Based On Game Theory In Cognitive Radio Networks

The number of users and the demand for services are increasing,but the available spectrum resources for communication are limited.At the same time,the phenomenon of unreasonable distribution of spectrum resources has become increasingly prominent.How to allocate spectrum resources reasonably has become a major problem that restricts wireless communication technologies.In this context,cognitive radio,as one of the methods to effectively improve the utilization of spectrum resources,has gradually gained attention and been applied in the field of wireless communications.Dynamic spectrum access is one of the key technologies for the development of cognitive radio networks.Cognitive users are required to understand changes in the wireless network environment in a timely manner so as to dynamically adjust the accessed spectrum resources.Different from the existing modes of spectrum direct authorization and static access,the dynamic spectrum access technology utilizes the spectrum sensing and channel detection capabilities of the cognitive radio to dynamically acquire the idle spectrum information of the spectrum resource,thereby selecting and using the idle spectrum according to the sensing result.Accordingly,the using efficiency of spectrum resources is improved.Game theory,as a method of systematically analyzing competitive game strategies,has been gradually applied to the field of wireless communication in recent years.It provides a theoretical analysis framework for cognitive users' spectrum resource competition and strategy selection.In cognitive radio networks,the participants of the game model are cognitive users,whose strategy is the selection of wireless spectrum resources.Based on the game theory,this paper studies the dynamic spectrum access technology in cognitive radio networks.The main work is as follows:Firstly,based on the introduction of dynamic spectrum access technology,the paper analyzes the impact of the uncertainty of the external network environment on the system performance,and proposes a probabilistic based update algorithm for dynamic spectrum access in uncertain wireless environment,assuming that the channel state changes at any time during the model construction.Secondly,in order to facilitate the application of dynamic spectrum access,this paper further expands the system model based on the probabilistic based update algorithm,which not only considers the impact of external network environment on system performance,but also considers the state information of cognitive users.On this basis,the idea of feedback learning is introduced and a feedback learning algorithm based on user state information is proposed.In this algorithm,the location information and communication requirements of the cognitive users will change with certain probabilities respectively.Cognitive users should adjust their channel selection probabilities and selection strategies in time to maximize system performance through feedback learning of spectrum resources competition and utility function valuesIn this paper,the above two algorithms are simulated by MATLAB software platform and the simulation results verify the feasibility of the two algorithms.