Research On Channel Prediction And Resource Scheduling Method In LTE-V System

Vehicle to vehicle(V2V)is one of the key technologies in Internet of Vehicles(IoVs).When vehicles broadcast interactive communication messages,they have higher requirements on the reliability of the communication link.Reasonable resource scheduling largely determines the reliability of communication links.With the popularization of Long Term Evolution(LTE)networks,research on time-frequency resource allocation under this network architecture has practical needs and theoretical significance.To this end,this paper studies the centralized resource scheduling method based on the Long Term Evolution-Vehicle(LTE-V)standard.The main research contents of the paper include:First of all,this paper aims at the scenario of vehicles broadcasting data in dense road traffic.In order to ensure the reliability of data transmission links and avoid interference between vehicles,a resource scheduling optimization model based on the LTE-V system is constructed.Four types of constraints are defined:avoiding that the vehicles within the reachable communication range are assigned to subchannels in the same subframe;avoiding the vehicles within twice the reachable communication range sharing the same resource;avoiding the allocation of resources to vehicles over time;ensure the reliability of the transmission link by judging the signal-to-interference and noise ratio(SINR).The thesis transforms the resource scheduling problem into an optimized model that maximizes the utilization rate of time-frequency resources.Finally,a Minimizing Increment of Spectral Radius Based(MISRBased)algorithm is used to compare with the other two algorithms through simulation.The experimental results prove that the algorithm used in this thesis has higher resource utilization rate in dense scenarios that require higher data transmission reliability.Secondly,combined with the actual scenario of continuous vehicle movement and real-time channel changes,a method for predicting channel parameters under vehicle wireless channel conditions is proposed based on vehicle movement models and timevarying parameter channel models.After analyzing the channel function between vehicles,two time-varying parameters affecting link reliability,the distance between vehicles and the path loss index are obtained.This method estimates the position of the vehicle based on the vehicle’s movement model and uses the Wiener predictor method to predict future data based on the obtained historical parameters,thereby obtaining vehicle and channel information for the next scheduling cycle.Simulation results show that when the prediction method is used,the result of resource scheduling can effectively increase the transmission capacity of the network.