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Unmanned Aerial Vehicle (UAV)-Enabled Wireless Communications and Networking

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

Deadline for manuscript submissions: closed (15 January 2022) | Viewed by 49392

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Guest Editor
Department of Information Technology, IMEC-Ghent University-WAVES, Technologiepark-Zwijnaarde 126, 9052 Ghent, Belgium
Interests: (green) wireless network design; energy- and exposure-aware networking; 5G and beyond 5G networks; unmanned aerial networks; Internet of Animals; digital agriculture; machine learning
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Special Issue Information

Dear Colleagues,

 

The emerging massive density of human-held and machine-type nodes implies a larger deviation in the traffic than we are facing today. The future network will be characterized by a high degree of flexibility, allowing it to adapt smoothly, autonomously, and efficiently to the quickly changing traffic demand both in time and space. This flexibility cannot be achieved when the network’s infrastructure remains static. To this end, the topic of UAV (unmanned aerial vehicle)-enabled wireless communications and networking has lately been receiving a lot of attention.

 

As mentioned above, in the future, the network has to serve a massive density of nodes which can be either human-held (user devices) or machine-type nodes (sensors). If we want to properly serve these sensors and get the most out of their data, a proper wireless connection is fundamental. By using UAV-enabled communication and networks, we will able to achieve this.

 

This Special Issue will address the many open issues that still exist to allow UAV-enabled wireless communications and networking.

Dr. Margot Deruyck
Guest Editor

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Keywords

  • UAV-aided network
  • UAV-enabled communication
  • drones
  • UABS
  • 5G
  • beyond 5G

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Published Papers (13 papers)

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Editorial

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3 pages, 182 KiB  
Editorial
Editorial: Special Issue “Unmanned Aerial Vehicle (UAV)-Enabled Wireless Communications and Networking”
by Margot Deruyck
Sensors 2022, 22(12), 4458; https://doi.org/10.3390/s22124458 - 13 Jun 2022
Viewed by 1090
Abstract
In the last decade, the behavior of mobile data users has completely changed [...] Full article

Research

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23 pages, 1592 KiB  
Article
Continuous Hidden Markov Model Based Spectrum Sensing with Estimated SNR for Cognitive UAV Networks
by Yuqing Feng, Wenjun Xu, Zhi Zhang and Fengyu Wang
Sensors 2022, 22(7), 2620; https://doi.org/10.3390/s22072620 - 29 Mar 2022
Cited by 5 | Viewed by 1820
Abstract
In this paper, to enhance the spectrum utilization in cognitive unmanned aerial vehicle networks (CUAVNs), we propose a cooperative spectrum sensing scheme based on a continuous hidden Markov model (CHMM) with a novel signal-to-noise ratio (SNR) estimation method. First, to exploit the Markov [...] Read more.
In this paper, to enhance the spectrum utilization in cognitive unmanned aerial vehicle networks (CUAVNs), we propose a cooperative spectrum sensing scheme based on a continuous hidden Markov model (CHMM) with a novel signal-to-noise ratio (SNR) estimation method. First, to exploit the Markov property in the spectrum state, we model the spectrum states and the corresponding fusion values as a hidden Markov model. A spectrum prediction is obtained by combining the parameters of CHMM and a preliminary sensing result (obtained from a clustered heterogeneous two-stage-fusion scheme), and this prediction can further guide the sensing detection procedure. Then, we analyze the detection performance of the proposed scheme by deriving its closed-formed expressions. Furthermore, considering imperfect SNR estimation in practical applications, we design a novel SNR estimation scheme which is inspired by the reconstruction of the signal on graphs to enhance the proposed CHMM-based sensing scheme with practical SNR estimation. Simulation results demonstrate the proposed CHMM-based cooperative spectrum sensing scheme outperforms the ones without CHMM, and the CHMM-based sensing scheme with the proposed SNR estimator can outperform the existing algorithm considerably. Full article
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20 pages, 8547 KiB  
Article
Deep Q-Learning-Based Transmission Power Control of a High Altitude Platform Station with Spectrum Sharing
by Seongjun Jo, Wooyeol Yang, Haing Kun Choi, Eonsu Noh, Han-Shin Jo and Jaedon Park
Sensors 2022, 22(4), 1630; https://doi.org/10.3390/s22041630 - 19 Feb 2022
Cited by 9 | Viewed by 2226
Abstract
A High Altitude Platform Station (HAPS) can facilitate high-speed data communication over wide areas using high-power line-of-sight communication; however, it can significantly interfere with existing systems. Given spectrum sharing with existing systems, the HAPS transmission power must be adjusted to satisfy the interference [...] Read more.
A High Altitude Platform Station (HAPS) can facilitate high-speed data communication over wide areas using high-power line-of-sight communication; however, it can significantly interfere with existing systems. Given spectrum sharing with existing systems, the HAPS transmission power must be adjusted to satisfy the interference requirement for incumbent protection. However, excessive transmission power reduction can lead to severe degradation of the HAPS coverage. To solve this problem, we propose a multi-agent Deep Q-learning (DQL)-based transmission power control algorithm to minimize the outage probability of the HAPS downlink while satisfying the interference requirement of an interfered system. In addition, a double DQL (DDQL) is developed to prevent the potential risk of action-value overestimation from the DQL. With a proper state, reward, and training process, all agents cooperatively learn a power control policy for achieving a near-optimal solution. The proposed DQL power control algorithm performs equal or close to the optimal exhaustive search algorithm for varying positions of the interfered system. The proposed DQL and DDQL power control yields the same performance, which indicates that the actional value overestimation does not adversely affect the quality of the learned policy. Full article
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17 pages, 3166 KiB  
Article
Resource Allocation in Uplink NOMA-IoT Based UAV for URLLC Applications
by Rana Karem, Mehaseb Ahmed and Fatma Newagy
Sensors 2022, 22(4), 1566; https://doi.org/10.3390/s22041566 - 17 Feb 2022
Cited by 9 | Viewed by 2292
Abstract
One of the main targets of future 5G cellular networks is enlarging the Internet of Things (IoT) devices’ connectivity while facing the challenging requirements of the available bandwidth, power and the restricted delay limits. Unmanned aerial vehicles (UAVs) have been recently used as [...] Read more.
One of the main targets of future 5G cellular networks is enlarging the Internet of Things (IoT) devices’ connectivity while facing the challenging requirements of the available bandwidth, power and the restricted delay limits. Unmanned aerial vehicles (UAVs) have been recently used as aerial base stations (BSs) to empower the line of sight (LoS), throughput and coverage of wireless networks. Moreover, non-orthogonal multiple access (NOMA) has become a bright multiple access technology. In this paper, NOMA is combined with UAV for establishing a high-capacity IoT uplink multi-application network, where the resource allocation problem is formulated with the objective of maximizing the system throughput while minimizing the delay of IoT applications. Moreover, power allocation was investigated to achieve fairness between users. The results show the superiority of the proposed algorithm, which achieves 31.8% delay improvement, 99.7% reliability increase and 50.8% fairness enhancement when compared to the maximum channel quality indicator (max CQI) algorithm in addition to preserving the system sum rate, spectral efficiency and complexity. Consequently, the proposed algorithm can be efficiently used in ultra-reliable low-latency communication (URLLC). Full article
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16 pages, 2218 KiB  
Article
Cooperative Friendly Jamming Techniques for Drone-Based Mobile Secure Zone
by Ga-Hye Jeon, Ji-Hyun Lee, Yeon-Su Sung, Hyun-Ju Park, You-Jin Lee, Sun-Woo Yun and Il-Gu Lee
Sensors 2022, 22(3), 865; https://doi.org/10.3390/s22030865 - 24 Jan 2022
Cited by 4 | Viewed by 3142
Abstract
Threats of eavesdropping and information leakages have increased sharply owing to advancements in wireless communication technology. In particular, the Internet of Things (IoT) has become vulnerable to sniffing or jamming attacks because broadcast communication is usually conducted in open-network environments. Although improved security [...] Read more.
Threats of eavesdropping and information leakages have increased sharply owing to advancements in wireless communication technology. In particular, the Internet of Things (IoT) has become vulnerable to sniffing or jamming attacks because broadcast communication is usually conducted in open-network environments. Although improved security protocols have been proposed to overcome the limitations of wireless-communication technology and to secure safe communication channels, they are difficult to apply to mobile communication networks and IoT because complex hardware is required. Hence, a novel security model with a lighter weight and greater mobility is needed. In this paper, we propose a security model applying cooperative friendly jamming using artificial noise and drone mobility, which are autonomous moving objects, and we demonstrate the prevention of eavesdropping and improved security through simulations and field tests. The Cooperative Friendly Jamming Techniques for Drone-based Mobile Secure Zone (CFJ-DMZ) can set a secure zone in a target area to support a safe wireless mobile communication network through friendly jamming, which can effectively reduce eavesdropping threats. According to the experimental results, the average information leakage rate of the eavesdroppers in CFJ-DMZ-applied scenarios was less than or equal to 3%, an average improvement of 92% over conventional methods. Full article
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18 pages, 835 KiB  
Article
Dynamic Selection Techniques for Detecting GPS Spoofing Attacks on UAVs
by Tala Talaei Khoei, Shereen Ismail and Naima Kaabouch
Sensors 2022, 22(2), 662; https://doi.org/10.3390/s22020662 - 15 Jan 2022
Cited by 40 | Viewed by 3655
Abstract
Unmanned aerial vehicles are prone to several cyber-attacks, including Global Positioning System spoofing. Several techniques have been proposed for detecting such attacks. However, the recurrence and frequent Global Positioning System spoofing incidents show a need for effective security solutions to protect unmanned aerial [...] Read more.
Unmanned aerial vehicles are prone to several cyber-attacks, including Global Positioning System spoofing. Several techniques have been proposed for detecting such attacks. However, the recurrence and frequent Global Positioning System spoofing incidents show a need for effective security solutions to protect unmanned aerial vehicles. In this paper, we propose two dynamic selection techniques, Metric Optimized Dynamic selector and Weighted Metric Optimized Dynamic selector, which identify the most effective classifier for the detection of such attacks. We develop a one-stage ensemble feature selection method to identify and discard the correlated and low importance features from the dataset. We implement the proposed techniques using ten machine-learning models and compare their performance in terms of four evaluation metrics: accuracy, probability of detection, probability of false alarm, probability of misdetection, and processing time. The proposed techniques dynamically choose the classifier with the best results for detecting attacks. The results indicate that the proposed dynamic techniques outperform the existing ensemble models with an accuracy of 99.6%, a probability of detection of 98.9%, a probability of false alarm of 1.56%, a probability of misdetection of 1.09%, and a processing time of 1.24 s. Full article
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19 pages, 731 KiB  
Article
Enhanced Dynamic Spectrum Access in UAV Wireless Networks for Post-Disaster Area Surveillance System: A Multi-Player Multi-Armed Bandit Approach
by Amr Amrallah, Ehab Mahmoud Mohamed, Gia Khanh Tran and Kei Sakaguchi
Sensors 2021, 21(23), 7855; https://doi.org/10.3390/s21237855 - 25 Nov 2021
Cited by 10 | Viewed by 2162
Abstract
Modern wireless networks are notorious for being very dense, uncoordinated, and selfish, especially with greedy user needs. This leads to a critical scarcity problem in spectrum resources. The Dynamic Spectrum Access system (DSA) is considered a promising solution for this scarcity problem. With [...] Read more.
Modern wireless networks are notorious for being very dense, uncoordinated, and selfish, especially with greedy user needs. This leads to a critical scarcity problem in spectrum resources. The Dynamic Spectrum Access system (DSA) is considered a promising solution for this scarcity problem. With the aid of Unmanned Aerial Vehicles (UAVs), a post-disaster surveillance system is implemented using Cognitive Radio Network (CRN). UAVs are distributed in the disaster area to capture live images of the damaged area and send them to the disaster management center. CRN enables UAVs to utilize a portion of the spectrum of the Electronic Toll Collection (ETC) gates operating in the same area. In this paper, a joint transmission power selection, data-rate maximization, and interference mitigation problem is addressed. Considering all these conflicting parameters, this problem is investigated as a budget-constrained multi-player multi-armed bandit (MAB) problem. The whole process is done in a decentralized manner, where no information is exchanged between UAVs. To achieve this, two power-budget-aware PBA-MAB) algorithms, namely upper confidence bound (PBA-UCB (MAB) algorithm and Thompson sampling (PBA-TS) algorithm, were proposed to realize the selection of the transmission power value efficiently. The proposed PBA-MAB algorithms show outstanding performance over random power value selection in terms of achievable data rate. Full article
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23 pages, 2525 KiB  
Article
Optimal UAV Deployment and Resource Management in UAV Relay Networks
by Sang Ik Han and Jaeuk Baek
Sensors 2021, 21(20), 6878; https://doi.org/10.3390/s21206878 - 16 Oct 2021
Cited by 5 | Viewed by 2341
Abstract
UAV equipped three-dimensional (3D) wireless networks can provide a solution for the requirements of 5G communications, such as enhanced Mobile Broadband (eMBB) and massive Machine Type Communications (mMTC). Especially, the introduction of an unmanned aerial vehicle (UAV) as a relay node can improve [...] Read more.
UAV equipped three-dimensional (3D) wireless networks can provide a solution for the requirements of 5G communications, such as enhanced Mobile Broadband (eMBB) and massive Machine Type Communications (mMTC). Especially, the introduction of an unmanned aerial vehicle (UAV) as a relay node can improve the connectivity, extend the terrestrial base station (BS) coverage and enhance the throughput by taking advantage of a strong air-to-ground line of sight (LOS) channel. In this paper, we consider the deployment and resource allocation of UAV relay network (URN) to maximize the throughput of user equipment (UE) within a cell, while guaranteeing a reliable transmission to UE outside the coverage of BS. To this end, we formulate joint UAV deployment and resource allocation problems, whose analytical solutions can be hardly obtained, in general. We propose a fast and practical algorithm to provide the optimal solution for the number of transmit time slots and the UAV relay location in a sequential manner. The transmit power at BS and UAV is determined in advance based on the availability of channel state information (CSI). Simulation results demonstrate that the proposed algorithms can significantly reduce the computational effort and complexity to determine the optimal UAV location and transmit time slots over an exhaustive search. Full article
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18 pages, 989 KiB  
Article
Analytical Blind Beamforming for a Multi-Antenna UAV Base-Station Receiver in Millimeter-Wave Bands
by Pingchuan Liu, Kuangang Fan and Yuhang Chen
Sensors 2021, 21(19), 6561; https://doi.org/10.3390/s21196561 - 30 Sep 2021
Cited by 2 | Viewed by 1673
Abstract
Over the last decade, unmanned aerial vehicles (UAVs) with antenna arrays have usually been employed for the enhancement of wireless communication in millimeter-wave bands. They are commonly used as aerial base stations and relay platforms in order to serve multiple users. Many beamforming [...] Read more.
Over the last decade, unmanned aerial vehicles (UAVs) with antenna arrays have usually been employed for the enhancement of wireless communication in millimeter-wave bands. They are commonly used as aerial base stations and relay platforms in order to serve multiple users. Many beamforming methods for improving communication quality based on channel estimation have been proposed. However, these methods can be resource-intensive due to the complexity of channel estimation in practice. Thus, in this paper, we formulate an MIMO blind beamforming problem at the receivers for UAV-assisted communications in which channel estimation is omitted in order to save communication resources. We introduce one analytical method, which is called the analytical constant modulus algorithm (ACMA), in order to perform blind beamforming at the UAV base station; this relies only on data received by the antenna. The feature of the constant modulus (CM) is employed to restrict the target user signals. Algebraic operations, such as singular value decomposition (SVD), are applied to separate the user signal space from other interferences. The number of users in the region served by the UAV can be detected by exploring information in the measured data. We seek solutions that are expressible as one Kronecker product structure in the signal space; then, the beamformers that correspond to each user can be successfully estimated. The simulation results show that, by using this analytically derived blind method, the system can achieve good signal recovery accuracy, a reasonable system sum rate, and acceptable complexity. Full article
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19 pages, 3988 KiB  
Article
Algorithms for Delivery of Data by Drones in an Isolated Area Divided into Squares
by Adrian Marius Deaconu, Razvan Udroiu and Corina-Ştefania Nanau
Sensors 2021, 21(16), 5472; https://doi.org/10.3390/s21165472 - 13 Aug 2021
Cited by 9 | Viewed by 2461
Abstract
Drones are frequently used for the delivery of materials or other goods, and to facilitate the capture and transmission of data. Moreover, drone networks have gained significant interest in a number of scenarios, such as in quarantined or isolated areas, following technical damage [...] Read more.
Drones are frequently used for the delivery of materials or other goods, and to facilitate the capture and transmission of data. Moreover, drone networks have gained significant interest in a number of scenarios, such as in quarantined or isolated areas, following technical damage due to a disaster, or in non-urbanized areas without communication infrastructure. In this context, we propose a network of drones that are able to fly on a map covered by regular polygons, with a well-established mobility schedule, to carry and transfer data. Two means exist to equidistantly cover an area with points, namely, grouping the points into equilateral triangles or squares. In this study, a network of drones that fly in an aerial area divided into squares was proposed and investigated. This network was compared with the case in which the area is divided into equilateral triangles. The cost of the square drone network was lower than that of the triangular network with the same cell length, but the efficiency factors were better for the latter. Two situations related to increasing the drone autonomy using drone charging or battery changing stations were analyzed. This study proposed a Delay Tolerant Network (DTN) to optimize the transmission of data. Multiple simulation studies based on experimental flight tests were performed using the proposed algorithm versus five traditional DTN methods. A light Wi-Fi Arduino development board was used for the data transfer between drones and stations using delivery protocols. The efficiency of data transmission using single-copy and multiple-copy algorithms was analyzed. Simulation results showed a better performance of the proposed Time-Dependent Drone (TD-Drone) Dijkstra algorithm compared with the Epidemic, Spray and Wait, PRoPHET, MaxProp, and MaxDelivery routing protocols. Full article
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22 pages, 6081 KiB  
Article
Machine Learning for the Dynamic Positioning of UAVs for Extended Connectivity
by Francisco Oliveira, Miguel Luís and Susana Sargento
Sensors 2021, 21(13), 4618; https://doi.org/10.3390/s21134618 - 05 Jul 2021
Cited by 4 | Viewed by 2441
Abstract
Unmanned Aerial Vehicle (UAV) networks are an emerging technology, useful not only for the military, but also for public and civil purposes. Their versatility provides advantages in situations where an existing network cannot support all requirements of its users, either because of an [...] Read more.
Unmanned Aerial Vehicle (UAV) networks are an emerging technology, useful not only for the military, but also for public and civil purposes. Their versatility provides advantages in situations where an existing network cannot support all requirements of its users, either because of an exceptionally big number of users, or because of the failure of one or more ground base stations. Networks of UAVs can reinforce these cellular networks where needed, redirecting the traffic to available ground stations. Using machine learning algorithms to predict overloaded traffic areas, we propose a UAV positioning algorithm responsible for determining suitable positions for the UAVs, with the objective of a more balanced redistribution of traffic, to avoid saturated base stations and decrease the number of users without a connection. The tests performed with real data of user connections through base stations show that, in less restrictive network conditions, the algorithm to dynamically place the UAVs performs significantly better than in more restrictive conditions, reducing significantly the number of users without a connection. We also conclude that the accuracy of the prediction is a very important factor, not only in the reduction of users without a connection, but also on the number of UAVs deployed. Full article
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Review

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25 pages, 15826 KiB  
Review
Closing Connectivity Gap: An Overview of Mobile Coverage Solutions for Not-Spots in Rural Zones
by Diego Fernando Cabrera-Castellanos, Alejandro Aragón-Zavala and Gerardo Castañón-Ávila
Sensors 2021, 21(23), 8037; https://doi.org/10.3390/s21238037 - 01 Dec 2021
Cited by 10 | Viewed by 3248
Abstract
Access to broadband communications in different parts of the world has become a priority for some governments and regulatory authorities around the world in recent years. Building new digital roads and pursuing a connected society includes looking for easier access to the internet. [...] Read more.
Access to broadband communications in different parts of the world has become a priority for some governments and regulatory authorities around the world in recent years. Building new digital roads and pursuing a connected society includes looking for easier access to the internet. In general, not all areas where people congregate are fully covered, especially in rural zones, thus restricting access to data communications and inducing inequality. In the present review article, we have comprehensively surveyed the use of three platforms to deliver broadband services to such remote and low-income areas, and they are proposed as follows: unmanned aerial vehicles (UAV), altitude platforms (AP), and low-Earth orbit (LEO) satellites. These novel strategies support the connected and accessible world hypothesis. Hence, UAVs are considered a noteworthy solution since their efficient maneuverability can solve rural coverage issues or not-spots. Full article
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24 pages, 1015 KiB  
Review
The Internet of Drones: Requirements, Taxonomy, Recent Advances, and Challenges of Research Trends
by Abdelzahir Abdelmaboud
Sensors 2021, 21(17), 5718; https://doi.org/10.3390/s21175718 - 25 Aug 2021
Cited by 54 | Viewed by 18409
Abstract
The use of unmanned aerial vehicles or drones are a valuable technique in coping with issues related to life in the general public’s daily routines. Given the growing number of drones in low-altitude airspace, linking drones to form the Internet of drones (IoD) [...] Read more.
The use of unmanned aerial vehicles or drones are a valuable technique in coping with issues related to life in the general public’s daily routines. Given the growing number of drones in low-altitude airspace, linking drones to form the Internet of drones (IoD) is a highly desirable trend to improve the safety as well as the quality of flight. However, there remain security, privacy, and communication issues related to IoD. In this paper, we discuss the key requirements of security, privacy, and communication and we present a taxonomy of IoD based on the most relevant considerations. Furthermore, we present the most commonly used commercial case studies and address the latest advancements and solutions proposed for the IoD environments. Lastly, we discuss the challenges and future research directions of IoD. Full article
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