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Advanced Unmanned Aerial Vehicle (UAV) Wireless Communication and Networking Technologies
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Advanced Unmanned Aerial Vehicle (UAV) Wireless Communication and Networking Technologies

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

Deadline for manuscript submissions: 15 June 2025 | Viewed by 3146

Special Issue Editors

Dr. Zhuangzhuang Cui

E-Mail Website
Guest Editor
WaveCoRE, Department of Electrical Engineering, Ku Leuven, 3000 Leuven, Belgium
Interests: wireless communication; UAV network; sensing and communication
Dr. Konstantinos Maliatsos

E-Mail Website
Guest Editor
Department of Information and Communication Systems Engineering, University of the Aegean, 83100 Samos, Greece
Interests: vehicular communications (V2X); channel modeling; MIMO; ITS

Special Issue Information

Dear Colleagues,

Unmanned aerial vehicles (UAVs) play an important role in wireless communications and networks thanks to their low cost, as well as their flexible and rapid deployment, making them integral in a hot spot or emergency environment. However, the roles of UAVs need to be further defined for next-generation wireless networks, such as the forthcoming 6G. For the next generation, wireless communications are expected to be deployed everywhere in an integrated space–air–ground–sea environment and are expected to use massive antennas and diverse spectrums. In this context, UAV-based wireless communications and networks encounter many challenges such as non-stationary channels, intricate spectrum allocation, and complicated functionality tradeoff between sensing and communications. Thus, this Special Issue seeks to comprehensively investigate the topic “Advanced Unmanned Aerial Vehicle (UAV) Wireless Communication and Networking Technologies” by clarifying the challenges, opportunities, and future directions.

This Special Issue aims to feature original research and review articles discussing communication theories, radio channels, diverse functionalities enabled by UAVs, real-world applications, and implementations relevant to UAV-based wireless communications and networks. Through this Special Issue, our goal is to collect manuscripts describing the most recent advances and technical findings addressing problems encountered in both theoretical and practical applications for UAV communication and networking. Topics of interest include, but are not limited to, the following:

  • The channel characterization, modeling, and estimation for UAV communications
  • The performance analysis and optimization of UAV communications
  • UAV-assisted integrated sensing and communications;
  • Smart antenna systems (including reconfigurable intelligent surfaces for UAVs);
  • UAV-enabled non-terrestrial network architecture;
  • UAV-enabled air-to-ground communications;
  • The positioning, navigation, and timing (PNT) of UAV networks;
  • The real-world implementation of UAV communications;
  • The trends and future directions of UAVs in wireless networks.

Dr. Zhuangzhuang Cui
Dr. Konstantinos Maliatsos
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

  • 5G-A/6G wireless communications
  • aerial network
  • cellular-connected UAVs
  • channel modeling
  • non-terrestrial networks
  • smart antenna systems
  • unmanned aerial vehicles (UAVs)
  • UAV-vehicle communication
  • sensing and communication

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Published Papers (2 papers)

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Research

23 pages, 738 KiB  
Article
A Deep Q-Learning Based UAV Detouring Algorithm in a Constrained Wireless Sensor Network Environment
by Shakila Rahman, Shathee Akter and Seokhoon Yoon
Electronics 2025, 14(1), 1; https://doi.org/10.3390/electronics14010001 - 24 Dec 2024
Cited by 1 | Viewed by 1525
Abstract
Unmanned aerial vehicles (UAVs) play a crucial role in various applications, including environmental monitoring, disaster management, and surveillance, where timely data collection is vital. However, their effectiveness is often hindered by the limitations of wireless sensor networks (WSNs), which can restrict communications due [...] Read more.
Unmanned aerial vehicles (UAVs) play a crucial role in various applications, including environmental monitoring, disaster management, and surveillance, where timely data collection is vital. However, their effectiveness is often hindered by the limitations of wireless sensor networks (WSNs), which can restrict communications due to bandwidth constraints and limited energy resources. Thus, the operational context of the UAV is intertwined with the constraints on WSNs, influencing how they are deployed and the strategies used to optimize their performance in these environments. Considering the issues, this paper addresses the challenge of efficient UAV navigation in constrained environments while reliably collecting data from WSN nodes, recharging the sensor nodes’ power supplies, and ensuring the UAV detours around obstacles in the flight path. First, an integer linear programming (ILP) optimization problem named deadline and obstacle-constrained energy minimization (DOCEM) is defined and formulated to minimize the total energy consumption of the UAV. Then, a deep reinforcement learning-based algorithm, named the DQN-based UAV detouring algorithm, is proposed to enable the UAV to make intelligent detour decisions in the constrained environment. The UAV must finish its tour (data collection and recharging sensors) without exceeding its battery capacity, ensuring each sensor has the minimum residual energy and consuming energy for transmitting and generating data, after being recharged by the UAV at the end of the tour. Finally, simulation results demonstrate the effectiveness of the proposed DQN-based UAV detouring algorithm in data collection and recharging the sensors while minimizing the total energy consumption of the UAV. Compared to other baseline algorithm variants, the proposed algorithm outperforms all of them. Full article
(This article belongs to the Special Issue Advanced Unmanned Aerial Vehicle (UAV) Wireless Communication and Networking Technologies)
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22 pages, 1380 KiB  
Article
Performance Analysis of Reconnaissance Coverage for HUAV Swarms under Communication Interference Based on Different Architectures
by Yongjian Fan, Bing Chen, Yunlong Zhao, Feng Hu, Chunyan Liu and Yang Li
Electronics 2024, 13(20), 4067; https://doi.org/10.3390/electronics13204067 - 16 Oct 2024
Viewed by 962
Abstract
In environments with unknown communication interference, the mission efficiency of heterogeneous unmanned aerial vehicle (HUAV) swarms is often impacted by communication disruptions due to regions of strong interference encountered when executing reconnaissance and coverage missions. Existing research has rarely focused on communication interference [...] Read more.
In environments with unknown communication interference, the mission efficiency of heterogeneous unmanned aerial vehicle (HUAV) swarms is often impacted by communication disruptions due to regions of strong interference encountered when executing reconnaissance and coverage missions. Existing research has rarely focused on communication interference or on the differences in HUAV characteristics under various control architectures; thus, in this paper we explore the performance differences between HUAV swarms based on centralized, distributed, and centralized-distributed architectures when executing reconnaissance and coverage missions in environments with unknown communication interference. First, a communication model in an unknown interference environment is constructed to reflect the real-time communication status of the swarm. Second, in response to the limitations of the traditional artificial potential field (APF) algorithm in this environment, a coverage-oriented artificial potential field (COAPF) algorithm is proposed. Finally, based on the COAPF algorithm, a multi-dimensional comparison of the mission completion efficiency of HUAV swarms with three different architectures is conducted. Our simulation results indicate that the distributed architecture is suitable for large-scale environments with strong interference, while the centralized–distributed architecture performs better in small-scale environments with weak interference. Conversely, the centralized architecture exhibits poor performance in all interference scenarios due to its lack of decision-making capabilities. Full article
(This article belongs to the Special Issue Advanced Unmanned Aerial Vehicle (UAV) Wireless Communication and Networking Technologies)
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