Wireless Networks and UAV: 2nd Edition

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

Deadline for manuscript submissions: closed (27 December 2024) | Viewed by 1922

Special Issue Editor


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Guest Editor
Institut National Polytechnique de Toulouse, Toulouse, France
Interests: performance evaluation of mobile and vehicular networks; satellite networks; wireless sensor networks; cross-layer systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are inviting submissions for a Special Issue of Drones titled “Wireless Networks and UAV: 2nd Edition”.

The use of aerial drones, also known as unmanned aerial vehicles (UAVs), as well as unmanned marine vehicles (UMVs), has proven to be very useful in rescue operations or environmental monitoring; more specifically, they have been used for population surveillance during the management of the COVID-19 pandemic. Drones can be used for communication, monitoring, and delivery. Autonomous drone swarms help to monitor and connect mobile unconnected objects, as well as aid in Earth and extra-Earth exploration. The integration of unmanned vehicles with terrestrial and space networks has been standardized and is the focus of ongoing experiments.

Research in this domain has revealed several critical issues, such as autonomous deployment, navigation and control, energy management, and seamless services. Advanced methods should be designed to ensure the reliable and efficient functioning of an unmanned vehicle network.

This Special Issue focuses on new developments in the fields of placement, smart network control, and the navigation of unmanned vehicles from theoretical to experimental studies.

Potential topics include, but are not limited to, the following:

  • Efficient and resilient deployment of aerial drones;
  • Control of unmanned vehicles-aided networks;
  • UAV-aided mobile sensor networks;
  • Autonomous vehicle network monitoring;
  • Energy-efficient UAV tracking of mobile targets;
  • Energy harvesting for networks composed of unmanned vehicles;
  • Traffic monitoring aided by unmanned vehicles;
  • Beyond 5G space–air–ground network control;
  • Coverage optimization and control in UAV surveillance;
  • Smart autonomous networks of vehicles;
  • Collision avoidance for unmanned vehicles;
  • Autonomous networks for deep space exploration;
  • Experimental platforms for UAV-aided mobile networks.

Dr. Riadh Dhaou
Guest Editor

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

  • efficient and resilient deployment of aerial drones
  • control of unmanned vehicles aided networks
  • UAV-aided mobile sensor networks
  • autonomous vehicles networks monitoring
  • energy-efficient UAV tracking of mobile targets
  • energy harvesting for networks composed of unmanned vehicles
  • traffic monitoring aided by unmanned vehicles
  • beyond 5G space–air–ground network control
  • coverage optimization and control in UAV surveillance
  • smart autonomous networks of vehicles
  • collision avoidance for unmanned vehicles
  • autonomous networks for deep space exploration
  • experimental platforms for UAV-aided mobile networks

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Published Papers (1 paper)

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Review

21 pages, 1405 KiB  
Review
Variations in Multi-Agent Actor–Critic Frameworks for Joint Optimizations in UAV Swarm Networks: Recent Evolution, Challenges, and Directions
by Muhammad Morshed Alam, Sayma Akter Trina, Tamim Hossain, Shafin Mahmood, Md. Sanim Ahmed and Muhammad Yeasir Arafat
Drones 2025, 9(2), 153; https://doi.org/10.3390/drones9020153 - 19 Feb 2025
Viewed by 1570
Abstract
Autonomous unmanned aerial vehicle (UAV) swarm networks (UAVSNs) can efficiently perform surveillance, connectivity, computing, and energy transfer services for ground users (GUs). These missions require trajectory planning, UAV-GUs association, task offloading, next-hop selection, and resource allocation, including transmit power, bandwidth, timeslots, caching, and [...] Read more.
Autonomous unmanned aerial vehicle (UAV) swarm networks (UAVSNs) can efficiently perform surveillance, connectivity, computing, and energy transfer services for ground users (GUs). These missions require trajectory planning, UAV-GUs association, task offloading, next-hop selection, and resource allocation, including transmit power, bandwidth, timeslots, caching, and computing resources, to enhance network performance. Owing to the highly dynamic topology, limited resources, stringent quality of service requirements, and lack of global knowledge, optimizing network performance in UAVSNs is very intricate. To address this, an adaptive joint optimization framework is required to handle both discrete and continuous decision variables, ensuring optimal performance under various dynamic constraints. A multi-agent deep reinforcement learning-based adaptive actor–critic framework offers an effective solution by leveraging its ability to extract hidden features through agent interactions, generate hybrid actions under uncertainty, and adaptively learn with scalable generalization in dynamic conditions. This paper explores the recent evolutions of actor–critic frameworks to deal with joint optimization problems in UAVSNs by proposing a novel taxonomy based on the modifications in the internal actor–critic neural network structure. Additionally, key open research challenges are identified, and potential solutions are suggested as directions for future research in UAVSNs. Full article
(This article belongs to the Special Issue Wireless Networks and UAV: 2nd Edition)
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