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E-raamat: Autonomous Airborne Wireless Networks

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  • Formaat: EPUB+DRM
  • Sari: IEEE Press
  • Ilmumisaeg: 29-Jul-2021
  • Kirjastus: Wiley-IEEE Press
  • Keel: eng
  • ISBN-13: 9781119751700
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Autonomous Airborne Wireless NetworksSuurem pilt
  • Formaat: EPUB+DRM
  • Sari: IEEE Press
  • Ilmumisaeg: 29-Jul-2021
  • Kirjastus: Wiley-IEEE Press
  • Keel: eng
  • ISBN-13: 9781119751700
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Discover what lies beyond the bleeding-edge of autonomous airborne networks with this authoritative new resource 

Autonomous Airborne Wireless Networks delivers an insightful exploration of recent advances in the theory and practice of using airborne wireless networks to provide emergency communications, coverage and capacity expansion, information dissemination, and more. The distinguished engineers and editors have selected resources that cover the fundamentals of airborne networks, including channel models, recent regulation developments, self-organized networking, AI-enabled flying networks, and notable applications in a variety of industries.  

The book evaluates advances in the cutting-edge of unmanned aerial vehicle wireless network technology while offering readers new ideas on how airborne wireless networks can support various applications expected of future networks. The rapidly developing field is examined from a fresh perspective, one not just concerned with ideas of control, trajectory optimization, and navigation.  

Autonomous Airborne Wireless Networks considers several potential use cases for the technology and demonstrates how it can be integrated with concepts from self-organized network technology and artificial intelligence to deliver results in those cases. Readers will also enjoy: 

  • A thorough discussion of distributed drone base station positioning for emergency cellular networks using reinforcement learning (AI-enabled trajectory optimization) 
  • An exploration of unmanned aerial vehicle-to-wearables (UAV2W) indoor radio propagation channel measurements and modelling 
  • An up-to-date treatment of energy minimization in UAV trajectory design for delay tolerant emergency communication 
  • Examinations of cache-enabled UAVs, 3D MIMO for airborne networks, and airborne networks for Internet of Things communications  

Perfect for telecom engineers and industry professionals working on identifying practical and efficient concepts tailored to overcome challenges facing unmanned aerial vehicles providing wireless communications, Autonomous Airborne Wireless Networks also has a place on the bookshelves of stakeholders, regulators, and research agencies working on the latest developments in UAV communications. 

Editor Biographies xiii
List of Contributors xv
1 Introduction 1(6)
Muhammad A. Imran
Oluwakayode Onireti
Shuja S. Ansari
Qammer H. Abbasi
2 Channel Model for Airborne Networks 7(20)
Aziz A. Khuwaja
Yunfei Chen
2.1 Introduction
7(1)
2.2 UAV Classification
8(2)
2.3 UAV-Enabled Wireless Communication
10(1)
2.4 Channel Modeling in UAV Communications
11(8)
2.4.1 Background
12(7)
2.4.1.1 Path Loss and Large-Scale Fading
13(4)
2.4.1.2 Small-Scale Fading
17(1)
2.4.1.3 Airframe Shadowing
18(1)
2.5 Key Research Challenges of UAV-Enabled Wireless Network
19(1)
2.5.1 Optimal Deployment of UAVs
19(1)
2.5.2 UAV Trajectory Optimization
19(1)
2.5.3 Energy Efficiency and Resource Management
20(1)
2.6 Conclusion
20(1)
Bibliography
21(6)
3 Ultra-wideband Channel Measurements and Modeling for Unmanned Aerial Vehicle-to-Wearables (UAV2W) Systems 27(20)
Amit Kachroo
Surbhi Vishwakarma
Jacob N. Dixon
Hisham Abuella
Adithya Popuri
Qammer H. Abbasi
Charles F. Bunting
Jamey D. Jacob
Sabit Ekin
3.1 Introduction
27(1)
3.2 Measurement Settings
28(5)
3.3 UWB-UAV2W Radio Channel Characterization
33(9)
3.3.1 Path Loss Analysis
33(1)
3.3.2 Time Dispersion Analysis
34(4)
3.3.3 Path Loss Analysis for Different Postures
38(1)
3.3.4 Time Dispersion Analysis for Different Postures
38(4)
3.4 Statistical Analysis
42(2)
3.5 Conclusion
44(1)
Bibliography
44(3)
4 A Cooperative Multiagent Approach for Optimal Drone Deployment Using Reinforcement Learning 47(26)
Rigoberto Acosta-Gonzalez
Paulo V. Klaine
Samuel Montejo-Sanchez
Richard D. Souza
Lei Zhang
Muhammad A. Imran
4.1 Introduction
48(3)
4.2 System Model
51(3)
4.2.1 Urban Model
51(1)
4.2.2 Communications Model
51(3)
4.3 Reinforcement Learning Solution
54(8)
4.3.1 Fully Cooperative Markov Games
54(3)
4.3.2 Decentralized Q-Learning
57(1)
4.3.3 Selection of Actions
58(3)
4.3.4 Metrics
61(1)
4.4 Representative Simulation Results
62(6)
4.4.1 Simulation Scenarios
62(1)
4.4.2 Environment
62(1)
4.4.3 User Distribution
62(1)
4.4.4 Simulation
63(1)
4.4.5 Numerical Results
64(4)
4.4.5.1 Single Frequency
64(1)
4.4.5.2 Three Frequencies
65(1)
4.4.5.3 Six Frequencies
66(2)
4.5 Conclusions and Future Work
68(1)
4.5.1 Conclusions
68(1)
4.5.2 Future Work
69(1)
Acknowledgments
69(1)
Bibliography
69(4)
5 SWIPT-PS Enabled Cache-Aided Self-Energized UAV for Cooperative Communication 73(24)
Tharindu D. Ponnimbaduge Perera
Dushantha Nalin K. Jayakody
5.1 Introduction
73(4)
5.2 System Model
77(5)
5.2.1 Air-to-Ground Channel Model
80(1)
5.2.2 Signal Structure
81(1)
5.2.3 Caching Mechanism at the UAV
82(1)
5.3 Optimization Problem Formulation
82(4)
5.3.1 Maximization of the Achievable Information Rate at the User
82(2)
5.3.2 Trajectory Optimization with Fixed Time and Energy Scheduling
84(2)
5.4 Numerical Simulation Results
86(6)
5.5 Conclusion
92(1)
Acknowledgments
92(1)
5.A Proof of Optimal Solutions Obtained in (P1)
93(1)
Bibliography
94(3)
6 Performance of mmWave UAV-Assisted 5G Hybrid Heterogeneous Networks 97(22)
Muhammad K. Shehzad
Muhammad W. Akhtar
Syed A. Hassan
6.1 The Significance of UAV Deployment
97(1)
6.2 Contribution
98(1)
6.3 The Potential of mmWave and THz Communication
98(2)
6.4 Challenges and Applications
100(3)
6.4.1 Challenges
101(1)
6.4.1.1 Complex Hardware Design
101(1)
6.4.1.2 Imperfection in Channel State Information
101(1)
6.4.1.3 High Mobility
101(1)
6.4.1.4 Beam Misalignment
101(1)
6.4.2 Applications
102(1)
6.5 Fronthaul Connectivity using UAVs
103(2)
6.5.1 Distribution of SCBs
104(1)
6.5.2 Placement of UAVs
104(1)
6.6 Communication Model
105(3)
6.6.1 Communication Constraints and Objective
107(1)
6.7 Association of SCBs with UAVs
108(2)
6.8 Results and Discussions
110(4)
6.8.1 Analysis of Results
110(4)
6.9 Conclusion
114(1)
Bibliography
115(4)
7 UAV-Enabled Cooperative Jamming for Physical Layer Security in Cognitive Radio Network 119(22)
Phu X. Nguyen
Hieu V Nguyen
Van-Dinh Nguyen
Oh-Soon Shin
7.1 Introduction
119(2)
7.2 System Model
121(4)
7.2.1 Signal Model
121(4)
7.2.2 Optimization Problem Formulation
125(1)
7.3 Proposed Algorithm
125(8)
7.3.1 Tractable Formulation for the Optimization Problem P2
126(2)
7.3.1.1 Tractable Formulation for Rs[ n]
126(1)
7.3.1.2 Tractable Formulation for Rg[ n]
127(1)
7.3.1.3 Tractable Formulation for Constraint (7.10i)
127(1)
7.3.1.4 Safe Optimization Problem
128(1)
7.3.2 Proposed IA-Based Algorithm
128(5)
7.4 Numerical Results
133(3)
7.5 Conclusion
136(2)
Bibliography
138(3)
8 IRS-Assisted Localization for Airborne Mobile Networks 141(16)
Olaoluwa Popoola
Shuja Ansari
Rafay I. Ansari
Lina Mohjazi
Syed A. Hassan
Nauman Aslam
Qammer H. Abbasi
Muhammad A. Imran
8.1 Introduction
141(3)
8.1.1 Related Work
143(1)
8.1.2 Unmanned Aerial Vehicles
143(1)
8.1.3 Intelligent Reflecting Surface
143(1)
8.2 Intelligent Reflecting Surfaces in Airborne Networks
144(5)
8.2.1 Aerial Networks with Integrated IRS
145(2)
8.2.1.1 Integration of IRS in High-Altitude Platform Stations (HAPSs) for Remote Areas Support
145(1)
8.2.1.2 Integration of IRS in UAVs for Terrestrial Networks Support
146(1)
8.2.1.3 Integration of IRS with Tethered Balloons for Terrestrial/Aerial Users Support
147(1)
8.2.2 IRS-Assisted Aerial Networks
147(2)
8.3 Localization Using IRS
149(3)
8.3.1 IRS Localization with Single Small Cell (SSC)
150(2)
8.3.1.1 IRS Localization Using RSS with an SSC
150(2)
8.4 Research Challenges
152(1)
8.4.1 Challenges in UAV-Based Airborne Mobile Networks
152(1)
8.4.2 Challenges in IRS-Based Localization
153(1)
8.5 Summary and Conclusion
153(1)
Bibliography
154(3)
9 Performance Analysis of UAV-Enabled Disaster Recovery Networks 157(38)
Rabeea Basir
Saad Qaisar
Mudassar Ali
Naveed Ahmad Chughtai
Muhammad Ali Imran
Anas Hashmi
9.1 Introduction
157(1)
9.2 UAV Networks
158(5)
9.2.1 UAV System's Architecture
159(1)
9.2.1.1 Single UAV Systems
160(11)
9.2.1.2 Multi-UAV Systems
161(1)
9.2.1.3 Cooperative Multi-UAVs
161(1)
9.2.1.4 Multilayer UAV Networks
162(1)
9.3 Benefits of UAV Networks
163(3)
9.4 Design Consideration of UAV Networks
166(5)
9.5 New Technology and Infrastructure Trends
171(13)
9.5.1 Network Function Virtualization (NFV)
179(1)
9.5.2 Software-Defined Networks (SDNs)
179(1)
9.5.3 Cloud Computing
180(1)
9.5.4 Image Processing
180(1)
9.5.5 Millimeter Wave Communication
181(1)
9.5.6 Artificial Intelligence
182(1)
9.5.7 Machine Learning
183(1)
9.5.8 Optimization and Game Theory
184(1)
9.6 Research Trends
184(3)
9.7 Future Insights
187(1)
9.8 Conclusion
188(1)
Bibliography
188(7)
10 Network-Assisted Unmanned Aerial Vehicle Communication for Smart Monitoring of Lockdown 195(22)
Navuday Sharma
Muhammad Awais
Haris Peryaiz
Hassan Malik
Qiang Ni
10.1 Introduction
195(4)
10.1.1 Relevant Literature
198(1)
10.2 UAVs as Aerial Base Stations
199(8)
10.2.1 Simulation Setting
200(1)
10.2.2 Optimal Number of ABSs for Cellular Coverage in a Geographical Area
201(1)
10.2.3 Performance Evaluation
202(5)
10.2.3.1 Variation of Number of ABSs with ABS Altitude
202(2)
10.2.3.2 Variation of Number of ABS with ABS Transmission Power
204(1)
10.2.3.3 Variation of Number of ABSs with Geographical Area
205(2)
10.3 UAV as Relays for Terrestrial Communication
207(5)
10.3.1 5G Air Interface
209(1)
10.3.2 Simulation Setup
210(2)
10.4 Conclusion
212(1)
Bibliography
213(4)
11 Unmanned Aerial Vehicles for Agriculture: an Overview of IoT-Based Scenarios 217(20)
Bacco Manlio
Barsocchi Paolo
Gotta Alberto
Ruggeri Massimiliano
11.1 Introduction
217(1)
11.2 The Perspective of Research Projects
218(3)
11.3 IoT Scenarios in Agriculture
221(3)
11.3.1 Use of Data and Data Ownership
224(1)
11.4 Wireless Communication Protocols
224(3)
11.5 Multi-access Edge Computing and 5G Networks
227(3)
11.6 Conclusion
230(1)
Bibliography
231(6)
12 Airborne Systems and Underwater Monitoring 237(24)
Elizabeth Basha
Jason To-Tran
Davis Young
Sean Thalken
Christopher Uramoto
12.1 Introduction
237(2)
12.2 Automated Image Labeling
239(6)
12.2.1 Point Selection
239(1)
12.2.2 Measurement System
239(1)
12.2.3 Region Labeling
240(2)
12.2.4 Testing
242(3)
12.2.4.1 Measurement System Testing
242(1)
12.2.4.2 Point Selection Simulations
243(1)
12.2.4.3 Field Experiments
244(1)
12.3 Water/Land Visual Differentiation
245(4)
12.3.1 Classifier Training
245(1)
12.3.2 Online Algorithm
246(1)
12.3.3 Mapping
246(1)
12.3.4 Transmit
247(1)
12.3.5 Field Experiments
248(1)
12.3.5.1 Calibration
248(1)
12.3.5.2 Simulation
249(1)
12.3.5.3 Overall
249(1)
12.4 Offline Bathymetric Mapping
249(4)
12.4.1 Algorithm Overview
250(1)
12.4.2 Algorithm Simulation
250(1)
12.4.3 Algorithm Implementation
251(1)
12.4.4 Bathymetric Measurement System
252(1)
12.5 Online Bathymetric Mapping
253(5)
12.5.1 Point Selection Algorithms
254(2)
12.5.1.1 Monotone Chain Hull Algorithm
254(1)
12.5.1.2 Incremental Hull Algorithm
254(1)
12.5.1.3 Quick Hull Algorithm
254(1)
12.5.1.4 Gift Wrap Algorithm
255(1)
12.5.1.5 Slope-Based Algorithm
255(1)
12.5.1.6 Combination (Slope-Based and Probability) Algorithm
255(1)
12.5.2 Simulation Setup
256(1)
12.5.3 Results and Analysis
256(6)
12.5.3.1 Spline
256(1)
12.5.3.2 IDW
257(1)
12.5.3.3 Overall Summary
258(1)
12.6 Conclusion and Future Work
258(1)
Bibliography
258(3)
13 Demystifying Futuristic Satellite Networks: Requirements, Security Threats, and Issues 261(14)
Muhammad Usman
Muhammad R. Asghar
Imran S. Ansari
Marwa Qaraqe
13.1 Introduction
261(1)
13.2 Inter-Satellite and Deep Space Network
262(4)
13.2.1 Tier-1 of Satellite Networks
263(1)
13.2.2 Tier-2 of Satellite Networks
264(1)
13.2.3 Tier-3 of Satellite Networks
265(1)
13.3 Security Requirements and Challenges in ISDSN
266(4)
13.3.1 Security Challenges
267(2)
13.3.1.1 Key Management
267(1)
13.3.1.2 Secure Routing
268(1)
13.3.2 Security Threats
269(1)
13.3.2.1 Denial of Service Attack
269(1)
13.3.2.2 Data Tampering
269(1)
13.4 Conclusion
270(1)
Bibliography
270(5)
14 Conclusion 275(4)
14.1 Future Hot Topics
275(2)
14.1.1 Terahertz Communications
275(1)
14.1.2 3D MIMO for Airborne Networks
276(1)
14.1.3 Cache-Enabled Airborne Networks
276(1)
14.1.4 Blockchain-Enabled Airborne Wireless Networks
276(1)
14.2 Concluding Remarks
277(2)
Index 279
Muhammad Ali Imran, is Dean University of Glasgow, UESTC, Professor of Communication Systems and Head of Communications Sensing and Imaging Group at the James Watt School of Engineering, University of Glasgow, UK.

Oluwakayode Onireti, PhD, is a Lecturer at the James Watt School of Engineering, University of Glasgow, UK. He received his PhD in Electronics Engineering from the University of Surrey in Guildford, UK.

Shuja Ansari, PhD, is currently a Research Associate at University of Glasgow and actively involved as a Use Case implementation lead for Wave-1 Urban Innovation Projects for Scotland 5G Centre. He received his PhD in Engineering from Glasgow Caledonian University, UK.

Qammer H. Abbasi, is Senior Lecturer (Associate Professor) and Deputy Head of Communications Sensing and Imaging Group at the James Watt School of Engineering the University of Glasgow, UK.
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