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Drones
Special Issues
UAV-Assisted Mobile Wireless Networks and Applications
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UAV-Assisted Mobile Wireless Networks and Applications

A special issue of Drones (ISSN 2504-446X). This special issue belongs to the section "Drone Communications".

Deadline for manuscript submissions: 29 November 2024 | Viewed by 7191

Special Issue Editors

Dr. Tomotaka Kimura

E-Mail Website
Guest Editor
Faculty of Science and Engineering, Doshsiha University 1-3 Tatara Miyakodani, Kyotanabe-shi, 610-0321, Kyoto, Japan
Interests: wireless communications; UAV networks; sensor networks
Special Issues, Collections and Topics in MDPI journals
Dr. Chinthaka Premachandra

E-Mail Website
Guest Editor
Department of Electronic Engineering, School of Engineering, Shibaura Institute of Technology, Tokyo 135-8548, Japan
Interests: UAV; Artificial Intelligence (AI); ITS; aerial/mobile robotics; audio/video processing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

UAV (Unmanned Aerial Vehicle)-assisted mobile wireless networks are expected to be used in a wide range of applications such as agriculture, transport, environmental monitoring and rescue operations. To realize these applications, it is crucial to establish efficient network operation techniques. Therefore, the special issue calls for papers regarding the recent advances related to UAV-assisted mobile wireless networks in a wide range of topics, including (but not limited to) the following:

  • UAV mobile control techniques
  • Control of UAV-assited networks
  • Performance evaluation of UAV-assited networks
  • Applications for UAV-assisted mobile wireless networks
  • Multi-hop networking
  • Traffic management in UAV-assisted networks
  • Smart autonomous networks
  • UAV sensor networks
  • Security meassures for UAV networks
  • Energy-efficient routing
  • On-UAV edge computing
  • Collision avoidance for UAVs
  • Experimental platforms for UAV-aided mobile networks
  • AI-based UAV network control

Dr. Tomotaka Kimura
Dr. Chinthaka Premachandra
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. Drones is an international peer-reviewed open access monthly 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 2600 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 networks
  • mobility management
  • network control
  • routing
  • traffic management

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Published Papers (6 papers)

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Research

13 pages, 1136 KiB  
Article
Message Passing Detectors for UAV-Based Uplink Grant-Free NOMA Systems
by Yi Song, Yiwen Zhu, Kun Chen-Hu, Xinhua Lu, Peng Sun and Zhongyong Wang
Drones 2024, 8(7), 325; https://doi.org/10.3390/drones8070325 - 14 Jul 2024
Viewed by 457
Abstract
Utilizing unmanned aerial vehicles (UAVs) as mobile access points or base stations has emerged as a promising solution to address the excessive traffic demands in wireless networks. This paper investigates improving the detector performance at the unmanned aerial vehicle base stations (UAV-BSs) in [...] Read more.
Utilizing unmanned aerial vehicles (UAVs) as mobile access points or base stations has emerged as a promising solution to address the excessive traffic demands in wireless networks. This paper investigates improving the detector performance at the unmanned aerial vehicle base stations (UAV-BSs) in an uplink grant-free non-orthogonal multiple access (GF-NOMA) system by considering the activity state (AS) temporal correlation of the different user equipments (UEs) in the time domain. The Bernoulli Gaussian-Markov chain (BG-MC) probability model is used for exploiting both the sparsity and slow change characteristic of the AS of the UE. The GAMP Bernoulli Gaussian-Markov chain (GAMP-BG-MC) algorithm is proposed to improve the detector performance, which can utilize the bidirectional message passing between the neighboring time slots to fully exploit the temporally correlated AS of the UE. Furthermore, the parameters of the BG-MC model can be updated adaptively during the estimation procedure with unknown system statistics. Simulation results show that the proposed algorithm can improve the detection accuracy compared to existing methods while keeping the same order complexity. Full article
(This article belongs to the Special Issue UAV-Assisted Mobile Wireless Networks and Applications)
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18 pages, 4767 KiB  
Article
Autonomous UAV Safety Oriented Situation Monitoring and Evaluation System
by Zhuoyong Shi, Jiandong Zhang, Guoqing Shi, Mengjie Zhu, Longmeng Ji and Yong Wu
Drones 2024, 8(7), 308; https://doi.org/10.3390/drones8070308 - 9 Jul 2024
Viewed by 511
Abstract
In this paper, a LabVIEW-based online monitoring and safety evaluation system for UAVs is designed to address the deficiencies in UAV flight state parameter monitoring and safety evaluation. The system consists of a lower unit for UAV recording and an upper unit on [...] Read more.
In this paper, a LabVIEW-based online monitoring and safety evaluation system for UAVs is designed to address the deficiencies in UAV flight state parameter monitoring and safety evaluation. The system consists of a lower unit for UAV recording and an upper unit on the ground. The lower unit collects and detects flight data and connects to the upper unit through a wireless digital transmission module via a serial port. The upper unit receives the data and carries out the monitoring and safety situation evaluation of the UAV. The lower unit of the system adopts multi-sensors to collect UAV navigation information in real time to achieve flight detection, while the upper unit adopts LabVIEW to design the UAV online monitoring and safety situation prediction system, enabling monitoring and safety situation prediction during UAV navigation. The test results show that the system can detect and comprehensively display the navigation information of the UAV in real time, and realize the safety evaluation and warning function of the UAV. Full article
(This article belongs to the Special Issue UAV-Assisted Mobile Wireless Networks and Applications)
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20 pages, 619 KiB  
Article
Intelligent Online Offloading and Resource Allocation for HAP Drones and Satellite Collaborative Networks
by Cheng Gao, Xilin Bian, Bo Hu, Shanzhi Chen and Heng Wang
Drones 2024, 8(6), 245; https://doi.org/10.3390/drones8060245 - 5 Jun 2024
Viewed by 723
Abstract
High-altitude platform (HAP) drones and satellites collaborate to form a network that provides edge computing services to terrestrial internet of things (IoT) devices, which is considered a promising method. In this network, IoT devices’ tasks can be split into multiple parts and processed [...] Read more.
High-altitude platform (HAP) drones and satellites collaborate to form a network that provides edge computing services to terrestrial internet of things (IoT) devices, which is considered a promising method. In this network, IoT devices’ tasks can be split into multiple parts and processed by servers at non-terrestrial nodes in different locations, thereby reducing task processing delays. However, splitting tasks and allocating communication and computing resources are important challenges. In this paper, we investigate the task offloading and resource allocation problem in multi-HAP drones and multi-satellite collaborative networks. In particular, we formulate a task splitting and communication and computing resource optimization problem to minimize the total delay of all IoT devices’ tasks. To solve this problem, we first transform and decompose the original problem into two subproblems. We design a task splitting optimization algorithm based on deep reinforcement learning, which can achieve online task offloading decision-making. This algorithm structurally designs the actor network to ensure that output actions are always valid. Furthermore, we utilize convex optimization methods to optimize the resource allocation subproblem. The simulation results show that our algorithm can effectively converge and significantly reduce the total task processing delay when compared with other baseline algorithms. Full article
(This article belongs to the Special Issue UAV-Assisted Mobile Wireless Networks and Applications)
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17 pages, 4881 KiB  
Article
Intelligent Packet Priority Module for a Network of Unmanned Aerial Vehicles Using Manhattan Long Short-Term Memory
by Dino Budi Prakoso, Jauzak Hussaini Windiatmaja, Agus Mulyanto, Riri Fitri Sari and Rosdiadee Nordin
Drones 2024, 8(5), 183; https://doi.org/10.3390/drones8050183 - 7 May 2024
Viewed by 976
Abstract
Unmanned aerial vehicles (UAVs) are becoming more common in wireless communication networks. Using UAVs can lead to network problems. An issue arises when the UAVs function in a network-access-limited environment with nodes causing interference. This issue could potentially hinder UAV network connectivity. This [...] Read more.
Unmanned aerial vehicles (UAVs) are becoming more common in wireless communication networks. Using UAVs can lead to network problems. An issue arises when the UAVs function in a network-access-limited environment with nodes causing interference. This issue could potentially hinder UAV network connectivity. This paper introduces an intelligent packet priority module (IPPM) to minimize network latency. This study analyzed Network Simulator–3 (NS-3) network modules utilizing Manhattan long short-term memory (MaLSTM) for packet classification of critical UAV, ground control station (GCS), or interfering nodes. To minimize network latency and packet delivery ratio (PDR) issues caused by interfering nodes, packets from prioritized nodes are transmitted first. Simulation results and evaluation show that our proposed intelligent packet priority module (IPPM) method outperformed previous approaches. The proposed IPPM based on MaLSTM implementation for the priority packet module led to a lower network delay and a higher packet delivery ratio. The performance of the IPPM averaged 62.2 ms network delay and 0.97 packet delivery ratio (PDR). The MaLSTM peaked at 97.5% accuracy. Upon further evaluation, the stability of LSTM Siamese models was observed to be consistent across diverse similarity functions, including cosine and Euclidean distances. Full article
(This article belongs to the Special Issue UAV-Assisted Mobile Wireless Networks and Applications)
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21 pages, 2806 KiB  
Article
Study on Drone Handover Methods Suitable for Multipath Interference Due to Obstacles
by Kakeru Hirata, Takefumi Hiraguri, Tomotaka Kimura, Takahiro Matsuda, Tetsuro Imai, Jiro Hirokawa, Kazuki Maruta and Satoshi Ujigawa
Drones 2024, 8(2), 32; https://doi.org/10.3390/drones8020032 - 23 Jan 2024
Viewed by 2066
Abstract
Networks constructed in the sky are known as non-terrestrial networks (NTNs). As an example of an NTN, relay transmission using drones as radio stations enables flexible network construction in the air by performing handovers with ground stations. However, the presence of structures or [...] Read more.
Networks constructed in the sky are known as non-terrestrial networks (NTNs). As an example of an NTN, relay transmission using drones as radio stations enables flexible network construction in the air by performing handovers with ground stations. However, the presence of structures or obstacles in the flight path causes multipath interference; consequently, the propagation environment fluctuates significantly based on the flight. In such a communication environment, it is difficult for a drone to select an optimal ground station for a handover. Moreover, unlike a terrestrial network, the propagation environment of a flying drone is affected by structures and other factors that cause multipaths based on the flight speed and altitude, making the conditions of the propagation environment even more complex. To solve these problems, we propose handover schemes between drones and the ground that consider the multipath interference caused by obstacles. The proposed methods are used to perform handovers based on an optimal threshold of received power considering interference and avoid unnecessary handovers based on the moving speed, which makes the handover seamless. Finally, we develop a simulator that evaluates the cross layer from propagation to upper network protocols in a virtual space, including buildings, evaluate the communication quality of a drone flying in a three-dimensional space, and confirm the effectiveness of the proposed methods as well as the evaluation of the real environment. Full article
(This article belongs to the Special Issue UAV-Assisted Mobile Wireless Networks and Applications)
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25 pages, 1091 KiB  
Article
Heterogeneous Drone Small Cells: Optimal 3D Placement for Downlink Power Efficiency and Rate Satisfaction
by Nima Namvar, Fatemeh Afghah and Ismail Guvenc
Drones 2023, 7(10), 634; https://doi.org/10.3390/drones7100634 - 13 Oct 2023
Viewed by 1599
Abstract
In this paper, we delve into the domain of heterogeneous drone-enabled aerial base stations, each equipped with varying transmit powers, serving as downlink wireless providers for ground users. A central challenge lies in strategically selecting and deploying a subset from the available drone [...] Read more.
In this paper, we delve into the domain of heterogeneous drone-enabled aerial base stations, each equipped with varying transmit powers, serving as downlink wireless providers for ground users. A central challenge lies in strategically selecting and deploying a subset from the available drone base stations (DBSs) to meet the downlink data rate requirements while minimizing the overall power consumption. To tackle this, we formulate an optimization problem to identify the optimal subset of DBSs, ensuring wireless coverage with an acceptable transmission rate in the downlink path. Moreover, we determine their 3D positions for power consumption optimization. Assuming DBSs operate within the same frequency band, we introduce an innovative, computationally efficient beamforming method to mitigate intercell interference in the downlink. We propose a Kalai–Smorodinsky bargaining solution to establish the optimal beamforming strategy, compensating for interference-related impairments. Our simulation results underscore the efficacy of our solution and offer valuable insights into the performance intricacies of heterogeneous drone-based small-cell networks. Full article
(This article belongs to the Special Issue UAV-Assisted Mobile Wireless Networks and Applications)
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