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Resource management in UAV-assisted MEC: state-of-the-art and open challenges

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Abstract

Unmanned aerial vehicles (UAV) have been widely used in various fields because of their high mobility and portability. At the same time, due to the rapid development of artificial intelligence, people’s demand for computing is increasing, and the computing power of existing mobile computing devices cannot fully meet the users’ needs for network quality. Therefore, people have proposed mobile edge computing technology (MEC), but MEC still has some shortcomings, such as poor dynamic performance. Therefore, combining the two will have better results. Due to the limited battery capacity of UAVs, the continuity of the UAV Communication Network is affected. Therefore, effectively using the limited spectrum resources, reducing the energy consumption of UAVs and meeting the users’ quality of service needs have become urgent problems to be solved. Under the framework of UAV-assisted MEC, this paper focuses on the downlink communication energy efficiency of a single UAV Communication Network, arranges and analyzes the methods and technologies found in different research, reviews specific UAV practical applications, provides a relevant discussion and method analysis for the problems existing in the UAV Communication Network, and presents its existing problems and our future research direction.

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Abbreviations

UAV:

unmanned aerial vehicle

MEC:

mobile edge computing

LoS:

line of sight

CPU:

central processing unit

MCC:

mobile cloud computing

ETSA:

European Telecommunications Standardization Association

WPT:

wireless power transmission

SCA:

successive convex approximation

IoT:

Internet of things

KKT:

Karush-Kuhn-Tucker

BC:

broadcast channel

D2D:

device-to-device

NOMA:

non-orthogonal multiple access

TD-LTE:

time division-long term elevation

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Authors and Affiliations

  1. College of Computer Science and Electronic Engineering, Hunan University, Changsha, 410082, China

    Zhu **ao, Yanxun Chen, Hongbo Jiang & Zhenzhen Hu

  2. Computer Science and Engineering Department, The Chinese University of Hong Kong (CUHK), Hong Kong, China

    John C. S. Lui

  3. Department of Mathematics and Computer Science, University of Exeter, Exeter, UK

    Geyong Min

  4. TU Wien, 1040, Vienna, Austria

    Schahram Dustdar

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  1. Zhu **ao
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  2. Yanxun Chen
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  3. Hongbo Jiang
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  4. Zhenzhen Hu
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  5. John C. S. Lui
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  6. Geyong Min
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  7. Schahram Dustdar
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Correspondence to Hongbo Jiang.

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This work was supported in part by the National Natural Science Foundation of China under Grant U20A20181; in part by the Key Research and Development Project of Hunan Province of China under Grant 2022GK2020; in part by Hunan Natural Science Foundation of China under Grant 2022JJ2059, in part by the Funding Projects of Zhejiang Lab under Grant 2021LC0AB05. (The corresponding author of this paper is Hongbo Jiang)

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**ao, Z., Chen, Y., Jiang, H. et al. Resource management in UAV-assisted MEC: state-of-the-art and open challenges. Wireless Netw 28, 3305–3322 (2022). https://doi.org/10.1007/s11276-022-03051-4

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