Research On Mobile Edge Computing System With UAV Based On Ground Cooperation

The rapid development of science and technology has brought about the rapid development of wireless communication.In the scenario of unmanned aerial vehicle communication,users are no longer satisfied with the simple point-to-point exchange of information.At the same time,a large number of computing-intensive applications emerge as the times require,which brings many challenges to UAV communication.Mobile edge computing(MEC)technology seeks technological innovations and breakthroughs for drone communication scenarios.The device equipped with the mobile edge computing server can help the communication terminal to offload some tasks to the edge of the mobile network when the communication task is too large,thereby relieving the communication pressure and improving the computing performance of the communication network.This paper studies a cellular-connected UAV communication system in which the UAV is associated with the terrestrial base station(TBS)to realize the offloading of computing tasks.With constant resource constraints,the energy consumption of all UAVs is a very meaningful research direction.On the other hand,this paper also considers the extension of the single-UAV communication system to multiple UAVs,and in order to allow the terrestrial base station to provide efficient computing offloading services for UAVs as much as possible,we discuss how to maximize the sum bits offloaded from UAV to the TBS,The main research contents are as follows:1.A cooperative communication scenario between UAV and terrestrial base station is studied.The UAV performs its own task and there are several ground base stations in its coverage area Through the research on the terrestrial base station based on mobile edge computing to help the single UAV communication system to offload computing tasks,considering the propulsion energy consumption of the rotor UAV and its own computing energy consumption,the total energy consumption of the UAV in the communication system is calculated.The problem of minimizing the total energy consumption of the UAV in the communication system is solved.The initial flight trajectory from the starting point to the target point is preset for the UAV.Here,the discrete initialization method based on the TSP path is used,and the TDMA communication method is used.Considering that it is not suitable to completely migrate computing tasks to the cloud platform in practical scenarios,a resource partitioning strategy is proposed.Migrate part of the mission to TBS for computation and the other part to do local computation on the drone.The goal is to minimize UAV energy consumption by jointly optimizing time,resource allocation,UAV trajectory,and bit allocation under UAV maneuverability and TBS energy budget constraints.By using the block coordinate descent(BCD)method and the continuous convex approximation(SCA)method,the problem is decomposed into multiple sub-problems,and each sub-problem is transformed into a solvable convex problem for alternate iterative optimization solutions.The simulation results are analyzed to verify the effectiveness of the proposed scheme and algorithm.2.Consider another cellular interconnected UAV communication system,which consists of multiple rotary wing UAVs and multiple terrestrial base stations within their coverage.The multiple UAVs in the scene also have their own communication tasks,and in order to allow the ground base stations within the coverage of all UAVs to provide efficient computing offload services for each UAV as much as possible,the number of transmitted bits offloaded to the terrestrial base station is studied.Under the premise of ensuring the constraints of UAV battery capacity and quality of service,as well as preventing demand conflicts and collisions of multiple UAVs,it is formed to maximize the number of unloaded bits from UAVs to terrestrial base stations.Optimization problem of upload power and associated scheduling of UAVs to terrestrial base stations.The constraint in this problem involves 0-1 integer variables,which can’t be solved directly.It needs to be relaxed first.In order to solve this optimization problem,the problem can be decomposed into multiple sub-problems by the method of block coordinate descent(BCD),each sub-problem is solved by the method of integer programming and continuous convex approximation(SCA),and the multivariate fixed iterative algorithm is used to solve the overall problem.problem to optimize.Finally,the effectiveness of the scheme is verified by the analysis of the simulation results.