scholarly journals Flying Height Optimization for Unmanned Aerial Vehicles in Cellular - Flying Adhoc Network

2018 ◽  
Vol 2 (4) ◽  
pp. 216
Author(s):  
Quynh Ngo ◽  
Duc Ngoc Minh Dang ◽  
Khoa Anh Tran
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Cellular Network ◽  
Base Stations ◽  
Flying Height ◽  
Medium Access ◽  
Creative Commons ◽  
Aerial Vehicles ◽  
Adhoc Network ◽  
Geometry Analysis ◽  
Design Factors

In Flying Adhoc NETwork (FANET), the communications between Unmanned Aerial Vehicles (UAV), UAVs to infrastructure, and UAVs to wireless sensors are crucial design factors. With strict energy constrain during flying operation, the allocation of power and resources, the flying strategy, and the medium access mechanism shall be effectively used. When employing cellular network as backhaul for UAVs, the flying height of UAVs not only affects the communication between UAVs and end users on the ground, but also determines the reception between infrastructure (base stations from the cellular network) to UAVs. In this paper, we optimize the flying height of UAVs for better reception from the cellular network by using stochastic geometry analysis to model the aggregated interference at the UAV side. The network system performance is also examined under the effect of fading-less channel and Rayleigh fading channel.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium provided the original work is properly cited.

scholarly journals Remotely Sensed Water Limitation in Vegetation: Insights from an Experiment with Unmanned Aerial Vehicles (UAVs)

2019 ◽  
Author(s):  
Kelly Easterday ◽  
Chippie Kislik ◽  
Tod E. Dawson ◽  
Sean Hogan ◽  
Maggi Kelly
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Water Content ◽  
Water Deficit ◽  
Water Status ◽  
Field Measurements ◽  
Flying Height ◽  
Plant Water ◽  
Spectral Indices ◽  
Aerial Vehicles ◽  
The Relationship

Unmanned aerial vehicles (UAVs) equipped with multispectral sensors present an opportunity to monitor vegetation with on-demand high spatial and temporal resolution. In this study, we use multispectral imagery from quadcopter UAVs to monitor the progression of a water manipulation experiment on a common shrub, Baccharis pilularis (coyote brush), at the Blue Oak Ranch Reserve (BORR) near San Jose, California. We recorded multispectral data from the plants at several altitudes with nearly hourly intervals to explore the relationship between two common spectral indices, NDVI and NDRE, and plant water content and water potential, as physiological metrics of plant water status, across a gradient of water deficit. An examination of the spatial and temporal thresholds at which water limitations were most detectable revealed that the best separation between levels of water deficit were at higher resolution (lower flying height), and in the morning (NDVI) and early morning (NDRE). We found that both measures were able to identify moisture deficit in plants and distinguish them from control and watered plants; however, NDVI was better able to distinguish between treatments than NDRE and was more positively correlated with field measurements of plant water content than NDRE. Finally, we explored how relationships between spectral indices and water status changed when the imagery was scaled to courser resolutions provided by satellite-based imagery (PlanetScope) and found that PlanetScope data was able to capture the overall trend in treatments but was not able to capture subtle changes in water content. These kinds of experiments that evaluate the relationship between direct field measurements and UAV camera sensitivity are needed to enable translation of field-based physiology measurements to landscape or regional scales.

scholarly journals Smart Search System of Autonomous Flight UAVs for Disaster Rescue

Sensors ◽  
2021 ◽  
Vol 21 (20) ◽  
pp. 6810
Author(s):  
Donggeun Oh ◽  
Junghee Han
Keyword(s):  
Genetic Algorithm ◽  
Unmanned Aerial Vehicles ◽  
Base Stations ◽  
Localization Algorithm ◽  
Tracking Accuracy ◽  
Long Distance ◽  
Search System ◽  
Autonomous Flight ◽  
Shadow Area ◽  
Aerial Vehicles

UAVs (Unmanned Aerial Vehicles) have been developed and adopted for various fields including military, IT, agriculture, construction, and so on. In particular, UAVs are being heavily used in the field of disaster relief thanks to the fact that UAVs are becoming smaller and more intelligent. Search for a person in a disaster site can be difficult if the mobile communication network is not available, and if the person is in the GPS shadow area. Recently, the search for survivors using unmanned aerial vehicles has been studied, but there are several problems as the search is mainly using images taken with cameras (including thermal imaging cameras). For example, it is difficult to distinguish a distressed person from a long distance especially in the presence of cover. Considering these challenges, we proposed an autonomous UAV smart search system that can complete their missions without interference in search and tracking of castaways even in disaster areas where communication with base stations is likely to be lost. To achieve this goal, we first make UAVs perform autonomous flight with locating and approaching the distressed people without the help of the ground control server (GCS). Second, to locate a survivor accurately, we developed a genetic-based localization algorithm by detecting changes in the signal strength between distress and drones inside the search system. Specifically, we modeled our target platform with a genetic algorithm and we re-defined the genetic algorithm customized to the disaster site’s environment for tracking accuracy. Finally, we verified the proposed search system in several real-world sites and found that it successfully located targets with autonomous flight.

scholarly journals Efficient Deployment of Small Cell Base Stations Mounted on Unmanned Aerial Vehicles for the Internet of Things Infrastructure

2020 ◽  
Vol 20 (13) ◽  
pp. 7460-7471 ◽  
Author(s):  
Mohammad Javad Sobouti ◽  
Zahra Rahimi ◽  
Amir Hossein Mohajerzadeh ◽  
Seyed Amin Hosseini Seno ◽  
Reza Ghanbari ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Unmanned Aerial Vehicles ◽  
Small Cell ◽  
Base Stations ◽  
The Internet ◽  
Aerial Vehicles ◽  
The Internet Of Things ◽  
Cell Base

scholarly journals Medium Access Control Protocols for the Internet of Things Based on Unmanned Aerial Vehicles: A Comparative Survey

Sensors ◽  
2020 ◽  
Vol 20 (19) ◽  
pp. 5586
Author(s):  
Shreya Khisa ◽  
Sangman Moh
Keyword(s):  
Internet Of Things ◽  
Access Control ◽  
Medium Access Control ◽  
Unmanned Aerial Vehicles ◽  
Mac Protocols ◽  
The Internet ◽  
Medium Access ◽  
Aerial Vehicles ◽  
Iot Devices ◽  
The Internet Of Things

The Internet of Things (IoT), which consists of a large number of small low-cost devices, has become a leading solution for smart cities, smart agriculture, smart buildings, smart grids, e-healthcare, etc. Integrating unmanned aerial vehicles (UAVs) with IoT can result in an airborne UAV-based IoT (UIoT) system and facilitate various value-added services from sky to ground. In addition to wireless sensors, various kinds of IoT devices are connected in UIoT, making the network more heterogeneous. In a UIoT system, for achieving high throughput in an energy-efficient manner, it is crucial to design an efficient medium access control (MAC) protocol because the MAC layer is responsible for coordinating access among the IoT devices in the shared wireless medium. Thus, various MAC protocols with different objectives have been reported for UIoT. However, to the best of the authors’ knowledge, no survey had been performed so far that dedicatedly covers MAC protocols for UIoT. Hence, in this study, state-of-the-art MAC protocols for UIoT are investigated. First, the communication architecture and important design considerations of MAC protocols for UIoT are examined. Subsequently, different MAC protocols for UIoT are classified, reviewed, and discussed with regard to the main ideas, innovative features, advantages, limitations, application domains, and potential future improvements. The reviewed MAC protocols are qualitatively compared with regard to various operational characteristics and system parameters. Additionally, important open research issues and challenges with recommended solutions are summarized and discussed.

Towards a Predictive Analysis of UAV-Based Flying Base Station Decisions

2020 ◽  
Vol 16 (2) ◽  
pp. 20-52 ◽  
Author(s):  
Hamid Garmani ◽  
Driss Ait Omar ◽  
Mohamed El Amrani ◽  
Mohamed Baslam ◽  
Mostafa Jourhmane
Keyword(s):  
Nash Equilibrium ◽  
Unmanned Aerial Vehicles ◽  
Base Station ◽  
Base Stations ◽  
Practical Significance ◽  
Game Model ◽  
Activity Scheduling ◽  
Area Of Interest ◽  
Aerial Vehicles ◽  
Fairness Concern

The use of unmanned aerial vehicles (UAVs) as a communication platform is of great practical significance in the wireless communications field. This paper studies the activity scheduling of unmanned aerial vehicles acting as aerial base stations in an area of interest for a specific period. Specifically, competition among multiple UAVs is explored, and a game model for the competition is developed. The Nash equilibrium of the game model is then analyzed. Based on the analysis, an algorithm for Nash equilibrium computation is proposed. Then, a game model with fairness concern is established, and its equilibrium price is also analyzed. In addition, numerical examples are conducted to determine the factors that affect the strategies (price, quality of service, and beaconing duration) of the UAV and to show how the expected profits of UAVs change with that fairness concern point. The authors believe that this research paper will shed light on the application of UAV as a flying base station.

scholarly journals Integrating Cognitive Radio with Unmanned Aerial Vehicles: An Overview

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 830
Author(s):  
Guilherme Marcel Dias Santana ◽  
Rogers Silva de Cristo ◽  
Kalinka Regina Lucas Jaquie Castelo Branco
Keyword(s):  
Cognitive Radio ◽  
Unmanned Aerial Vehicles ◽  
Smart Cities ◽  
Low Cost ◽  
Real Data ◽  
Base Stations ◽  
Communication Performance ◽  
Transmission Frequency ◽  
Aerial Vehicles ◽  
Future Challenges

Unmanned Aerial Vehicles (UAVs) demand technologies so they can not only fly autonomously, but also communicate with base stations, flight controllers, computers, devices, or even other UAVs. Still, UAVs usually operate within unlicensed spectrum bands, competing against the increasing number of mobile devices and other wireless networks. Combining UAVs with Cognitive Radio (CR) may increase their general communication performance, thus allowing them to execute missions where the conventional UAVs face limitations. CR provides a smart wireless communication which, instead of using a transmission frequency defined in the hardware, uses software transmission. CR smartly uses free transmission channels and/or chooses them according to application’s requirements. Moreover, CR is considered a key enabler for deploying technologies that require high connectivity, such as Smart Cities, 5G, Internet of Things (IoT), and the Internet of Flying Things (IoFT). This paper presents an overview on the field of CR for UAV communications and its state-of-the-art, testbed alternatives for real data experiments, as well as specifications to build a simple and low-cost testbed, and indicates key opportunities and future challenges in the field.

scholarly journals Hybrid Direction of Arrival Precoding for Multiple Unmanned Aerial Vehicles Aided Non-Orthogonal Multiple Access in 6G Networks

2022 ◽  
Vol 12 (2) ◽  
pp. 895
Author(s):  
Laura Pierucci
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Multiple Access ◽  
Estimation Method ◽  
Direction Of Arrival ◽  
Base Station ◽  
Flying Height ◽  
Maximization Problem ◽  
Aerial Vehicles ◽  
Sum Rate ◽  
Hybrid Beamforming

Unmanned aerial vehicles (UAV) have attracted increasing attention in acting as a relay for effectively improving the coverage and data rate of wireless systems, and according to this vision, they will be integrated in the future sixth generation (6G) cellular network. Non-orthogonal multiple access (NOMA) and mmWave band are planned to support ubiquitous connectivity towards a massive number of users in the 6G and Internet of Things (IOT) contexts. Unfortunately, the wireless terrestrial link between the end-users and the base station (BS) can suffer severe blockage conditions. Instead, UAV relaying can establish a line-of-sight (LoS) connection with high probability due to its flying height. The present paper focuses on a multi-UAV network which supports an uplink (UL) NOMA cellular system. In particular, by operating in the mmWave band, hybrid beamforming architecture is adopted. The MUltiple SIgnal Classification (MUSIC) spectral estimation method is considered at the hybrid beamforming to detect the different direction of arrival (DoA) of each UAV. We newly design the sum-rate maximization problem of the UAV-aided NOMA 6G network specifically for the uplink mmWave transmission. Numerical results point out the better behavior obtained by the use of UAV relays and the MUSIC DoA estimation in the Hybrid mmWave beamforming in terms of achievable sum-rate in comparison to UL NOMA connections without the help of a UAV network.

scholarly journals Optimization of Base Location and Patrol Routes for Unmanned Aerial Vehicles in Border Intelligence, Surveillance and Reconnaissance

2018 ◽  
Author(s):  
Yao Liu ◽  
Zhong Liu ◽  
Jianmai Shi ◽  
Guohua Wu ◽  
Chao Chen
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Heuristic Algorithms ◽  
Programming Model ◽  
Base Station ◽  
Base Stations ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Solution Approach ◽  
Location Routing ◽  
Aerial Vehicles

The location routing problem of unmanned aerial vehicles (UAV) in border patrol for intelligence, surveillance and reconnaissance is investigated, where the location of UAV base stations and the UAV flying routes for visiting the targets in border area are jointly optimized. The capacity of the base station and the endurance of the UAV are considered. A binary integer programming model is developed to formulate the problem, and two heuristic algorithms combined with local search strategies are designed for solving the problem. The experiment design for simulating the distribution of stations and targets in border is proposed for generating random test instances. Also, an example based on the Sino-Vietnamese border is presented to illustrate the problem and the solution approach. The performance of the two algorithms are analyzed and compared through randomly generated instances.

scholarly journals Optimization of Base Location and Patrol Routes for Unmanned Aerial Vehicles in Border Intelligence, Surveillance and Reconnaissance

2019 ◽  
Author(s):  
Yao Liu ◽  
Zhong Liu ◽  
Jianmai Shi ◽  
Guohua Wu ◽  
Chao Chen
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Heuristic Algorithms ◽  
Programming Model ◽  
Base Station ◽  
Base Stations ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Solution Approach ◽  
Location Routing ◽  
Aerial Vehicles

The location routing problem of unmanned aerial vehicles (UAV) in border patrol for intelligence, surveillance and reconnaissance is investigated, where the location of UAV base stations and the UAV flying routes for visiting the targets in border area are jointly optimized. The capacity of the base station and the endurance of the UAV are considered. A binary integer programming model is developed to formulate the problem, and two heuristic algorithms combined with local search strategies are designed for solving the problem. The experiment design for simulating the distribution of stations and targets in border is proposed for generating random test instances. Also, an example based on the Sino-Vietnamese border is presented to illustrate the problem and the solution approach. The performance of the two algorithms are analyzed and compared through randomly generated instances.

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