Power Control And Resource Allocation Using Game Theory In Cognitive Radio Networks

In cognitive radio networks where spectrum can be shared, unlicensed users(secondary users) are allowed to use licensed users'(primary users) spectrum resource to enhance the spectrum efficiency. Due to the fixed spectrum resource, how to develop efficient allocation schemes is very important. Game theory is an efficient mathematical tool, which has been used to handle the resource allocation problems in cognitive radio networks. This thesis gives the latest development of power control based game theory and spectrum sharing analysis of the cognitive radio technology, then investigates the following three research works:Game theory is used to control users' transmission power in recent literatures, which indicates that the efficient utility is related with the modulation of radio access, however, this kind of efficient utility has high bit error rate and complexity. Therefore, this thesis defines a new efficiency function regardless of the modulation, in order to reduce the complexity. After that, according to users' signal to interference plus noise ratio(SINR) and generated interference, the model develops an efficient punishment parameter and utility function to ganrantee the fairness amog the secondary users. In addition, this chapter also presents the proof of the existence of Nash Equilibrium, and an iterative algorithm for achieving Nash Equilibrium point is given finally. At last, simulation results indicate that the proposed game not only enhances the secondary users' throughput, but also guarantees their fairness.The interference and outage probability constraints play important roles in resource allocation in cognitive radio networks, a Stackelberg game is formulated to control users' transmission power in this thesis. First, a hierarchical competition model is built, where primary users and secondary users are considered to be leaders and followers, respectively. As leaders, primary users try to maximize their own utility, through setting interference price to secondary users, and secondary users pay for primary users when they use the spectrum of primary users. Then, a comprehensive investigation of game model is developed with interference and outage probability constraints, where new utility functions are developed. Then, the global efficiency of the Stackelberg equilibrium is analyzed, the chapter also uses the Lagrange dual decomposition method to compute the optimal transmission power, and an efficient iterative algorithm is developed to update power, as well as its complexity is also discussed. Simulation results analyze the given scheme that the developed scheme can enhance the networks' throughout as well as reduce the outage probability with low complexity.Recently, few works have investigated multiple primary service providers compete with each other to share their spectrum resource, this thesis develops a new non-cooperative game spectrum allocation scheme. This model considers three primary service providers and one secondary provider in spectrum sharing networks, primary service providers compete with each other to sell their spectrum to a secondary provider, and then to maximize their individual profit by dynamically updating their selling prices. In this system, the Bertrand game theory is applied to investigate the price game strategy between primary service providers and a secondary service provider. In this Bertrand competition model, an improved pricing function is developed for both primary and secondary service providers, in order to guarantee the system's fairness and make sure the satisfaction level among providers. Then, the convergence of the scheme is proved, and the impact of the different number of primary users and learning factors on the proposed game is analyzed. Simulation results indicate that the effectiveness of the proposed algorithm in this thesis.