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Electronics
Special Issues
Intelligent UAV Based Data Collection Networks
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Intelligent UAV Based Data Collection Networks

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Microwave and Wireless Communications".

Deadline for manuscript submissions: closed (15 August 2023) | Viewed by 2150

Special Issue Editors

Prof. Shu Fu

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Guest Editor
School of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China
Interests: B5G/6G ultra-dense cellular network; UAV; low orbit satellite communication
Special Issues, Collections and Topics in MDPI journals
Dr. Yueyue Dai

E-Mail Website
Guest Editor
School of Cyber Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Interests: MEC; federated learning; blockchain
Special Issues, Collections and Topics in MDPI journals
Dr. Lingxiang Li

E-Mail Website
Guest Editor
National Key Laboratory of Science and Technology on Communications, University of Electronic Science and Technology of China, Chengdu 611731, China
Interests: terahertz communications; joint sensing and communications; mobile computing

Special Issue Information

Dear Colleagues,

In recent years, UAV technology has developed rapidly and has been widely used in various industries. The combination of UAV and wireless sensor networks can effectively enhance the communication ability, perception ability, age of information (AoI) and energy efficiency of the network. The era of Internet of Things needs to realize massive node coverage and connection. For some remote areas, the Internet of Things communication technology cannot collect data in time. The UAV has the characteristics of flexibility and mobility so that it can be used for wireless sensor network data collection in the Internet of Things.

At present, there are several studies on UAV data collection, but they are not comprehensive enough. Most of the studies model the channel between the UAV and the ground equipment as a simple line-of-sight transmission channel. In the multi-UAV network, the limited energy of UAV and limitation of AoI are not considered. Most of the existing literature includes studies on the UAV path planning problem, but there is still room for improvement in the algorithm used in the path planning problem, and there is a lack of UAV path planning methods for dynamic changes in the path planning environment.

In fact, the application of intelligent UAV-assisted data collection is varied, including but not limited to the use of a variety of intelligent algorithms to optimize the number and height of UAVs in data collection, the flight trajectory, and the resource allocation, etc., to improve the overall performance of the system, such as timeliness, energy consumption, energy efficiency, and so on. The data collection network based on intelligent UAV is studied to supplement the blanks and deficiencies of current related research, improve the efficiency of data collection in the Internet of Things, and help 6G to realize the vision of establishing an air–space–ground–sea integrated network.

Dr. Shu Fu
Dr. Yueyue Dai
Dr. Lingxiang Li
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • UAV
  • data collection
  • intelligent algorithm
  • wireless sensor networks
  • IoT network

Published Papers (1 paper)

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Research

12 pages, 446 KiB  
Article
Data Collection Mechanism for UAV-Assisted Cellular Network Based on PPO
by Tuo Chen, Feihong Dong, Hu Ye, Yun Wang and Bin Wu
Electronics 2023, 12(6), 1376; https://doi.org/10.3390/electronics12061376 - 13 Mar 2023
Cited by 2 | Viewed by 1431
Abstract
Unmanned aerial vehicles (UAVs) are increasingly gaining in application value in many fields because of their low cost, small size, high mobility and other advantages. In the scenario of traditional cellular networks, UAVs can be used as a kind of aerial mobile base [...] Read more.
Unmanned aerial vehicles (UAVs) are increasingly gaining in application value in many fields because of their low cost, small size, high mobility and other advantages. In the scenario of traditional cellular networks, UAVs can be used as a kind of aerial mobile base station to collect information of edge users in time. Therefore, UAVs provide a promising communication tool for edge computing. However, due to the limited battery capacity, these may not be able to completely collect all the information. The path planning can ensure that the UAV collects as much data as possible under the limited flight distance, so it is very important to study the path planning of the UAV. In addition, due to the particularity of air-to-ground communication, the flying altitude of the UAV can have a crucial impact on the channel quality between the UAV and the user. As a mature technology, deep reinforcement learning (DRL) is an important algorithm in the field of machine learning which can be deployed in unknown environments. Deep reinforcement learning is applied to the data collection of UAV-assisted cellular networks, so that UAVs can find the best path planning and height joint optimization scheme, which ensures that UAVs can collect more information under the condition of limited energy consumption, save human and material resources as much as possible, and finally achieve higher application value. In this work, we transform the UAV path planning problem into an Markov decision process (MDP) problem. By applying the proximal policy optimization (PPO) algorithm, our proposed algorithm realizes the adaptive path planning of UAV. Simulations are conducted to verify the performance of the proposed scheme compared to the conventional scheme. Full article
(This article belongs to the Special Issue Intelligent UAV Based Data Collection Networks)
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