Robust Power Control For Internet Of Vehicles Under Uncertain Channel Environment

The scarcity of wireless communication resources and the increasing number of vehicles have made the rational use of spectrum resources in Internet of Vehicles(Io V)communication a hot research topic.Compared with Ad-hoc and traditional cellular network communication,the device to device communication method is more in line with the short distance transmission characteristics of the Io V.The vehicle to vehicle communication method and channel reuse technology in the IoV can effectively alleviate the scarcity of wireless resources.However,reuse technology will bring complex interference between users,so interference management is particularly important in Io V communication.In addition,the communication environmen is rapid change when the vehicle is driving,which makes the channel gain uncertain.More accurate channel gain descriptions and the handling of channel uncertainty are also particularly important.Based on vehicle location information,road conditions,communication users,and base station(BS)location information,the channel gain of a vehicle to vehicle dynamic communication link is described.The uncertainty of the channel gain makes it difficult to solve the optimal power.This paper uses robust power control to achieve the optimal power.Firstly,the channel state information(CSI)includins the problem of delay in the vehicle to vehicle link and the vehicle to person link.A dynamic communication link model including communication delay time and vehicle speed information is established.And the information delay and dynamic communication environment in the vehicle to vehicle link lead to the uncertainty of the channel gain.Based on this,an optimization problem that takes the maximum throughput as the target under uncertain constraints.For the uncertainty of the channel,two error models are used to complete the transformation of the uncertainty constraints.For non-convex problems,the convex approximation is completed by continuous convex approximation.Finally,a robust power control algorithm is used to solve the optimal power.Secondly,in order to make the channel gain description more dynamic,vehicle dynamic information is added to the channel gain description.A one-to-one reuse methodis adopted to solve the problem of low spectrum utilization,which can reduce interference and improve communication quality.With the system energy efficiency maximization as the optimization goal,the channel uncertainty constraint is considered.Channel uncertainty is transformed through probability constraints.The optimal power is solved using a robust power control algorithm.The objective function non-convex problem is solved by fractional programming,and energy efficiency comparison under three matching strategies is achieved.Finally,because 5G has fast transmission rates and short delays,it is more in line with the requirements of the IoV scene.Therefore,the IoV scene is extended in the 5G environment.And the serial interference cancellation(SIC)technology in 5G technology can further improve the communication quality.Taking the maximization of throughput as the optimization goal,the optimization problem under uncertain constraints is considered.The uncertainty of the channel is transformed by a probability constraint.Robust power control is used to solve the optimal power.And the maximum match of throughput is achieved by the Hungarian algorithm with the lowest algorithm complexity.