Research On The Cooperation Strategies Of D2D Network Based On Dynamic Evolutionary Game

As the key technology of 5G which can improve the spectrum efficiency and network service quality, Device-to-Device technology has aroused comprehensive attention. D2D technology is able to improve network throughput, lower the load of base station and reduce the terminal devices’ transmitting power. However, it also faced with huge challenges. Since D2D communication requires extra resources consume, we need to guarantee the end users has enough incentive to supply a D2D cooperative communication to its neighbors. Generally, an efficient D2D network needs a high cooperation rate among its terminals, which means that most end users willing to sacrifice themselves in order to supply D2D communication to its neighbors.Different from traditional network, D2D network is highly dynamical, we need to simulate this network with a dynamic game model. Since the owner of the D2D terminal is people, they will establish various social connections through social network. So, we need to consider the social relationships and network dynamic when we study the cooperation rate of the D2D network. In order to improve the cooperation rate of the D2D network, we use dynamic evolutionary game theory model the social relationship and network dynamic, with the process of model-analysis-experiment to study the problem. Considering the social relationships between the users and the dynamic of the network, our main works are as follows:(?) We assume the builder will adopt some incentive methods to improve the cooperation rate. Based on Public Good Game, which consider the quality of D2D network as a public good, we establish a dynamic evolutionary game model between the builder and the user. Then we demonstrate the equilibrium of the evolutionary game and find the best incentive method.(?) We also build a dynamic game model between the users based on Prisoner’s Dilemma Game. Then we analysis the influence of moving probability and radius with various simulation environments. The results will helps to build a higher cooperation rate D2D network.