Joint Placement and Resource Allocation for UAV-Assisted Mobile Edge Computing Networks with URLLC

doi:10.12142/ZTECOM.202002007

ZTE Communications ›› 2020, Vol. 18 ›› Issue (2): 49-56.DOI: 10.12142/ZTECOM.202002007

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Joint Placement and Resource Allocation for UAV-Assisted Mobile Edge Computing Networks with URLLC

ZHANG Pengyu¹, XIE Lifeng¹, XU Jie²()

^1.School of Information Engineering, Guangdong University of Technology, Guangzhou, Guangdong 510006, China
^2.Future Network of Intelligence Institute and School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen，Guangdong 518172, China

Received:2019-04-27 Online:2020-06-25 Published:2020-08-07
About author:ZHANG Pengyu received the B.E. degree from Guangdong University of Technology， China in 2017. He is pursuing his master degree in the School of Information Engineering, Guangdong University of Technology. His research interests include UAV communications, mobile edge computing, and ultra-reliable and low-latency communications.|XIE Lifeng received the B.E. degree from Guangdong University of Technology,China in 2016. He is currently a Ph.D. candidate in the School of Information Engineering, Guangdong University of Technology. His research interests include energy harvesting in wireless communications, wireless information and power transfer, and UAV communications.|XU Jie (xujie@cuhk.edu.cn) received the B.E. and Ph.D. degrees from University of Science and Technology of China in 2007 and 2012 respectively. From 2012 to 2014, he was a Research Fellow with the Department of Electrical and Computer Engineering, National University of Singapore. From 2015 to 2016, he was a post-doctoral Research Fellow with the Engineering Systems and Design Pillar, Singapore University of Technology and Design. From 2016 to 2019, he was a professor with the School of Information Engineering, Guangdong University of Technology, China. He is currently an associate professor with the School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, China. His research interests include energy efficiency and energy harvesting in wireless communications, wireless information and power transfer, UAV communications, and mobile edge computing and learning.
Supported by:
the Key Area R&D Program of Guangdong Province with(2018B030338001);the National Key R&D Program of China with(2018YFB1800800);Natural Science Foundation of China with(61871137);the Guangdong Province Basic Research Program (Natural Science) with(2018KZDXM028);Guangdong Zhujiang Project(2017ZT07X152);Shenzhen Key Lab Fund(ZDSYS201707251409055)

Abstract

Abstract:

This paper investigates an unmanned aerial vehicle (UAV) assisted mobile edge computing (MEC) network with ultra-reliable and low-latency communications (URLLC), in which a UAV acts as an aerial edge server to collect information from a set of sensors and send the processed data (e.g., command signals) to the corresponding actuators. In particular, we focus on the round-trip URLLC from the sensors to the UAV and to the actuators in the network. By considering the finite block-length codes, our objective is to minimize the maximum end-to-end packet error rate (PER) of these sensor-actuator pairs, by jointly optimizing the UAV’s placement location and transmitting power allocation, as well as the users’ block-length allocation, subject to the UAV’s sum transmitting power constraint and the total block-length constraint. Although the maximum-PER minimization problem is non-convex and difficult to be optimally solved, we obtain a high-quality solution to this problem by using the technique of alternating optimization. Numerical results show that our proposed design achieves significant performance gains over other benchmark schemes without the joint optimization.

Key words: UAV, MEC, URLLC, placement optimization, resource allocation

ZHANG Pengyu, XIE Lifeng, XU Jie. Joint Placement and Resource Allocation for UAV-Assisted Mobile Edge Computing Networks with URLLC[J]. ZTE Communications, 2020, 18(2): 49-56.

Figures/Tables 3

References 29

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Joint Placement and Resource Allocation for UAV-Assisted Mobile Edge Computing Networks with URLLC

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