Internet of Drones-Enabled Smart Cities

2020 ◽  
pp. 107-133
Author(s):  
Navuday Sharma ◽  
Maurizio Magarini ◽  
Muhammad Mahtab Alam
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Channel Model ◽  
Smart Cities ◽  
Base Stations ◽  
Cell Coverage ◽  
Optimal Replacement ◽  
Coverage Analysis ◽  
Channel Parameters ◽  
Aerial Platforms ◽  
Flash Crowds

Unmanned aerial vehicles (UAVs) are expected to provide data service to users as aerial base stations, as gateways to collect the data from various sensors, and as sensor-mounted aerial platforms deployed in smart cities. The study in this chapter initially starts with the air-to-ground (A2G) channel model. Due to the unavailability of channel parameters for UAVs at low altitudes, measurements were performed using a radio propagation simulator for generalized environments developed using ITU-R parameters. Further, cell coverage analysis is shown with simulation results obtained from the ray tracing. Later, an optimal replacement to UDNs was proposed to support the flash crowds and smart cites known as ultra-dense cloud drone network. This system is advantageous as it offers reduction in total cost of ownership due to its on-demand capability. Further, work is shown on implementing parameters for 5G physical layer with generalized frequency division multiplexing modulation over A2G channel on the UAV network to provide reliable and faster connectivity for ground users and sensors.

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.

Unmanned Aerial Vehicles for Smart Cities

2021 ◽  
pp. 444-477
Author(s):  
Tetiana Shmelova ◽  
Vitalii Lazorenko ◽  
Oleksandr Burlaka
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Aerial Photography ◽  
Smart Cities ◽  
First Aid ◽  
Mathematical Methods ◽  
Aerial Vehicles ◽  
Area Monitoring ◽  
The City ◽  
Navigation Information ◽  
Estimation Of Risk

In this chapter, the authors are presenting opportunities for the use of unmanned aerial vehicles (UAV) in town. Methods for the optimization of flight routes of UAVs in the dependence of target tasks in the city are presented, for example, area monitoring; search and rescue operations; retransmission of communication (in places, where the antenna coverage cannot be set due to terrain specifications); organization of logistics as the safe, cheap, and fast transportation method of goods; for aerial photography, for controlling traffic; for the provision of the first aid to people in emergencies; unmanned taxi. It is done using air navigation information and mathematical methods. Authors suggest dynamic programming methods, GRID analyses, expert judgment method, and fuzzy-logic methods for estimation of risk/safety of flights in the city. Optimization of flows and flexible redistribution of UAV routes in multilevel airspace is provided according to air navigation requirements and standards.

scholarly journals Performance Analysis of Millimeter-Wave UAV Swarm Networks under Blockage Effects

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4593
Author(s):  
Haejoon Jung ◽  
In-Ho Lee
Keyword(s):  
Millimeter Wave ◽  
Channel Model ◽  
High Mobility ◽  
Base Stations ◽  
Shape Theory ◽  
High Data ◽  
Mobile Cellular ◽  
Seamless Connectivity ◽  
Mobile Cellular Networks ◽  
Uav Swarm

Due to their high mobility, unmanned aerial vehicles (UAVs) can offer better connectivity by complement or replace with the existing terrestrial base stations (BSs) in the mobile cellular networks. In particular, introducing UAV and millimeter wave (mmWave) technologies can better support the future wireless networks with requirements of high data rate, low latency, and seamless connectivity. However, it is widely known that mmWave signals are susceptible to blockages because of their poor diffraction. In this context, we consider macro-diversity achieved by the multiple UAV BSs, which are randomly distributed in a spherical swarm. Using the widely used channel model incorporated with the distance-based random blockage effects, which is proposed based on stochastic geometry and random shape theory, we investigate the outage performance of the mmWave UAV swarm network. Further, based on our analysis, we show how to minimize the outage rate by adjusting various system parameters such as the size of the UAV swarm relative to the distance to the receiver.

scholarly journals Deployment of an aerial platform system for rapid restoration of communications links after a disaster: a machine learning approach

Computing ◽  
2019 ◽  
Vol 102 (4) ◽  
pp. 829-864 ◽  
Author(s):  
Faris A. Almalki ◽  
Marios C. Angelides
Keyword(s):  
Machine Learning ◽  
Physical Model ◽  
Ad Hoc Network ◽  
Ad Hoc ◽  
Propagation Model ◽  
Base Stations ◽  
Emergency Relief ◽  
Wide Range ◽  
Relief Operations ◽  
Aerial Platforms

AbstractHaving reliable telecommunication systems in the immediate aftermath of a catastrophic event makes a huge difference in the combined effort by local authorities, local fire and police departments, and rescue teams to save lives. This paper proposes a physical model that links base stations that are still operational with aerial platforms and then uses a machine learning framework to evolve ground-to-air propagation model for such an ad hoc network. Such a physical model is quick and easy to deploy and the underlying air-to-ground (ATG) propagation models are both resilient and scalable and may use a wide range of link budget, grade of service (GoS), and quality of service (QoS) parameters to optimise their performance and in turn the effectiveness of the physical model. The prediction results of a simulated deployment of such a physical model and the evolved propagation model in an ad hoc network offers much promise in restoring communication links during emergency relief operations.

scholarly journals An urban expressway forwarding scheme for cognitive Internet of vehicles

2020 ◽  
Vol 16 (3) ◽  
pp. 155014772091294
Author(s):  
Jing Wang ◽  
Huyin Zhang ◽  
Sheng Hao ◽  
Chuhao Fu
Keyword(s):  
Cognitive Radio ◽  
Traffic Safety ◽  
Smart Cities ◽  
Radio Spectrum ◽  
Base Stations ◽  
Radio Link ◽  
Integer Optimization ◽  
Internet Of Vehicles ◽  
Urban Expressway ◽  
Channel Availability

The Internet of vehicles is an essential component for building smart cities that can improve traffic safety and provide multimedia entertainment services. The cognitive radio–enabled Internet of vehicles was proposed to resolve the conflict between the increasing demand of Internet of vehicles applications and the limited spectrum resources. The multi-hop transmission is one of the most important issues in cognitive radio–enabled Internet of vehicles networks. Nevertheless, most existing forwarding solutions designed for the cognitive radio–enabled Internet of vehicles did not consider the urban expressway scenario, where primary base stations are densely installed with small coverage areas. In this case, it is difficult to ensure that the sender and the receiver of the same cognitive radio link have similar channel availability statistics, which makes cognitive radio links more likely to be interrupted. To address this challenge, we develop a multi-hop forwarding scheme to minimize the end-to-end delay for such networks. We first formulate the delay minimization problem as a non-linear integer optimization problem. Then, we propose an approach to select the relay candidates by jointly considering the high mobility of vehicles and the unique cognitive radio spectrum usage distributions in urban expressway scenarios. Finally, we propose the low-latency forwarding strategies by considering the channel availability and the delay cost of different situations of relay candidates. Simulations show the advantages of our proposed scheme, compared with state-of-art methods.

scholarly journals Coverage and Energy Efficiency Analysis for Two-Tier Heterogeneous Cellular Networks Based on Matérn Hard-Core Process

2019 ◽  
Vol 12 (1) ◽  
pp. 1
Author(s):  
Jie Yang ◽  
Ziyu Pan ◽  
Lihong Guo
Keyword(s):  
Energy Efficiency ◽  
Cellular Networks ◽  
Mutual Exclusion ◽  
Interference Management ◽  
Hard Core ◽  
Approximate Expression ◽  
Base Stations ◽  
Heterogeneous Cellular Networks ◽  
Coverage Analysis ◽  
Management Techniques

Due to the dense deployment of base stations (BSs) in heterogeneous cellular networks (HCNs), the energy efficiency (EE) of HCN has attracted the attention of academia and industry. Considering its mathematical tractability, the Poisson point process (PPP) has been employed to model HCNs and analyze their performance widely. The PPP falls short in modeling the effect of interference management techniques, which typically introduces some form of spatial mutual exclusion among BSs. In PPP, all the nodes are independent from each other. As such, PPP may not be suitable to model networks with interference management techniques, where there exists repulsion among the nodes. Considering this, we adopt the Matérn hard-core process (MHCP) instead of PPP, in which no two nodes can be closer than a repulsion radius from one another. In this paper, we study the coverage performance and EE of a two-tier HCN modelled by Matérn hard-core process (MHCP); we abbreviate this kind of two-tier HCN as MHCP-MHCP. We first derive the approximate expression of coverage probability of MHCP-MHCP by extending the approximate signal to interference ratio analysis based on the PPP (ASAPPP) method to multi-tier HCN. The concrete SIR gain of the MHCP model relative to the PPP model is derived through simulation and data fitting. On the basis of coverage analysis, we derive and formulate the EE of MHCP-MHCP network. Simulation results verify the correctness of our theoretical analysis and show the performance difference between the MHCP-MHCP and PPP modelled network.

scholarly journals 3D non-stationary unmanned aerial vehicles' MIMO channel model

2019 ◽  
Vol 13 (18) ◽  
pp. 2941-2945
Author(s):  
Haolin Jia ◽  
Hui Chen ◽  
Shiwen Wang ◽  
Yahong Zhang
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Channel Model ◽  
Mimo Channel ◽  
Aerial Vehicles

scholarly journals Renewable Energy-Enabled Cellular Networks

2021 ◽  
Author(s):  
Young-Chai Ko ◽  
Kug-Jin Jung ◽  
Ki Hong Park ◽  
Mohamed-Slim Alouini
Keyword(s):  
Renewable Energy ◽  
Cellular Networks ◽  
Energy Demand ◽  
Feasibility Studies ◽  
Power Grids ◽  
Base Stations ◽  
Future Research ◽  
Survey Paper ◽  
Aerial Platforms ◽  
Carbon Dioxide Co2

<div> <div> <div> <p>Renewable energy (RE)-powered base stations (BSs) have been considered as an attractive solution to address the exponential increasing energy demand in cellular networks while decreasing carbon dioxide (CO2) emissions. For the regions where reliable power grids are insufficient and infeasible to deploy, such as aerial platforms and harsh environments, RE has been an alternative power source for BSs. In this survey paper, we provide an overview of RE-enabled cellular networks, detailing their analysis, classification, and related works. First, we introduce the key components of RE-powered BSs along with their frequently adopted models. Second, we analyze the proposed strategies and design issues for RE-powered BSs that can be incorporated into cellular networks and categorize them into several groups to provide a good grasp. Third, we introduce feasibility studies on RE-powered BSs based on the recent literature. Fourth, we investigate RE-powered network components other than terrestrial BSs to address potential issues regarding RE-enabled networks. Finally, we suggest future research directions and conclusions. </p><p><br></p> </div> </div> </div>

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 Performance Analysis of UAV-Assisted Wireless Powered Sensor Network over Shadowed κ − μ Fading Channels

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Ivan Milovanovic ◽  
Caslav Stefanovic
Keyword(s):  
Sensor Network ◽  
Fading Channels ◽  
Time Allocation ◽  
Channel Model ◽  
Sensor Nodes ◽  
Special Cases ◽  
Channel Parameters ◽  
Shadowing Effect ◽  
Aerial Vehicle ◽  
The Impact

In this work, we analyze performances of the unmanned aerial vehicle- (UAV-) assisted wireless powered sensor communication, where sensor transmission ability is supported by the UAV. Harvested energy from the UAV-broadcasted signal is further used at the sensor nodes for uplink information transmission to the UAV, over assumed shadowed κ − μ fading channels. Here, we observe a general scenario in which due to the flight conditions of the UAV, the channel’s content include the LOS components affected by the shadowing effect, modeled by the general shadowed κ − μ channel model, which can be reduced to other well-known channel models as its special cases. We derive closed-form expressions for the outage probability (OP) of such wireless sensor network (WSN) operating in shadowed κ − μ fading environments. Further, we analyze the optimization of time allocation to minimize OP subjected to UAV’s energy constraints. The impact of channel parameters on observed performance measures is analyzed, and obtained results are numerically validated.

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