Research On Technology Of Sensing And Computing Collaborated Radio Resource Management In Vehicular Networks

With the advancement of modern communication technology,the development of vehicular networks is gradually shifting towards the efficient sensing and transmission of information among humans,vehicles,and roads,in order to support the performance requirements of advanced autonomous driving applications.However,due to the complex urban environment and high-speed mobility of vehicles,maintaining a good quality for the wireless communication link between base stations and vehicles becomes challenging.Additionally,accurately estimating the communication link conditions between vehicles also poses difficulties,resulting in low efficiency of traditional vehicle-side sensing-based radio resource management in vehicular networks and an inability to meet the requirements for transmission rates and latency.This thesis investigates sensing and computing collaborated radio resource management methods in vehicular networks.Based on the radio sensing at the base station and the computational capabilities of communication nodes,the methods aim to establish stable and reliable communication links and select appropriate access modes for vehicles,and then allocate radio resources to the communication links,solving the problems of inefficient radio resource management caused by high mobility and complex environments in vehicular networks.The main research contents and innovations of this thesis include:(1)To address the inefficiency of communication resource allocation caused by high-speed vehicle mobility,a sensing collaborated downlink radio resource management method is proposed for vehicular networks.Specifically,the thesis first estimates the vehicle’s position based on radio sensing at the base station and constructs a joint optimization mathematical model for communication mode selection and radio resource allocation under the orthogonalization of communication and sensing resources.Subsequently,based on the radio sensing results,a vehicle clustering method using Delaunay triangulation is proposed to select communication modes for vehicles.The thesis also introduces transmission demand as a scheduling factor to improve the graph coloring resource allocation algorithm,enabling effective allocation of radio resources.Simulation results show that the proposed algorithm achieves better downlink communication performance gains compared to traditional methods under the same sensing resource allocation ratio.(2)To meet the low-latency requirements of advanced autonomous driving services in vehicular networks,a sensing and computing collaborated wireless network delay optimization method is proposed.Specifically,this thesis first constructs a resource management problem for joint access node selection and radio resource allocation based on vehicle movement information obtained from radio sensing of the base station.Then the thesis proposes both stepwise and joint access node selection resource allocation algorithms based on greedy strategies to reduce the maximum task latency of the system.Simulation results show that when the optimal sensing resources are allocated,the two sensing and computing collaborated radio resource management methods can achieve lower maximum task latency compared to traditional methods that do not consider radio sensing technology.In conclusion,the research achievements in sensing and computing collaborated radio resource management in vehicular networks provide theoretical and technical support for efficient management of radio resources and network latency optimization in vehicular networks.