Research On Channel Access And Cross-layer Optimization Of Internet Of Vehicles

With the fast development of the economy,the vehicle population in China is increasing rapidly,which brings convenience to people.But meanwhile,it increases traffic congestion,making the traffic safety problem more serious.As an important branch of Internet of Things(Io T),the Internet of Vehicles(Io V)is regarded as the foundation of Intelligent Transportation System(ITS)in the future and plays a key role in improving road safety.However,due to the mobility of vehicles,the topology of Io V changes drastically,and the channel resources are unbalanced,which brings a much-hidden risk to the real-time communication and reliability of Io V.Compared with other wireless communication networks,link-time between vehicle nodes in Io V is short,so improving channel access efficiency and concurrent communication capability are crucial to communication quality.Therefore,how to ensure the rapid update requirement of the safety-related information between vehicles,and reduce the communication delay through increasing the wireless channel utilization,have become urgent issues to be resolved.Most of the researches were focused on routing optimization algorithm,channel access strategy and resource scheduling,which are close to theoretical optimum.In view of the above,the characteristics of safety-related information are analyzed,starting with three scenarios of the vehicle to base station,vehicle to vehicle,and multi-base station,to optimize the channel access method based on the concept of cross-layer optimization in this dissertation.Combing vehicular mobility and communication load prediction to realize the application of interference management and channel sharing on Io V,the channel utilization and channel concurrent access capability are improved,and the robustness of the optimization method is ensured.The main contents of this dissertation are as follows:1)Research on the optimization algorithm of Interference Alignment(IA)between the car and the base stationMulti-Input Multi-Output(MIMO)communication system causes multi-user interference between vehicles,and IA,a new technology of interference management,can effectively address this problem and improve wireless access.To apply IA to optimize the channel access of Io V,a cross-layer optimization method is presented,which adopts Time Division Multiple Access(TDMA)to manage the physical layer access of the vehicle.Based on the characteristics of safety-related service,vehicle-to-vehicle and vehicle-to-base station IA communication models based on a multi-hop routing model are constructed.Thus the optimization problem of minimizing the number of time slots is proposed to reduce communication delay.Finally,the effects of this method are analyzed through simulation.The results show that this method can reduce the number of time slots required for communication,thereby reducing communication delay for 15%.2)Research on cross-layer optimization of IA in Vehicular Ad-hoc Networks(VANETs)Applying IA in vehicle to base station scenario can reduce the time required for the interaction of safety-related information between vehicles.Nevertheless,there are also some situations without base stations or RSUs in VANETs.Therefore,multi-antenna vehicles are chosen as dynamic base stations to adopt IA in Vehicle-to-Vehicle(V2V),by which the concurrency and real-time performance can be improved.To overcome the unstable factors caused by the rapid movement of vehicles to the IA,a state transition matrix algorithm and a Markov Decision Process(MDP)dynamic base station model are formulated to guide the multi-antenna vehicle to determine whether it can act as a dynamic base station depending on the status of the surrounding vehicles.Then the optimization goal of minimizing the number of time slots required for information exchange is put forward.Finally,experiments verify that,folloing the MDP strategy,the dynamic base station can switch in time which provides stable IA service for surrounding vehicles,and reduces the communication delay in VANETs for 40% compared with No IA.3)Research on hybrid network interference alignment and channel sharingWith the increase in the number of vehicles and the requirements of communication service,the Io V channel resource is accordingly finite.As the access point of the regional communication network,the service radius of the base station is small,but there are considerable interferences between adjacent vehicles.Moreover,due to the traffic,the communication load is uneven in the region.Consequently,a hybrid network channel sharing method is proposed to balance the communication load of the entire network.To reduce the impact of traffic flow fluctuations on the real-time and stability of the sharing algorithm,a traffic load prediction model is constructed to predict the communication load to dynamically adjust the base station channel sharing strategy.Finally,the simulation results show that the channel sharing algorithm improves the vehicle communication rate in high-load areas while a limited impact on the communication rate of the shared channel can be maintained.The channel access management method is built based on cross-layer optimization by combing the characteristics of communication in Io V,safety-related information and the mobility of vehicles,and by introducing IA and channel sharing in different scenarios,the concurrent communication capability and channel utilization are improved within the limited spectrum resources,while the vehicle communication rate is improved and the communication delay is reduced.