Resource Allocation Algorithm Based On D2D Communication In Internet Of Vehicles

Recently,Internet of Vehicles(IoV)technology has developed rapidly integrated with 5G,artificial intelligence,cloud computing,big data and other advanced technologies.The technique of IoV is an important scenario of 5G vertical applications.As a key technology of IoV,Device to Device(D2D)communication technology has also received more and more attention.In the mobile communication scenario where traditional cellular network and D2D communication technology coexist,D2D communication technology supports direct connection of end users and allows D2D Users(DUEs)users and Cellular User(CUE)to share wireless spectrum resources.It can reduce the data processing volume of Base Station(BS),improve the communication quality of Telematics system and enhance the utilization of wireless communication resources.However,D2D communication technology also brings complex interference problems to users who multiplex the same sub-channel.Optimizing the system capacity while coordinating the interference between users has become a hot issue to be solved in the current D2D communication technology.To address this problem,this paper investigates the resource allocation strategy in the convergent communication scenario from the perspectives of D2D communication scenario,power control,and channel matching.(1)In highway D2D communication scenarios,a D2D resource allocation strategy based on Gray Wolf optimization and Hungarian algorithm is proposed to address the problems of limited spectrum resources,high system interference,and communication quality of DUEs.Under the premise of ensuring the communication quality of CUE as well as DUEs,the model first uses Gray Wolf optimization to obtain the optimal transmit power for each DUE,and then uses the Hungarian algorithm to achieve the optimal channel matching between DUEs and CUEs to maximize the capacity and of DUEs.Simulation results show that the algorithm can effectively improve the total capacity of DUEs while individual DUEs can also obtain high maximum and minimum capacities.(2)In dense vehicle D2D communication scenarios,aiming at the problems of high vehicle density,low communication resource utilization and poor communication quality of DUEs,a D2D resource allocation strategy based on clustering and Stackelberg game is proposed.It solves the problems of the DUE power allocation and channel matching.First,based on the principle of minimum interference between DUEs within each channel,all DUEs are clustered in the model.Then,for the CUE and DUE clusters,a one-to-many Stackelberg master-slave game model is constructed to optimize the transmit power of each DUE by iterative updating of multiplexed link interference parameters and intra-cluster interference parameters.Finally,the Hungarian algorithm is used to achieve the best channel matching between DUE clusters and CUEs to maximize the capacity and of DUEs.The simulation results show that the algorithm can effectively improve the total capacity of DUEs.