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Communication in Networks of Unmanned Aerial Vehicles (UAVs)
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Communication in Networks of Unmanned Aerial Vehicles (UAVs)

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Networks".

Deadline for manuscript submissions: closed (30 June 2020) | Viewed by 11770

Special Issue Editors

Prof. Dr. Hermann Hellwagner

E-Mail Website
Guest Editor
Institute of Information Technology, Klagenfurt University, Klagenfurt, Austria
Interests: Multimedia Communication; Distributed Multimedia Systems; Information-Centric Networking; Communication in Networks of Unmanned Aerial Vehicles (UAVs)
Prof. Dr. Cheng-Hsin Hsu

E-Mail Website
Guest Editor
Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan
Interests: Multimedia Networking; Mobile Computing, Broadcast/Wireless Networks; Internet of Things (IoT); Networked Games; Cloud/Fog Computing
Prof. Dr. Enrico Natalizio

E-Mail Website
Guest Editor
LORIA Laboratory, University of Lorraine, Vandœuvre-lès-Nancy, France
Interests: networks of intelligent objects; UAV, robot and sensor communications; security and privacy in the Internet of Things
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Sofie Pollin

E-Mail Website
Guest Editor
Departement Elektrotechniek (ESAT), KU Leuven, 3001 Leuven, Belgium
Interests: wireless communication; software defined radio and cognitive radio; sensor networks; energy-proportional communication; wireless standards: WLAN, WPAN, LTE; cross-layer optimization; learning in networks; aerial sensor networks
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Unmanned aerial vehicles (UAVs) have entered many fields of application, such as disaster management, search and rescue, localization and mapping, structural inspection, transportation and delivery of goods, pollution and radiation monitoring, precision farming, etc. In recent years, research has intensified on networks of UAVs (or, UAV swarms) and, consequently, on enabling the autonomous and collaborative behavior of UAV swarms, e.g., for autonomous simultaneous localization and mapping, navigation, and reconstruction. An important building block in that endeavor is to provide high performance and robust wireless communication capabilities among UAVs (air-to-air) and to/from ground stations or sensors (air-to-ground).

This Special Issue is devoted to reporting novel scientific ideas, approaches, results, and (prototype) solutions/applications on communication in UAV swarms and with ground entities. Contributions are solicited in the wide spectrum of topics related to UAV communication, as exemplarily listed as “keywords” below. We particularly welcome submissions addressing 4G+ and 5G networks as well as novel networking concepts adapted/adopted to improve UAV swarm communication (SDR/SDN, NFV, MEC, ICN).

Prof. Dr. Hermann Hellwagner
Prof. Dr. Cheng-Hsin Hsu
Prof. Dr. Enrico Natalizio
Prof. Dr. Sofie Pollin
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. Sensors 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 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

  • Communication technologies (e.g., WLANs, 4G/5G cellular systems, WANs, delay-tolerant networks) 
  • Communication architectures (e.g., communication protocols, routing, operating systems, software frameworks, libraries) 
  • Communication optimization, decision, and learning models (e.g., when to communicate what to whom) 
  • Interaction of communication with flight mission (e.g., swarm movement, formation, coordination, collaboration, autonomous behaviour) 
  • Novel networking concepts for UAV swarm communication (including but not limited to software-defined radio and networking (SDR/SDN), network function virtualization (NFV), (multi-access) edge computing (MEC), information-centric networking (ICN)) 
  • Energy consumption and energy-efficient communication
  • Security of communication 
  • Communication performance evaluation 
  • Experimental and benchmark results on UAV swarm communication for novel applications (e.g., from prototypes, test beds, demonstrations, measurement campaigns)

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Published Papers (3 papers)

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Research

32 pages, 993 KiB  
Article
Energy-Efficient UAVs Deployment for QoS-Guaranteed VoWiFi Service
by Vicente Mayor, Rafael Estepa, Antonio Estepa and Germán Madinabeitia
Sensors 2020, 20(16), 4455; https://doi.org/10.3390/s20164455 - 10 Aug 2020
Cited by 12 | Viewed by 3647
Abstract
This paper formulates a new problem for the optimal placement of Unmanned Aerial Vehicles (UAVs) geared towards wireless coverage provision for Voice over WiFi (VoWiFi) service to a set of ground users confined in an open area. Our objective function is constrained by [...] Read more.
This paper formulates a new problem for the optimal placement of Unmanned Aerial Vehicles (UAVs) geared towards wireless coverage provision for Voice over WiFi (VoWiFi) service to a set of ground users confined in an open area. Our objective function is constrained by coverage and by VoIP speech quality and minimizes the ratio between the number of UAVs deployed and energy efficiency in UAVs, hence providing the layout that requires fewer UAVs per hour of service. Solutions provide the number and position of UAVs to be deployed, and are found using well-known heuristic search methods such as genetic algorithms (used for the initial deployment of UAVs), or particle swarm optimization (used for the periodical update of the positions). We examine two communication services: (a) one bidirectional VoWiFi channel per user; (b) single broadcast VoWiFi channel for announcements. For these services, we study the results obtained for an increasing number of users confined in a small area of 100 m2 as well as in a large area of 10,000 m2. Results show that the drone turnover rate is related to both users’ sparsity and the number of users served by each UAV. For the unicast service, the ratio of UAVs per hour of service tends to increase with user sparsity and the power of radio communication represents 14–16% of the total UAV energy consumption depending on ground user density. In large areas, solutions tend to locate UAVs at higher altitudes seeking increased coverage, which increases energy consumption due to hovering. However, in the VoWiFi broadcast communication service, the traffic is scarce, and solutions are mostly constrained only by coverage. This results in fewer UAVs deployed, less total power consumption (between 20% and 75%), and less sensitivity to the number of served users. Full article
(This article belongs to the Special Issue Communication in Networks of Unmanned Aerial Vehicles (UAVs))
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19 pages, 531 KiB  
Article
An Energy Efficient Design of Computation Offloading Enabled by UAV
by Linpei Li, Xiangming Wen, Zhaoming Lu and Wenpeng Jing
Sensors 2020, 20(12), 3363; https://doi.org/10.3390/s20123363 - 13 Jun 2020
Cited by 9 | Viewed by 2889
Abstract
The data volume is exploding due to various newly-developing applications that call for stringent communication requirements towards 5th generation wireless systems. Fortunately, mobile edge computing makes it possible to relieve the heavy computation pressure of ground users and decrease the latency and energy [...] Read more.
The data volume is exploding due to various newly-developing applications that call for stringent communication requirements towards 5th generation wireless systems. Fortunately, mobile edge computing makes it possible to relieve the heavy computation pressure of ground users and decrease the latency and energy consumption. What is more, the unmanned aerial vehicle has the advantages of agility and easy deployment, which gives the unmanned aerial vehicle enabled mobile edge computing system opportunities to fly towards areas with communication demand, such as hotspot areas. However, the limited endurance time of unmanned aerial vehicle affects the performance of mobile edge computing services, which results in the incomplete mobile edge computing services under the time limit. Consequently, this paper concerns the energy-efficient scheme design of the unmanned aerial vehicle while providing high-quality offloading services for ground users, particularly in the regions where the ground communication infrastructures are overloaded or damaged after natural disasters. Firstly, the model of energy-efficient design of the unmanned aerial vehicle is set up taking the constraints of the energy limitation of the unmanned aerial vehicle, the data causality, and the speed of the unmanned aerial vehicle into account. Subsequently, aiming at maximizing the energy efficiency of the unmanned aerial vehicle in the unmanned aerial vehicle enabled mobile edge computing system, the bits allocation in each time slot and the trajectory of the unmanned aerial vehicle are jointly optimized. Secondly, a successive convex approximation based alternating algorithm is brought forward to deal with the non-convex energy efficiency maximization problem. Finally, it is proved that the proposed energy efficient scheme design of the unmanned aerial vehicle is superior to other benchmark schemes by the simulation results. Besides, how the performance of proposed scheme design change under different parameters is discussed. Full article
(This article belongs to the Special Issue Communication in Networks of Unmanned Aerial Vehicles (UAVs))
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25 pages, 9948 KiB  
Article
Ocean Surface Drifting Buoy System Based on UAV-Enabled Wireless Powered Relay Network
by Haole Chen, Feng Yin, Wei Huang, Mingliu Liu and Deshi Li
Sensors 2020, 20(9), 2598; https://doi.org/10.3390/s20092598 - 2 May 2020
Cited by 13 | Viewed by 4342
Abstract
We design an ocean surface drifting buoy system based on an unmanned aerial vehicle (UAV)-enabled wireless powered relay network in which the UAV acts as mobile hybrid access point that broadcasts energy to all buoys in the downlink and forwards information from the [...] Read more.
We design an ocean surface drifting buoy system based on an unmanned aerial vehicle (UAV)-enabled wireless powered relay network in which the UAV acts as mobile hybrid access point that broadcasts energy to all buoys in the downlink and forwards information from the buoys to a ship signal tower (ST) in the uplink. In order to maximize the resource allocation efficiency of the system, due to the different initial energy reserve of the buoys, a novel communication mode selection strategy is proposed. In the direct transmission mode (DT mode), an energy-sufficient buoy transmits information directly to the ST, and in the relay transmission mode (RT mode), an energy-insufficient buoy relays information to the ST through the UAV. By applying the block coordinate descent and successive convex optimization, a joint UAV trajectory and resource allocation algorithm is proposed to maximize the minimum throughput of the buoys to work in the RT mode. Simulation results show that the proposed algorithm can significantly improve the minimum throughput of the ocean surface drifting buoys. Full article
(This article belongs to the Special Issue Communication in Networks of Unmanned Aerial Vehicles (UAVs))
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