An Offloading Optimization Scheme for Multi-UAV Aided Network in Mobile Computing

被引：6

作者：

Gao, Ang ^{[1
,2
]}

Wang, Qi ^{[1
]}

Hu, Yansu ^{[3
]}

Duan, Weijun ^{[1
,2
]}

机构：

[1] Northwestern Polytech Univ, Sch Elect & Informat, Xian 710072, Peoples R China

[2] NPU, Yangtze River Delta Res Inst, Taicang 215400, Peoples R China

[3] Changan Univ, Sch Elect & Control, Xian 710064, Peoples R China

来源：

2020 16TH INTERNATIONAL WIRELESS COMMUNICATIONS & MOBILE COMPUTING CONFERENCE, IWCMC | 2020年

基金：

中国博士后科学基金;

关键词：

Computation Offloading; Quality of Experience; Multi-UAV; Energy Efficiency; HJPQ; Double DQN;

D O I：

10.1109/IWCMC48107.2020.9148136

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Multiple unmanned aerial vehicles (UAVs) can act as intermediate relay for their flexible mobility. In mobile cloud computing (MCC) and mobile edge computing (MEC), UAVs assist ground user equipments (UEs) to offload traffic to cloudlet or cloud. In this scenario, different UEs may have different quality of experience (QoE) requirement. Moreover, the endurance flying as well as battery limitation of UAVs and UEs make this offloading architecture power sensitive. Thus, UEs' QoE, as well as overall system power consumption should be well-balanced by the MIMO channel assignment and UAVs' trajectory plan. This paper formulates such issue as a non-convex and mixed-integer optimization problem, and further proposes a heuristic joint power and QoE (HJPQ) algorithm to solve it. The numeral simulations reveal the algorithm has great QoE performance with high energy efficiency in different conditions.

引用

页码：1468 / 1473

页数：6

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