Research On Device To Device Wireless Resource Allocation Algorithm For Internet Of Vehicles

With the development of technology,we are about to enter the 5G era.Device-to-Device(D2D)technology is an important part of 5G,and it has become a research hot spot.Compared with other technologies,D2 D has great advantages in the situation of short distance and small amount of data.At the same time,vehicles have become an important mode of transportation of peoples' daily life.The road safety problem caused by vehicle driving has always been the focus of social attention.Applying D2 D technology to the Internet of Vehicles can solve many traffic safety problems,such as traffic jams,vehicle collisions,and so on.Applying D2 D technology to the Internet of Vehicles must first solve the problem of resource allocation,which is also the research direction of this thesis.Many traditional resource allocation algorithms are dedicated to optimizing system capacity or quality of service,but the Internet of Vehicles scenario has higher requirements for allocation delay and allocation success rate.Therefore,on the basis of ensuring the system capacity,this thesis will design an algorithm that can not only improve the allocation success rate but also reduce the allocation delay and the SINR feedback times to ensure road safety and improve the quality of human life.Based on the analysis of existing resource allocation algorithms such as the greedy algorithm and the graph coloring algorithm,the thesis analyzes these algorithms.The results show that the graph coloring algorithm performs well in system capacity and allocation delay,but the SINR feedback times are high.Moreover,the allocation success rate needs to be improved.To this end,this thesis designs a D2 D wireless resource allocation algorithm based on location partitioning.The simulation results show that when the number of D2 D users is small,the algorithm has a slightly larger allocation delay than the graph coloring algorithm,but the allocation success rate is greatly improved,and the SINR feedback times are also significantly reduced.However,when the number of D2 D users is large,the allocation success rate of the location partitioning algorithm decreases significantly,and such performance is insufficient to meet the requirements of the Internet of Vehicles scenario.In order to further optimize the performance of the location partitioning algorithm,this thesis designs a clustered D2 D radio resource allocation algorithm based on location partitioning.Based on the location partitioning algorithm,the algorithm divides the roads at a certain distance to realize clustering of D2 D users.The simulation results show that compared with other algorithms,the clustering algorithm performs better in terms of allocation delay,allocation success rate and the SINR feedback times.Therefore,the clustered location-based partitioning D2 D radio resource allocation algorithm is more suitable for the Internet of Vehicles scenario.