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 2349

Special Issue Editors


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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

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

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

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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Published Papers (3 papers)

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Research

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 176
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
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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
Viewed by 639
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
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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 831
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
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