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作 者:Jingming XIA Yufeng LIU Ling TAN
机构地区:[1]School of Artificial Intelligence,Nanjing University of Information Science and Technology,Nanjing 210044,China [2]Engineering Research Center of Digital Forensics Ministry of Education,Nanjing University of Information Science and Technology,Nanjing 210044,China
出 处:《Chinese Journal of Electronics》2024年第3期823-832,共10页电子学报(英文版)
基 金:supported by the National Key Research and Development Program of China (Grant No.2021ZD0112200)。
摘 要:Since the computing capacity and battery energy of unmanned aerial vehicle(UAV)are constrained,UAV as aerial user is hard to handle the high computational complexity and time-sensitive applications.This paper investigates a cellular-connected multi-UAV network supported by mobile edge computing.Multiple UAVs carrying tasks fly from a given initial position to a termination position within a specified time.To handle the large number of tasks carried by UAVs,we propose a energy cost of all UAVs based problem to determine how many tasks should be offloaded to high-altitude balloons(HABs)for computing,where UAV-HAB association,the trajectory of UAV,and calculation task splitting are jointly optimized.However,the formulated problem has nonconvex structure.Hence,an efficient iterative algorithm by applying successive convex approximation and the block coordinate descent methods is put forward.Specifically,in each iteration,the UAV-HAB association,calculation task splitting,and UAV trajectory are alternately optimized.Especially,for the nonconvex UAV trajectory optimization problem,an approximate convex optimization problem is settled.The numerical results indicate that the scheme of this paper proposed is guaranteed to converge and also significantly reduces the entire power consumption of all UAVs compared to the benchmark schemes.
关 键 词:Unmanned aerial vehicles High-altitude balloons Mobile edge computing Task splitting Block coordinate descent
分 类 号:TN929.5[电子电信—通信与信息系统] V279[电子电信—信息与通信工程] V249[航空宇航科学与技术—飞行器设计]
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