Research On Power Control Algorithm Based On Game Theory In Cognitive Radio System

With the rapid development of wireless communication technology and the increasing need of wireless communication, the shortage of radio spectrum resources becomes more and more serious. Cognitive radio technology is considered to be an effective scheme to solve this problem. Many researchers and institutions around the world have comprehensively and deeply studied this technology. Many new research achievements have been obtained in the areas of spectrum sensing, spectrum allocation and power control of cognitive radio. The research of power control algorithms based on non-cooperative games in cognitive radio is of important guiding significance for resolving the problem of power control in cognitive radio.The research scheme of combining theoretical analysis and numerical simulation is adopted to improve the power control in cognitive radio. The existence of Nash Equilibrium points is proved for the models of non-cooperative power control game model. The effectiveness in constraining users’ transmitting power of two existing algorithms are evaluated through simulations, and the properties in transmitting power of the simulation results are compared and analyzed.In order to improve the performance of original power control game algorithms, a new normalized utility function is proposed for the purpose of application to enhance the convergence rate of the game algorithm and reduce the transmitting power of all the cognitive users. The existence and uniqueness of the Nash Equilibrium (NE) in the proposed utility function are proved by the principle of game theory and the corresponding optimizations. The problem is solved recursively, and the convergence of the recursive algorithm is proved under R. D. Yates’framework. In different scenarios regarding the distribution of users, the properties of the proposed algorithm (such as convergence rate, transmitting power and signal-to-interference ratio) are evaluated through simulations, and compared with those of the SINR balancing algorithm, Koskie-Gajic algorithm, and NPGP-IL algorithm. Simulation results show that, whether in the cases of fixed users, or in the cases of randomly-distributed users, the properties in transmitting power and signal-to-interference ratio of the proposed game algorithm are better than those of the original game algorithms. The proposed game algorithm has an obvious effect in reducing power consumption and saving energy.