Mode Selection And Power Control For D2D System

With the rapid development of wireless network, the integrations of different access networks could take advantages of multiple wireless access technologies and improve both network capacity and the utilization of spectrum resources, thus have become the main trend of communication. Device-to-Device (D2D) communication is one of the key technologies,which allows the direct communication between two devices when they are in a close proximity. D2D communication could improve the utilization of the wireless resources and data transmission rate, and also decrease the transmission power of mobile terminals. Therefore, it is of great importance to investigate D2D communications.In the thesis, the research background are first outlined, anda brief introduction of the state-of-the-art for D2D technology is given, including D2D session management, channel measurement, the end of this part focuses on summing resource management strategies and the corresponding algorithm.Secondly,the thesis presents a mathematical model for multi-user MIMO system, allowing single D2D pair sharing multiple cellular users’ resources. Under this model, a mode-selection strategy for potential D2D pair is designed. Furthermore, the zero forcing interference elimination strategy for D2D link receiver is proposed. Simulation results have shown that the proposed strategies can protect D2D receiver from the interference from multi-user MIMO system, thus it could increase the spectrum efficiency of D2D system, and effectively enhance the resource utilization.Finally, the thesis presents a mathematical model allowing multiple D2D user pairs sharing multiple cellular users’ resources. A potential game model based on non-cooperative game theory is proposed accordingly. It is proved that the model can converge to the unique Nash equilibrium point. Then the thesis designs a corresponding algorithm which allows D2D users and cellular users to choose the appropriate spectrum resources and adjust their power levels until the system converge to the Nash equilibrium point. The simulation results have shown that the proposed algorithms can achieve good performance with relatively low complexity.