Оглавление
Группа авторов. Autonomous Airborne Wireless Networks
Table of Contents
List of Tables
List of Illustrations
Guide
Pages
Autonomous Airborne Wireless Networks
Editor Biographies
List of Contributors
1 Introduction
2 Channel Model for Airborne Networks
2.1 Introduction
2.2 UAV Classification
2.3 UAV‐Enabled Wireless Communication
2.4 Channel Modeling in UAV Communications
2.4.1 Background
2.4.1.1 Path Loss and Large‐Scale Fading
2.4.1.2 Small‐Scale Fading
2.4.1.3 Airframe Shadowing
2.5 Key Research Challenges of UAV‐Enabled Wireless Network
2.5.1 Optimal Deployment of UAVs
2.5.2 UAV Trajectory Optimization
2.5.3 Energy Efficiency and Resource Management
2.6 Conclusion
Bibliography
3 Ultra‐wideband Channel Measurements and Modeling for Unmanned Aerial Vehicle‐to‐Wearables (UAV2W) Systems
3.1 Introduction
3.2 Measurement Settings
3.3 UWB‐UAV2W Radio Channel Characterization
3.3.1 Path Loss Analysis
3.3.2 Time Dispersion Analysis
3.3.3 Path Loss Analysis for Different Postures
3.3.4 Time Dispersion Analysis for Different Postures
3.4 Statistical Analysis
3.5 Conclusion
Bibliography
Notes
4 A Cooperative Multiagent Approach for Optimal Drone Deployment Using Reinforcement Learning
4.1 Introduction
4.2 System Model
4.2.1 Urban Model
4.2.2 Communications Model
4.3 Reinforcement Learning Solution
4.3.1 Fully Cooperative Markov Games
4.3.2 Decentralized Q‐Learning
4.3.3 Selection of Actions
4.3.4 Metrics
4.4 Representative Simulation Results. 4.4.1 Simulation Scenarios
4.4.2 Environment
4.4.3 User Distribution
4.4.4 Simulation
4.4.5 Numerical Results. 4.4.5.1 Single Frequency
4.4.5.2 Three Frequencies
4.4.5.3 Six Frequencies
4.5 Conclusions and Future Work. 4.5.1 Conclusions
4.5.2 Future Work
Acknowledgments
Bibliography
5 SWIPT‐PS Enabled Cache‐Aided Self‐Energized UAV for Cooperative Communication
5.1 Introduction
5.2 System Model
5.2.1 Air‐to‐Ground Channel Model
5.2.2 Signal Structure
5.2.3 Caching Mechanism at the UAV
5.3 Optimization Problem Formulation
5.3.1 Maximization of the Achievable Information Rate at the User
5.3.2 Trajectory Optimization with Fixed Time and Energy Scheduling
5.4 Numerical Simulation Results
5.5 Conclusion
Acknowledgments
Appendix 5.A. Proof of Optimal Solutions Obtained in (P1)
Bibliography
Notes
6 Performance of mmWave UAV‐Assisted 5G Hybrid Heterogeneous Networks
6.1 The Significance of UAV Deployment
6.2 Contribution
6.3 The Potential of mmWave and THz Communication
6.4 Challenges and Applications
6.4.1 Challenges
6.4.1.1 Complex Hardware Design
6.4.1.2 Imperfection in Channel State Information
6.4.1.3 High Mobility
6.4.1.4 Beam Misalignment
6.4.2 Applications
6.5 Fronthaul Connectivity using UAVs
6.5.1 Distribution of SCBs
6.5.2 Placement of UAVs
6.6 Communication Model
6.6.1 Communication Constraints and Objective
6.7 Association of SCBs with UAVs
6.8 Results and Discussions
6.8.1 Analysis of Results
6.9 Conclusion
Bibliography
Notes
7 UAV‐Enabled Cooperative Jamming for Physical Layer Security in Cognitive Radio Network
7.1 Introduction
7.2 System Model
7.2.1 Signal Model
7.2.2 Optimization Problem Formulation
7.3 Proposed Algorithm
7.3.1 Tractable Formulation for the Optimization Problem
7.3.1.1 Tractable Formulation for
7.3.1.2 Tractable Formulation for
7.3.1.3 Tractable Formulation for Constraint (7.10i)
7.3.1.4 Safe Optimization Problem
7.3.2 Proposed IA‐Based Algorithm
7.4 Numerical Results
7.5 Conclusion
Bibliography
8 IRS‐Assisted Localization for Airborne Mobile Networks
8.1 Introduction
8.1.1 Related Work. 8.1.2 Unmanned Aerial Vehicles
8.1.3 Intelligent Reflecting Surface
8.2 Intelligent Reflecting Surfaces in Airborne Networks
8.2.1 Aerial Networks with Integrated IRS
8.2.1.1 Integration of IRS in High‐Altitude Platform Stations (HAPSs) for Remote Areas Support
8.2.1.2 Integration of IRS in UAVs for Terrestrial Networks Support
8.2.1.3 Integration of IRS with Tethered Balloons for Terrestrial/Aerial Users Support
8.2.2 IRS‐Assisted Aerial Networks
8.3 Localization Using IRS
8.3.1 IRS Localization with Single Small Cell (SSC)
8.3.1.1 IRS Localization Using RSS with an SSC
8.4 Research Challenges
8.4.1 Challenges in UAV‐Based Airborne Mobile Networks
8.4.2 Challenges in IRS‐Based Localization
8.5 Summary and Conclusion
Bibliography
9 Performance Analysis of UAV‐Enabled Disaster Recovery Networks
9.1 Introduction
9.2 UAV Networks
9.2.1 UAV System's Architecture
9.2.1.1 Single UAV Systems
9.2.1.2 Multi‐UAV Systems
9.2.1.3 Cooperative Multi‐UAVs
9.2.1.4 Multilayer UAV Networks
9.3 Benefits of UAV Networks
9.4 Design Consideration of UAV Networks
9.5 New Technology and Infrastructure Trends
9.5.1 Network Function Virtualization (NFV)
9.5.2 Software‐Defined Networks (SDNs)
9.5.3 Cloud Computing
9.5.4 Image Processing
9.5.5 Millimeter Wave Communication
9.5.6 Artificial Intelligence
9.5.7 Machine Learning
9.5.8 Optimization and Game Theory
9.6 Research Trends
9.7 Future Insights
9.8 Conclusion
Bibliography
10 Network‐Assisted Unmanned Aerial Vehicle Communication for Smart Monitoring of Lockdown
10.1 Introduction
10.1.1 Relevant Literature
10.2 UAVs as Aerial Base Stations
10.2.1 Simulation Setting
10.2.2 Optimal Number of ABSs for Cellular Coverage in a Geographical Area
10.2.3 Performance Evaluation
10.2.3.1 Variation of Number of ABSs with ABS Altitude
10.2.3.2 Variation of Number of ABS with ABS Transmission Power
10.2.3.3 Variation of Number of ABSs with Geographical Area
10.3 UAV as Relays for Terrestrial Communication
10.3.1 5G Air Interface
10.3.2 Simulation Setup
10.4 Conclusion
Bibliography
Note
11 Unmanned Aerial Vehicles for Agriculture: an Overview of IoT‐Based Scenarios
11.1 Introduction
11.2 The Perspective of Research Projects
11.3 IoT Scenarios in Agriculture
11.3.1 Use of Data and Data Ownership
11.4 Wireless Communication Protocols
11.5 Multi‐access Edge Computing and 5G Networks
11.6 Conclusion
Bibliography
Notes
12 Airborne Systems and Underwater Monitoring
12.1 Introduction
12.2 Automated Image Labeling
12.2.1 Point Selection
12.2.2 Measurement System
12.2.3 Region Labeling
12.2.4 Testing
12.2.4.1 Measurement System Testing
12.2.4.2 Point Selection Simulations
12.2.4.3 Field Experiments
12.3 Water/Land Visual Differentiation
12.3.1 Classifier Training
12.3.2 Online Algorithm
12.3.3 Mapping
12.3.4 Transmit
12.3.5 Field Experiments
12.3.5.1 Calibration
12.3.5.2 Simulation
12.3.5.3 Overall
12.4 Offline Bathymetric Mapping
12.4.1 Algorithm Overview
12.4.2 Algorithm Simulation
12.4.3 Algorithm Implementation
12.4.4 Bathymetric Measurement System
12.5 Online Bathymetric Mapping
12.5.1 Point Selection Algorithms
12.5.1.1 Monotone Chain Hull Algorithm
12.5.1.2 Incremental Hull Algorithm
12.5.1.3 Quick Hull Algorithm
12.5.1.4 Gift Wrap Algorithm
12.5.1.5 Slope‐Based Algorithm
12.5.1.6 Combination (Slope‐Based and Probability) Algorithm
12.5.2 Simulation Setup
12.5.3 Results and Analysis
12.5.3.1 Spline
12.5.3.2 IDW
12.5.3.3 Overall Summary
12.6 Conclusion and Future Work
Bibliography
13 Demystifying Futuristic Satellite Networks: Requirements, Security Threats, and Issues
13.1 Introduction
13.2 Inter‐Satellite and Deep Space Network
13.2.1 Tier‐1 of Satellite Networks
13.2.2 Tier‐2 of Satellite Networks
13.2.3 Tier‐3 of Satellite Networks
13.3 Security Requirements and Challenges in ISDSN
13.3.1 Security Challenges
13.3.1.1 Key Management
13.3.1.2 Secure Routing
13.3.2 Security Threats
13.3.2.1 Denial of Service Attack
13.3.2.2 Data Tampering
13.4 Conclusion
Bibliography
Notes
14 Conclusion
14.1 Future Hot Topics. 14.1.1 Terahertz Communications
14.1.2 3D MIMO for Airborne Networks
14.1.3 Cache‐Enabled Airborne Networks
14.1.4 Blockchain‐Enabled Airborne Wireless Networks
14.2 Concluding Remarks
Index
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