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Electronics
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Advanced Technologies in Unmanned Aerial Vehicle (UAV)-Based Communications
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Advanced Technologies in Unmanned Aerial Vehicle (UAV)-Based Communications

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

Deadline for manuscript submissions: 30 November 2024 | Viewed by 7273

Special Issue Editors

Dr. Sang Ik Han

E-Mail Website
Guest Editor
School of Smart IT, Semyung University, Jecheon, Chungcheongbuk-do 27136, Korea
Interests: UAV wireless networks; next-generation communication systems; artificial intelligence; drone; autonomous vehicle technology; smart mobility
Dr. Joobum Kim

E-Mail Website
Guest Editor
Department of Information Technology, Middle Georgia State University, Macon, GA 31206, USA
Interests: queueing analysis; routing and spectrum allocation; elastic optical network; Internet of Things; LoRa/LoRaWAN; edge computing
Prof. Dr. Shiho Kim

E-Mail Website
Guest Editor
School of Integrated Technology (SIT), Yonsei University, Incheon 21983, Republic of Korea
Interests: autonomous driving; quantum computing; blockchain for security and decentralization; deep reinforcement learning
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Nurul Sarkar

E-Mail Website
Guest Editor
Department of Computer Science and Software Engineering, Auckland University of Technology, Auckland 1010, New Zealand
Interests: UAV networks, IoT, sensor networks, network protocols, wireless communication netwok, 5G and beyond, edge and fog computing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With the development of sophisticated technologies, unmanned aerial vehicles (UAVs) have become more advanced in recent years, achieving a light weight, high flexibility and longer battery life. Such advances have made UAVs able to be utilized in a wide range of applications, such as military, public safety and civil applications. Moreover, much attention has been paid to utilizing UAVs in 5G networks and beyond to enhance their capacity due to their swift deployment, low maintenance costs and high mobility. In addition, since deploying UAVs in wireless communication networks does not require a cell reorganization, UAVs can provide a viable solution for existing networks. However, UAV wireless networks still leave many issues to be resolved for stable and reliable service. The rapid changes in the network topology, including the number of nodes and links in operation and the relative positions of nodes, require special attention. The routing protocol cannot be implemented in a simple proactive or reactive manner because the UAV wireless network needs to be reorganized repeatedly when a UAV is out of service. Furthermore, the instantaneous management of users’ links when transferring from an inactive UAV to an active UAV is challenging. Most importantly, UAV wireless networks require energy efficiency to prolong the lifetime of networks.

This Special Issue aims to gather the latest research on advanced technologies for UAV-based communications. Reviews and survey papers on this topic are welcome. The topics of interest include, but are not limited to, the following:

  • Applications of UAV-based communications;
  • Artificial intelligence (AI) in UAV-based communications;
  • Machine learning (ML)-based optimization;
  • UAV deployment or trajectory;
  • Practical channel modeling;
  • Resource allocation in UAV-based communications;
  • Energy efficiency in UAV-based communications;
  • Security issues in UAV-based communications;
  • Interference mitigation in UAV-based communications;
  • Non-orthogonal multiple access (NOMA) in UAV-based communications;
  • Multi-input and multi-output (MIMO) in UAV-based communications;
  • 3D beamforming in UAV-based communications;
  • Routing and scheduling in UAV-based communications;
  • Millimeter wave communications;
  • Multi-UAV communications;
  • Wireless power transfer and energy harvesting;
  • UAV management and control.

Dr. Sang Ik Han
Dr. Joobum Kim
Prof. Dr. Shiho Kim
Dr. Nurul I. Sarkar
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

  • applications of UAV-based communications
  • AI in UAV-based communications
  • ML-based optimization
  • UAV deployment
  • resource allocation in UAV-based communications
  • energy efficiency in UAV-based communications

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Published Papers (3 papers)

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Research

20 pages, 2056 KiB  
Article
A Deep Learning Approach for Fault-Tolerant Data Fusion Applied to UAV Position and Orientation Estimation
by Majd Saied, Abbas Mishi, Clovis Francis and Ziad Noun
Electronics 2024, 13(16), 3342; https://doi.org/10.3390/electronics13163342 - 22 Aug 2024
Viewed by 743
Abstract
This work introduces a novel fault-tolerance technique for data fusion in Unmanned Aerial Vehicles (UAVs), designed to address sensor faults through a deep learning-based framework. Unlike traditional methods that rely on hardware redundancy, our approach leverages Long Short-Term Memory (LSTM) networks for state [...] Read more.
This work introduces a novel fault-tolerance technique for data fusion in Unmanned Aerial Vehicles (UAVs), designed to address sensor faults through a deep learning-based framework. Unlike traditional methods that rely on hardware redundancy, our approach leverages Long Short-Term Memory (LSTM) networks for state estimation and a moving average (MA) algorithm for fault detection. The novelty of our technique lies in its dual strategy: utilizing LSTMs to analyze residuals and detect errors, while the MA algorithm identifies faulty sensors by monitoring variations in sensor data. This method allows for effective error correction and system recovery by replacing faulty measurements with reliable ones, eliminating the need for a fault-free prediction model. The approach has been validated through offline testing on real sensor data from a hexarotor UAV with simulated faults, demonstrating its efficacy in maintaining robust UAV operations without resorting to redundant hardware solutions. Full article
(This article belongs to the Special Issue Advanced Technologies in Unmanned Aerial Vehicle (UAV)-Based Communications)
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22 pages, 1343 KiB  
Article
Unmanned-Aircraft-System-Assisted Early Wildfire Detection with Air Quality Sensors
by Doaa Rjoub, Ahmad Alsharoa and Ala’eddin Masadeh
Electronics 2023, 12(5), 1239; https://doi.org/10.3390/electronics12051239 - 4 Mar 2023
Cited by 5 | Viewed by 2636
Abstract
Numerous hectares of land are destroyed by wildfires every year, causing harm to the environment, the economy, and the ecology. More than fifty million acres have burned in several states as a result of recent forest fires in the Western United States and [...] Read more.
Numerous hectares of land are destroyed by wildfires every year, causing harm to the environment, the economy, and the ecology. More than fifty million acres have burned in several states as a result of recent forest fires in the Western United States and Australia. According to scientific predictions, as the climate warms and dries, wildfires will become more intense and frequent, as well as more dangerous. These unavoidable catastrophes emphasize how important early wildfire detection and prevention are. The energy management system described in this paper uses an unmanned aircraft system (UAS) with air quality sensors (AQSs) to monitor spot fires before they spread. The goal was to develop an efficient autonomous patrolling system that detects early wildfires while maximizing the battery life of the UAS to cover broad areas. The UAS will send real-time data (sensor readings, thermal imaging, etc.) to a nearby base station (BS) when a wildfire is discovered. An optimization model was developed to minimize the total amount of energy used by the UAS while maintaining the required levels of data quality. Finally, the simulations showed the performance of the proposed solution under different stability conditions and for different minimum data rate types. Full article
(This article belongs to the Special Issue Advanced Technologies in Unmanned Aerial Vehicle (UAV)-Based Communications)
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22 pages, 3865 KiB  
Article
An Intelligent Cluster-Based Communication System for Multi-Unmanned Aerial Vehicles for Searching and Rescuing
by Amjad Mehmood, Zeeshan Iqbal, Arqam Ali Shah, Carsten Maple and Jaime Lloret
Electronics 2023, 12(3), 607; https://doi.org/10.3390/electronics12030607 - 26 Jan 2023
Cited by 11 | Viewed by 2588
Abstract
It has been observed that the use of UAVs in search and rescue (SAR) operations is very advantageous. When, all of a sudden, a crisis strikes, UAV technology is incredibly helpful and works more effectively to identify the entire region of a disaster [...] Read more.
It has been observed that the use of UAVs in search and rescue (SAR) operations is very advantageous. When, all of a sudden, a crisis strikes, UAV technology is incredibly helpful and works more effectively to identify the entire region of a disaster and identify victims trapped in the region. The deployment of a UAV network with a high battery lifespan and complete coverage of the disaster region is the primary emphasis of this article. For the efficient communication of UAVS, we suggested the intelligent cluster-based multi-unmanned aerial vehicle (ICBM-UAV) protocol. In order to discover victims swiftly and rescue those who are trapped in the afflicted region as soon as possible, ICBM-UAV uses the clustering technique smartly, which helps conserve drone batteries and performs some of the useful computations within the CH and hence helps to lessen workload on network congestion. Dividing the CMBM-UAV into two parts, the information gathering and the user equipment location identification, improves network life and makes the search and rescue operation more efficient and successful. After going to through vigorous result calculation, it is deduced that the proposed scheme has outperformed the existing state-of-the-art protocols such as AODV, OSLR and flocking mechanisms in terms of throughput, PDR, and coverage area probability by considering each scenario with and without the presence of obstacles. Hence, by delivering an exploitable estimate before reaching the victim, the proposed approach could drastically minimize the search and rescue time to save valuable lives. Full article
(This article belongs to the Special Issue Advanced Technologies in Unmanned Aerial Vehicle (UAV)-Based Communications)
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