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Drones
Special Issues
Drone Communication, Networking, and Trajectory Control in Urban Environments
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Drone Communication, Networking, and Trajectory Control in Urban Environments

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

Deadline for manuscript submissions: 15 November 2025 | Viewed by 3359

Special Issue Editors

Dr. Endrowednes Kuantama

E-Mail Website
Guest Editor
School of Computing, Macquarie University, Sydney 2109, Australia
Interests: internet of drones; design and implementation of unmanned aerial vehicles for aerial manipulation; sensing; recognition; and path planning for autonomous drone; machine learning and data analytics; SLAM algorithms and robotics control system
Special Issues, Collections and Topics in MDPI journals
Dr. Yu Zhang

E-Mail Website
Guest Editor
School of Computing, Macquarie University, Sydney 2109, Australia
Interests: internet of things (IoT); mobile and ubiquitous computing; embedded and edge AI; drone systems, and AI-based IoT data analytics
Dr. Ningning Hou

E-Mail Website
Guest Editor
School of Computing, Macquarie University, Macquarie Park, NSW 2109, Australia
Interests: smart city and urban computing; artificial intelligence of things (AIoT); wireless sensing and networking; and wireless security; low-power wide-area networks; robotics
Special Issues, Collections and Topics in MDPI journals
Dr. Yimeng Feng

E-Mail Website
Guest Editor
School of Computing, Macquarie University, Sydney 2109, Australia
Interests: internet of things; intelligent transportation systems; integrated sensing and communications

Special Issue Information

Dear Colleagues,

In recent years, the integration of drone technology into urban environments has attracted significant attention due to its potential to revolutionize sectors such as logistics, surveillance, emergency response, and infrastructure inspection. The ability of drones to navigate complex urban landscapes and perform tasks autonomously depends on advancements in communication systems, networking, and trajectory control. This special issue focuses on three key parameters: communication systems, networking, and trajectory control.

Communication systems are essential for ensuring reliable data transmission between drones, between drones and ground stations, and within drone networks. Networking involves the creation of ad-hoc networks for drone coordination and real-time information sharing. Lastly, trajectory control pertains to the navigation systems for single and multiple drones in various scenarios.

This Special Issue aims to gather original research articles and review papers that provide insights into the latest advancements and challenges in drone communication, networking, and trajectory control in urban environments.

We welcome manuscripts that address the following themes:

  • Drone communication and networking
  • Multi-drone coordination
  • Real-time data transmission
  • Urban air traffic management
  • Trajectory planning
  • Sustainable urban transport
  • On-board AI processing
  • Millimeter wave radar enabled drone navigation
  • Drone remote sensing using millimeter wave radar
  • LoRa enabled drone monitoring and networking

LoRa-assisted drone communication and networking

  • LoRa for long range drone applications
  • Novel drone applications
  • Drone Assisted Wireless Communications for 5G and Beyond
  • Drone security
  • Integrated sensing and communication drone networks
  • Remote object detection from drone
  • Urban Computing

We look forward to receiving your original research articles and reviews.

Dr. Endrowednes Kuantama
Dr. Yu Zhang
Dr. Ningning Hou
Dr. Yimeng Feng
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

  • drone communication and networking
  • multi-drone coordination
  • real-time data transmission
  • urban air traffic management
  • drone navigation
  • trajectory planning
  • sustainable urban transport
  • on-board AI processing
  • millimeter wave radar enabled drone navigation
  • drone remote sensing using millimeter wave radar
  • LoRa-assisted drone communication and networking
  • LoRa for long range drone applications
  • novel drone applications
  • drone assisted wireless communications for 5G and beyond
  • drone security
  • integrated sensing and communication drone networks
  • remote object detection from drone
  • urban computing

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (5 papers)

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Research

23 pages, 1095 KiB  
Article
Bridging ACO-Based Drone Logistics and Computing Continuum for Enhanced Smart City Applications
by Salvatore Rosario Bassolillo, Egidio D’Amato, Immacolata Notaro, Luca D’Agati, Giovanni Merlino and Giuseppe Tricomi
Drones 2025, 9(5), 368; https://doi.org/10.3390/drones9050368 - 13 May 2025
Viewed by 167
Abstract
In the context of evolving Smart Cities, the integration of drone technology and distributed computing paradigms presents significant potential for enhancing urban infrastructure and services. This paper proposes a comprehensive approach to optimizing urban delivery logistics through a cloud-based model that employs Ant [...] Read more.
In the context of evolving Smart Cities, the integration of drone technology and distributed computing paradigms presents significant potential for enhancing urban infrastructure and services. This paper proposes a comprehensive approach to optimizing urban delivery logistics through a cloud-based model that employs Ant Colony Optimization (ACO) for planning and Model Predictive Control (MPC) for trajectory tracking within a broader Computing Continuum framework. The proposed system addresses the Capacitated Vehicle Routing Problem (CVRP) by considering both drone capacity constraints and autonomy, using the ACO-based algorithm to efficiently assign delivery destinations while minimizing travel distances. Collision-free paths are computed by using a Visibility Graph (VG) based approach, and MPC controllers enable drones to adapt to dynamic obstacles in real time. Additionally, this work explores how clusters of drones can be deployed as edge devices within the Computing Continuum, seamlessly integrating with IoT sensors and fog computing infrastructure to support various urban applications, such as traffic management, crowd monitoring, and infrastructure inspections. This dual-architecture approach, combining the optimization capabilities of ACO with the flexible, distributed nature of the Computing Continuum, allows for scalable and efficient urban drone deployment. Simulation results validate the effectiveness of the proposed model in enhancing delivery efficiency and collision avoidance while demonstrating the potential of integrating drone technology into Smart City environments for improved data collection and real-time response. Full article
(This article belongs to the Special Issue Drone Communication, Networking, and Trajectory Control in Urban Environments)
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31 pages, 1200 KiB  
Article
Power-Efficient UAV Positioning and Resource Allocation in UAV-Assisted Wireless Networks for Video Streaming with Fairness Consideration
by Zaheer Ahmed, Ayaz Ahmad, Muhammad Altaf and Mohammed Ahmed Hassan
Drones 2025, 9(5), 356; https://doi.org/10.3390/drones9050356 - 7 May 2025
Viewed by 308
Abstract
This work proposes a power-efficient framework for adaptive video streaming in UAV-assisted wireless networks specially designed for disaster-hit areas where existing base stations are nonfunctional. Delivering high-quality videos requires higher video rates and more resources, which leads to increased power consumption. With the [...] Read more.
This work proposes a power-efficient framework for adaptive video streaming in UAV-assisted wireless networks specially designed for disaster-hit areas where existing base stations are nonfunctional. Delivering high-quality videos requires higher video rates and more resources, which leads to increased power consumption. With the increasing demand of mobile video, efficient bandwidth allocation becomes essential. In shared networks, users with lower bitrates experience poor video quality when high-bitrate users occupy most of the bandwidth, leading to a degraded and unfair user experience. Additionally, frequent video rate switching can significantly impact user experience, making the video rates’ smooth transition essential. The aim of this research is to maximize the overall users’ quality of experience in terms of power-efficient adaptive video streaming by fair distribution and smooth transition of video rates. The joint optimization includes power minimization, efficient resource allocation, i.e., transmit power and bandwidth, and efficient two-dimensional positioning of the UAV while meeting system constraints. The formulated problem is non-convex and difficult to solve with conventional methods. Therefore, to avoid the curse of complexity, the block coordinate descent method, successive convex approximation technique, and efficient iterative algorithm are applied. Extensive simulations are performed to verify the effectiveness of the proposed solution method. The simulation results reveal that the proposed method outperforms 95–97% over equal allocation, 77–89% over random allocation, and 17–40% over joint allocation schemes. Full article
(This article belongs to the Special Issue Drone Communication, Networking, and Trajectory Control in Urban Environments)
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26 pages, 8258 KiB  
Article
Low-Altitude Sensing Model: Analysis Leveraging ISAC in Real-World Environments
by Xiao Li, Xue Ding, Weiliang Xie, Wenbo Wang, Jinyang Yu and Wen-Yu Dong
Drones 2025, 9(4), 283; https://doi.org/10.3390/drones9040283 - 8 Apr 2025
Viewed by 338
Abstract
With the explosive growth of unmanned aerial vehicle (UAV) applications in numerous fields, low-altitude networks face formidable challenges in monitoring. In this context, integrated sensing and communication (ISAC) networks through three-dimensional (3D) wide-area sensing have emerged as the key solution. However, the differences [...] Read more.
With the explosive growth of unmanned aerial vehicle (UAV) applications in numerous fields, low-altitude networks face formidable challenges in monitoring. In this context, integrated sensing and communication (ISAC) networks through three-dimensional (3D) wide-area sensing have emerged as the key solution. However, the differences in networking mechanisms between communication and sensing, along with the transition from two-dimensional (2D) to 3D networking, complicate the realization of seamless 3D sensing. We aimed to address these challenges by analyzing the sensing capabilities of a single base station and the disparities between communication and sensing. Based on this, an innovative 3D sensing model for ISAC single base stations was proposed, defining the sensing boundaries and providing a foundation for designing the key parameters of ISAC base stations. Additionally, a multi-base station (multi-BS) low-altitude networked 3D sensing cellular-like architecture was proposed, overcoming the limitations of traditional 2D networks and achieving seamless 3D sensing. To validate the effectiveness of the model, comprehensive tests were conducted in both controlled laboratory conditions and real-world commercial network environments. The results show that the model successfully achieved stable and continuous sensing with the expected coverage and accuracy in networked environments. Full article
(This article belongs to the Special Issue Drone Communication, Networking, and Trajectory Control in Urban Environments)
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25 pages, 943 KiB  
Article
Optimization of Bandwidth Allocation and UAV Placement in Active RIS-Assisted UAV Communication Networks with Wireless Backhaul
by Thi-Thuy-Minh Tran, Binh-Minh Vu and Oh-Soon Shin
Drones 2025, 9(2), 111; https://doi.org/10.3390/drones9020111 - 2 Feb 2025
Cited by 1 | Viewed by 845
Abstract
In this paper, we present a novel design for unmanned aerial vehicle (UAV) communication networks with wireless backhaul, where an active reconfigurable intelligent surface (ARIS) is deployed to improve connections between a UAV and multiple users, while mitigating channel impairments in complex environments. [...] Read more.
In this paper, we present a novel design for unmanned aerial vehicle (UAV) communication networks with wireless backhaul, where an active reconfigurable intelligent surface (ARIS) is deployed to improve connections between a UAV and multiple users, while mitigating channel impairments in complex environments. The proposed design aims to maximize the achievable sum rate of all networks by jointly optimizing UAV placement; resource management strategies; transmit power allocation; and ARIS reflection coefficients, subject to backhaul constraints and power budget limitations in the ARIS system. The resulting optimization problem is highly non-convex, posing significant challenges. To tackle this, we decompose the problem into three interrelated sub-problems and apply inner approximation (IA) techniques to handle the non-convexities within each sub-problem. Moreover, a comprehensive alternating optimization framework is proposed to implement an iterative solution for the sub-problems. Simulation results demonstrate that the proposed algorithm achieves approximately 59% improvement in the average sum rate, substantially enhancing overall network reliability compared to existing benchmark schemes. Full article
(This article belongs to the Special Issue Drone Communication, Networking, and Trajectory Control in Urban Environments)
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23 pages, 7195 KiB  
Article
Unmanned Aerial Vehicle-Enabled Aerial Radio Environment Map Construction: A Multi-Stage Approach to Data Sampling and Path Planning
by Junyi Lin, Hongjun Wang, Tao Wu, Zhexian Shen, Ruhao Jiang and Xiaochen Fan
Drones 2025, 9(2), 81; https://doi.org/10.3390/drones9020081 - 21 Jan 2025
Viewed by 921
Abstract
An aerial Radio Environment Map (REM) characterizes the spatial distribution of Received Signal Strength (RSS) across a geographic space of interest, which is crucial for optimizing wireless communication in the air. Aerial REM construction can rely on Unmanned Aerial Vehicles (UAVs) to autonomously [...] Read more.
An aerial Radio Environment Map (REM) characterizes the spatial distribution of Received Signal Strength (RSS) across a geographic space of interest, which is crucial for optimizing wireless communication in the air. Aerial REM construction can rely on Unmanned Aerial Vehicles (UAVs) to autonomously select interesting positions for sampling RSS data, enhancing the quality of construction. However, due to the lack of prior information about the environment, it is challenging for UAVs to determine suitable sampling positions online. Additionally, achieving efficient exploration of the target area through collaboration among multiple UAVs is difficult. To address this issue, this paper proposes a multi-stage approach to data sampling and path planning with multiple UAVs. Specifically, the UAVs’ data sampling task over the target area is divided into multiple stages. By selecting an appropriate stage position, we use the RSS values at that position to determine whether additional data need to be sampled in a specific local area. At each stage, the area is divided into Voronoi diagrams based on the current position of each UAV, assigning each UAV its own region to explore. In our sampling strategy, the probability distribution for sampling is obtained by estimating the RSS and uncertainty of unsampled positions and then taking the weighted sum of these two values. To obtain the shortest flight path for selected sampling positions, we employ a network structure based on self-attention as the policy network, which is trained through the actor–critic framework to obtain an improvement heuristic strategy, replacing traditional manually designed strategies. Experimental results across three different scenarios indicate that the approach improves the quality of aerial REM construction while efficiently planning the shortest paths for UAVs between sampling positions. Full article
(This article belongs to the Special Issue Drone Communication, Networking, and Trajectory Control in Urban Environments)
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