Research On Resource Sharing Algorithm Of Cellular Vehicular Network Based On D2D Communication

In the current era of rapid development of information,automobile has become an increasingly important travel tool.In order to meet the needs of intelligent driving,vehicle entertainment and safe travel,vehicles must interact with the outside world.This data transmission interaction process is called vehicle-to-everything(V2X).The rapid development of intelligent transportation puts forward higher requirements for the quality and speed of vehicular communication.The traditional centralized networking through the base station cannot meet the explosive growth of the demand for communication and spectrum resources of the vehiclular network.Therefore,after the analysis of experts and scholars,the device to device(D2D)communication mode is considered to be introduced into the vehiclular communication.The paper focuses on the resource sharing of vehicle-to-vehicle(V2V)communication in vehiclular network.The main research contents are as follows:Firstly,combined with the current situation of spectrum resource shortage and the requirements of low delay and high reliability in vehiclular network,aiming at the spectrum sharing problem of V2V pairs in vehiclular network,a spectrum sharing algorithm considering the joint optimization of V2V communication mode selection and resource allocation is proposed to maximize the total throughput of V2V pairs in vehiclular network on the premise of ensuring the communication quality of cellular users and V2V pairs.Firstly,based on the three modes of D2D communication,namely cellular mode,dedicated mode and reuse mode,this paper proposes a mode selection scheme based on distance detection and channel state information(CSI)sensing in vehicular network.In reuse mode,V2V pairs share spectrum resources with cellular users.In order to achieve the optimal channel resources allocation of V2V pairs in reuse mode,the resource sharing problem in the reuse mode is modeled as a game theory problem,and the Nash equilibrium point of non-cooperative game is used to find the optimal resource allocation strategy to maximize the V2V throughput.Simulation results show that the proposed joint optimization algorithm of mode selection and resource allocation can ensure the communication quality of cellular users and V2V pairs,realize the sharing of spectrum resources between different users and improve the spectrum utilization.In reuse mode,there is much co-frequency interference between cellular users and V2V pairs due to resource reusing.Aiming at the interference caused by resource reuse in V2V communication,a multi-agent reinforcement learning resource allocation algorithm based on game theory is proposed.The algorithm combines game theory and Q-learning to optimize the power control and channel allocation of V2V pair,aiming to maximize the total throughput of cellular users and V2V pairs.Simulation results show that the proposed multi-agent reinforcement learning resource allocation algorithm can ensure the communication quality of cellular users and V2V pairs,coordinate the interference,maximize the total throughput of the network system.