The Research Of Uav-assisted C-V2X Resource Allocation Algorithm Based On Auction Model

With the rapid development of Cellular-Vehicle to Everything(C-V2X),scenarios such as autonomous driving and platooning of vehicles are gradually becoming a reality.However,the explosive growth of vehicle nodes,the complex and changeable network topology,and the uncertainty of road conditions make the communication connection unstable,making it difficult to meet the high reliability and low latency service requirements of V2X applications.Unmanned aerial vehicles(UAVs)equipped with communication and computing equipment can realize computing offloading or relay forwarding,which can alleviate the problems of unstable communication connections and resource shortages in the V2X.Therefore,UAV-assisted V2X has become a research hotspot in recent years.However,while UAV-assisted V2X technology provides wireless communication services in various V2X scenarios,it also brings a series of problems and challenges such as resource constraints and complex deployment.Due to the limited energy and resources of UAVs,its service time and the number of service users are severely limited.How to reasonably allocate UAV resources under the premise of meeting the needs of vehicle communication,and how to choose more suitable service vehicles,how to plan and design the location of the UAV are problems that must be considered in the UAV-assisted V2X.Therefore,this thesis introduces an auction model,and constructed a utility function by comprehensively considering various factors such as the communication needs of vehicle users,the energy consumption of UAVs,and the utilization of resources.In this thesis,in-depth researches are carried out on the resource allocation in the single-UAV-assisted V2X and the multi-UAV cooperative-assisted V2X.This thesis proposes a resource allocation algorithm for UAV utility optimization based on the auction model in the single UAV-assisted V2X scenario.When a single UAV assists the V2X in computing offloading,how to balance the utility of the UAV and the computing offloading requirements of the vehicle is one of the key issues to be solved.By designing a reasonable auction mechanism,this thesis considers the computing offloading requirements of vehicle nodes and the supply and demand relationship between vehicle nodes and UAVs,and maximize the utility of UAVs by jointly optimizing the selection of service vehicles,the allocation of computing and communication resources of UAV.Aiming at the problem of service vehicle selection,this thesis transforms it into a knapsack problem,and design an improved dynamic programming algorithm based on greedy thinking to solve it.Simulation results show that,compared with the traditional resource allocation algorithm and auction model,the algorithm significantly improves the utility of the UAV under the condition of satisfying the vehicle delay requirement.This thesis proposes a location optimization and resource allocation algorithm based on a multi-round two-way auction model in the multi-UAV-assisted V2X scenario.In the traffic congestion scenario,a large number of vehicles have communication and computing offloading requirements,and the existing resources of the base station are insufficient,so multiple UAVs are used to assist in providing services.Considering the different requirements of typical services in actual scenarios,two types of typical services are modeled,namely,the whole-process uninterrupted computing interaction with transmission rate requirements within the service time and the single computing offload with delay requirements.In order to better balance the interests of buyers and sellers,maximize the utility of the system,and consider the complexity of the resource allocation problem,the overall algorithm is divided into three parts.First,conduct the first round of auction for the communication and computing resources of base stations and UAV swarms,and then use an iterative algorithm to accurately match UAVs with the winning vehicles in the first round of auctions and optimize the location of UAVs.Finally,considering UAV limited resources and coverage,some winning vehicles in the first round of auctions may not be able to obtain UAV services,which resulting in some remaining resources.In order to improve resource utilization,the remaining resources will be allocated to the vehicles through the second auction.Simulation results show that,compared with the traditional auction model and the resource allocation algorithm without location optimization,the proposed algorithm can effectively improve the system utility under the premise of meeting the needs of vehicle business.