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Drones
Special Issues
Advances in Green Communications and Networking for Drones
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Advances in Green Communications and Networking for Drones

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

Deadline for manuscript submissions: closed (15 November 2023) | Viewed by 3365

Special Issue Editors

Dr. Haejoon Jung

E-Mail Website
Guest Editor
Department of Electronic Engineering, Kyung Hee University, Seoul 02447, Republic of Korea
Interests: communication theory; wireless communications; wireless power transfer; statistical signal processing
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. In-Ho Lee

E-Mail Website
Guest Editor
School of Electronic & Electrical Engineering, Hankyong National University, Anseong, Republic of Korea
Interests: wireless communications
Dr. Jung-Bin Kim

E-Mail Website
Guest Editor
Electronics and Telecommunications Research Institute, Daejeon, Republic of Korea
Interests: wireless communications

Special Issue Information

Dear Colleagues,

Unmanned aerial vehicles (UAVs), commonly known as drones, have witnessed remarkable advancements in recent years and have become valuable tools in various applications. From aerial photography and surveillance to package delivery and infrastructure inspection, drones offer unprecedented capabilities and efficiency. However, the widespread deployment of drones also raises concerns about their environmental impact, particularly in terms of energy consumption and carbon emissions.

This Special Issue aims to explore the field of green communications and networking for drones, focusing on novel techniques, technologies, and strategies to enhance their energy efficiency, reduce their carbon footprint, and promote sustainable operation. We invite researchers, academics, and industry experts to contribute original research articles, review papers, and case studies on the latest advancements in this emerging field.

Topics of interest include but are not limited to:

  • Energy-efficient communication protocols and algorithms for drones;
  • Green networking architectures and infrastructures for drone systems;
  • Power management and optimization techniques for drone platforms;
  • Renewable energy harvesting and power supply solutions for drones;
  • Energy-aware routing, scheduling, and resource allocation in drone networks;
  • Energy-efficient data processing and storage mechanisms for drone applications;
  • Adaptive and autonomous energy management for drone swarms;
  • Integration of drones with green communication technologies, such as the Internet of Things (IoT) and 5G/6G networks;
  • Environmental impact assessment and life cycle analysis of drone systems;
  • Regulations, policies, and standards promoting green practices in drone operations;
  • Energy-efficient sensing and data acquisition techniques for drones;
  • Dynamic spectrum management and cognitive radio for green drone communications;
  • Lightweight and low-power communication hardware for drones;
  • Energy-efficient localization and navigation systems for drones;
  • Collaborative communication and networking strategies for drone swarms;
  • Energy-efficient communication and networking for autonomous drones;
  • Machine learning and artificial intelligence approaches for optimizing green drone communications;
  • Advanced antenna designs for improved energy efficiency in drone communications;
  • Cross-layer optimization techniques for energy-efficient drone networks;
  • Energy-efficient multimedia streaming and video transmission for drones;
  • Green communication protocols and networking solutions for urban drone applications.

Papers submitted to this Special Issue should present original, unpublished work and must not be under consideration for publication elsewhere. All submitted manuscripts will undergo a rigorous peer-review process following the journal's guidelines. Authors should adhere to the journal's formatting and submission guidelines, which can be found on the journal's website.

Dr. Haejoon Jung
Prof. Dr. In-Ho Lee
Dr. Jung-Bin Kim
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.

Published Papers (2 papers)

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19 pages, 1030 KiB  
Article
Energy Minimization in Reconfigurable Intelligent Surface-Assisted Unmanned Aerial Vehicle-Enabled Wireless Powered Mobile Edge Computing Systems with Rate-Splitting Multiple Access
by Jihyung Kim, Eunhye Hong, Jaemin Jung, Jinkyu Kang and Seongah Jeong
Drones 2023, 7(12), 688; https://doi.org/10.3390/drones7120688 - 25 Nov 2023
Cited by 1 | Viewed by 1423
Abstract
In this study, a reconfigurable intelligent surface (RIS)-assisted wireless-powered mobile edge computing (WP-MEC) system is proposed, where a single-antenna unmanned aerial vehicle (UAV)-mounted cloudlet provides offloading opportunities to K user equipments (UEs) with a single antenna, and the K UEs can harvest the [...] Read more.
In this study, a reconfigurable intelligent surface (RIS)-assisted wireless-powered mobile edge computing (WP-MEC) system is proposed, where a single-antenna unmanned aerial vehicle (UAV)-mounted cloudlet provides offloading opportunities to K user equipments (UEs) with a single antenna, and the K UEs can harvest the energy from the broadcast radio-frequency signals of the UAV. In addition, rate-splitting multiple access is used to provide offloading opportunities to multiple UEs for effective power control and high spectral efficiency. The aim of this paper is to minimize the total energy consumption by jointly optimizing the resource allocation in terms of time, power, computing frequency, and task load, along with the UAV trajectory and RIS phase-shift matrix. Since coupling issues between optimization variable designs are caused, however, an alternating optimization-based algorithm is developed. The performance of the proposed algorithm is verified via simulations and compared with the benchmark schemes of partial optimizations of resource allocation, path planning, and RIS phase design. The proposed algorithm exhibits high performance in WP-MEC systems with insufficient resources, e.g., achieving up to 40% energy reduction for a UAV with eight elements of RIS. Full article
(This article belongs to the Special Issue Advances in Green Communications and Networking for Drones)
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15 pages, 524 KiB  
Article
Secrecy Energy Efficiency Maximization for Secure Unmanned-Aerial-Vehicle-Assisted Simultaneous Wireless Information and Power Transfer Systems
by Daehan Ha, Seongah Jeong, Jinkyu Kang and Joonhyuk Kang
Drones 2023, 7(11), 672; https://doi.org/10.3390/drones7110672 - 12 Nov 2023
Viewed by 1575
Abstract
Unmanned aerial vehicle (UAV)-assisted simultaneous wireless information and power transfer (SWIPT) systems have recently gained significant attraction in internet-of-things (IoT) applications that have limited or no infrastructure. Specifically, the free mobility of UAVs in three-dimensional (3D) space allows us good-quality channel links, thereby [...] Read more.
Unmanned aerial vehicle (UAV)-assisted simultaneous wireless information and power transfer (SWIPT) systems have recently gained significant attraction in internet-of-things (IoT) applications that have limited or no infrastructure. Specifically, the free mobility of UAVs in three-dimensional (3D) space allows us good-quality channel links, thereby enhancing the communication environment and improving performance in terms of achievable rates, latency, and energy efficiency. Meanwhile, IoT devices can extend their battery life by harvesting the energy following the SWIPT protocol, which leads to an increase in the overall system lifespan. In this paper, we propose a secure UAV-assisted SWIPT system designed to optimize the secrecy energy efficiency (SEE) of a ground network, wherein a base station (BS) transmits confidential messages to an energy-constrained device in the presence of a passive eavesdropper. Here, we employ a UAV acting as a helper node to improve the SEE of the system and to aid in the energy harvesting (EH) of the battery-limited ground device following the SWIPT protocol. To this end, we formulate the SEE maximization problem by jointly optimizing the transmit powers of the BS and UAV, the power-splitting ratio for EH operations, and the UAV’s flight path. The solution is obtained via a proposed algorithm that leverages successive convex approximation (SCA) and Dinkelbach’s method. Through simulations, we corroborate the feasibility and effectiveness of the proposed algorithm compared to conventional partial optimization approaches. Full article
(This article belongs to the Special Issue Advances in Green Communications and Networking for Drones)
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