Research On Cellular-Connected UAV:Trajectory Optimization And Computation Offloading Scheduling

In recent years,thanks to the support of high-speed,low-latency and other communication characteristics in the 5G era,cellular-connected UAVs,which are employed into existing cellular networks as aerial mobile users,have attracted extensive attention in many fields such as agriculture plant protection,exploration inspection and many other fields.Due to the limited computation capacity of UAVs,mobile edge com-puting(MEC)technology has been innovatively applied to the cellular-connected UAVs’ communication system.UAVs can offload their tasks to ground base stations(GBSs)equipped with MEC servers for remote computing,so as to cope with real-time observation,video recognition and other computation-intensive tasks.For the MEC-enabled cellular-connected UAVs’ communication system,how to design the UAV’s trajectory,as well as allocate the calculation and communication resources to improve the system performance is one of the important issues to be studied,although some studies have already discussed the above issues,but there are still some deficiencies:1)insufficient consideration of secure communication problem;2)the assumptions of the UAV task scenarios are relatively simple.To tackle the above problems,this article deeply studies the joint optimization of UAV trajectory and computation offloading scheduling for the MEC-enabled cellular-connected UAVs’ communication system,mainly including the following two aspects:1)Aiming at the problem of insufficient consideration of secure communication in existing studies,this article considered a secure MEC-enabled cellular-connected UAVs’ system,and modeled the problem of minimizing the total energy consumption of UAV in the presence of eavesdroppers.Then,this article jointly optimized the UAV trajectory,transmit power allocation,UAV-GBS association,and computation task allocation.Finally,the original nonconvex problem was solved by the block coordinate descent algorithm and the successive convex appro-ximation technology.Numerical results show that the proposed design effectively saves UAV’s energy consumption.2)Aiming at the problem that the assumptions about UAV task scenarios in existing studies are relatively simple,and it is difficult to meet the needs of actual application scenarios,this article innovatively maked assumptions and modelings about cellular-connected UAV performing complex mission scenarios that are similar to first collection and then calculation.Then,the problem of minimizing the mission time of the UAV in such above scenario was studied.Finally,the successive convex approximation technology was used to optimize the UAV path,the during period of path section,and the computation offloading time between the UAV and GBSs.Numerical results show that the proposed design can effectively shorten UAV’s mission completion time.