Cognitive Radio Spectrum Sharing Technology Based On Game Theory

With the rapid development of wireless communication technology in the recent decades,the demand of wireless spectrum resources has become very strong.Spectrum efficient is not high because of the fixed spectrum allocation policy. Wireless spectrum is a non-renewable resources.Cognitive radio is a new type of wireless communication technology which is proposed in recent years.it can take advantage of secondary users through spectrum sensing function,which can use the idle spectrum resources by dynamic adaptive, thus cognitive radio generate and develop very quickly. It can solve the low spectrum utilization by dynamic spectrum access technology and other related technology of spectrum sharing which are developed recently.Game Theory, also named decision theory, which is a branch of applied mathematics but also is an important subject of operations.Game Theory play important role in a competitive and decision issues.It exists widespread competitive between communication'users in wireless communications systems, so game theory can be well applied to the wireless communications systems.In this paper,I proposed a repeated game algorithm for the dynamic spectrum access of spectrum sharing, we studied the dynamic spectrum access by using continuous-time Markov time (CTMC).We has also studied spectrum access technology through self-learning of repeated game framework. The study of cognitive radio technology focus on dynamic spectrum access which belong to spectrum sharing.Due to the multiple secondary users competitive of spectrum sharing,we have proposed a dynamic game model.Namely:secondary users can adjust their strategies repeated according to the demand of the size spectrum.It has studied the local and global stability of spectrum sharing. It establish the static and dynamic game model,this paper use Nash equilibrium to analysis the static and dynamic game model, which is useful for the next generation cognitive radio network.Numerical results show that:Self-learning algorithm can achieve fast convergence which can improve the efficiency of game.In the dynamic spectrum access networks it is particularly useful for secondary users to cooperation.For the competition spectrum sharing, numerical results show that Nash equilibrium solution can achieve a balanced solution for the static and dynamic game.As the change of the learning rate and channel quality which will produce instability.