People’s strong desire for convenient communication promoted the rapid development of wireless communication technologies, more and more new technologies and applications emerged. By parallel signal transmission over multiple sub-carriers, OFDM technology can improve spectral efficiency and combat multi-path fading effectively, which has made it to be a preferred physical layer transmission technology in the next-generation wireless communication systems. Besides, cooperative communication technology can have spatial diversity gain by virtual MIMO, which is another way of practical use of MIMO technologies. And furthermore, cognitive radio technology can achieve dynamic spectrum sharing, which is a fundamental change in the way of wireless resource allocation and utilization. Finally, resource allocation and management is an eternal theme of wireless communications, how to effectively manage the scarce radio resources in new technologies and new systems has become an important problem to be resolved in future wireless communication systems.To solve the new problems, new research methods are created. Cooperative communication technology introduces the interaction between network users, cognitive radio technology enables network users with cognitive intelligence, and the competition and cooperation in resource allocation have been of great concern. Thus, a powerful mathematical tool in the field of economics——Game Theory, is introduced to analyze the interactive decision-making behavior of network users in radio resource allocations.In this thesis, for an OFDMA-based cooperative communication system and for a cognitive radio system, we introduce the game theory to analyze the resource allocation optimization in these systems,ⅰ.e., new schemes are proposed, theory analysis and numerical results are provided. In summary, the main contributions of this thesis include:1. In order to improve the efficiency and fairness of radio resource utilization, a scheme of dynamic cooperative sub-carrier and power allocation based on Nash bargaining solution (NBS_DCSPA) is proposed in the uplink of a three-node symmetric cooperative orthogonal frequency division multiple access (OFDMA) system.In the proposed NBS_DCSPA scheme, resource allocation problem is formulated as a two-person sub-carrier and power allocation bargaining game (SPABG) to maximize the system utility, under the constraints of each user’s maximal power and minimal rate, while considering the fairness between the two user nodes. Firstly, the equivalent direct channel gain of the relay link is introduced to decide the transmission mode of each sub-carrier. Then, all sub-carriers can be dynamically allocated to each user in terms of their selected transmission mode. After that, the adaptive power allocation scheme combined with dynamic sub-carrier allocation is optimized according to NBS. Finally, computer simulation is conducted to show the efficiency and fairness performance of the proposed NBS_DCSPA scheme.2. Based on GNBS (Generalized Nash Bargaining Solution) and RKSBS (Raiffa-Kalai-Smorodinsky Bargaining Solution), for an OFDMA-based cognitive radio system two dynamic sub-carrier allocation schemes are proposed, which can make fair sub-carrier allocation for two secondary networks with different number of users and different service requirement.A first-order two-state Markov chain model is used to reflect the activity of primary users over sub-carriers, and a discount factor is introduced to reflect the rate loss of secondary users which is caused by primary user activities. Based on cooperative game theory, the sub-carrier allocation for two networks is modeled as a bargaining game model, and two dynamic sub-carrier allocation schemes are proposed, which is based on GNBS and RKSBS. In the proposed schemes, the sub-carrier allocation for the users within a network is modeled as an assignment problem,ⅰ.e., sub-carriers are allocated to secondary users based on an improved Hungary algorithm. Numerical results show that the two proposed schemes can make fair sub-carrier allocation for the networks with different number of users and different service requirements. Considering the activity of primary users, the two proposed schemes can significantly outperform the resource allocation scheme which is based on Max-Min fair algorithm, as the former can further improve fairness in the allocation of time-varying resources.3. For an OFDMA-based cognitive radio system, we propose a multiple winner sub-carrier auction game which is based on VCG (Vickrey-Clarke-Groves) mechanism. Combined with iterative power allocation, the game can achieve spatial frequency multiplexing, and maximize the sum-rate of secondary networks.The game design considers the spatial frequency multiplexing in an OFDMA-based cognitive radio system, the conflict between the cognitive radio links over sub-carriers is described by interference criteria and adjacency matrix, thus the optimization problem to maximize the sum-rate of secondary networks is modeled as a multiple winner sub-carrier auction game which is based on VCG mechanism, the optimal solution can be obtained by solving a binary integer planning problem for each of the sub-carriers. Based on sub-carrier auction and combined with power allocation, the throughput of secondary networks is further increased. The optimal power allocation to maximize the sum-rate of interference channels is modeled as a non-cooperative game, and the optimal power allocation is found by a pricing-based iterative water-filling algorithm. Numerical results show that the proposed sub-carrier auction game which is combined with power allocation can effectively improve the utilization efficiency of the resources of cognitive radio networks. |