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Wireless Communications and Networking for Unmanned Aerial Vehicles [Hardback]

(Virginia Polytechnic Institute and State University), , (University of Oulu, Finland),
  • Formāts: Hardback, 530 pages, height x width x depth: 253x180x17 mm, weight: 720 g, Worked examples or Exercises
  • Izdošanas datums: 02-Apr-2020
  • Izdevniecība: Cambridge University Press
  • ISBN-10: 1108480748
  • ISBN-13: 9781108480741
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  • Cena: 144,45 €
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Wireless Communications and Networking for Unmanned Aerial VehiclesPalielināt
  • Formāts: Hardback, 530 pages, height x width x depth: 253x180x17 mm, weight: 720 g, Worked examples or Exercises
  • Izdošanas datums: 02-Apr-2020
  • Izdevniecība: Cambridge University Press
  • ISBN-10: 1108480748
  • ISBN-13: 9781108480741
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9781108480741.html
Keywords:
A thorough treatment of UAV wireless communications and networking research challenges and opportunities. Providing a holistic treatment of the fundamentals and applications of the subject, this is an essential tool for researchers, students, and engineers.

A thorough treatment of UAV wireless communications and networking research challenges and opportunities. Detailed, step-by-step development of carefully selected research problems that pertain to UAV network performance analysis and optimization, physical layer design, trajectory path planning, resource management, multiple access, cooperative communications, standardization, control, and security is provided. Featuring discussion of practical applications including drone delivery systems, public safety, IoT, virtual reality, and smart cities, this is an essential tool for researchers, students, and engineers interested in broadening their knowledge of the deployment and operation of communication systems that integrate or rely on unmanned aerial vehicles.

Recenzijas

'This book, written by the most prominent experts in the field, provides a complete in-depth analysis of UAV wireless communications. It should become a reference material for all the students, engineers and researchers who are building our next generation wireless communication networks.' Merouane Debbah, CentraleSupélec 'This is the most comprehensive book on the rapidly evolving field of wireless communications and networking for UAVs. The authors are among the researchers who have made the most profound contributions to this emerging field. Their impressive command on the subject matter results in a thorough presentation taking theory, practice, and industrial standards into account. A must-read for researchers and engineers working in this field.' Halim Yanikomeroglu, Carleton University, Ottawa

Papildus informācija

A thorough treatment of UAV wireless communications and networking research challenges and opportunities.
Acknowledgments xii
1 Wireless Communications and Networking with Unmanned Aerial Vehicles: An Introduction
1(11)
1.1 Brief Evolution of UAV Technology
1(1)
1.2 UAV Types and Regulations
2(3)
1.2.1 Classification of UAVs
3(1)
1.2.2 UAV Regulations
4(1)
1.3 Wireless Communications and Networking with UAVs
5(5)
1.3.1 UAVs as Flying Wireless Base Stations
6(2)
1.3.2 UAVs as Wireless Network User Equipment
8(1)
1.3.3 UAVs as Relays
9(1)
1.4 Summary and Book Overview
10(2)
2 UAV Applications and Use Cases
12(10)
2.1 UAVs for Public Safety Scenarios
12(1)
2.2 UAV-Assisted Ground Wireless Networks for Information Dissemination
13(1)
2.3 Three-Dimensional MIMO and Millimeter-Wave Communication with UAVs
14(2)
2.4 Drones in Internet of Things Systems
16(1)
2.5 UAVs for Virtual Reality Applications
16(2)
2.6 Drones in Wireless Backhauling for Ground Networks
18(1)
2.7 Cellular-Connected UAV UEs
19(1)
2.8 UAVs in a Smart City
20(1)
2.9
Chapter Summary
21(1)
3 Aerial Channel Modeling and Waveform Design
22(46)
3.1 Fundamentals of Radio Wave Propagation and Modeling
23(4)
3.2 Overview of Aerial Wireless Channel Characteristics
27(3)
3.3 Large-Scale Propagation Channel Effects
30(21)
3.3.1 Free-Space Path Loss
30(1)
3.3.2 Ray Tracing X
31(6)
3.3.3 Log-Distance Path Loss Models
37(3)
3.3.4 Empirical Path Loss Models
40(2)
3.3.5 Shadowing
42(2)
3.3.6 Line-of-Sight Probability
44(6)
3.3.7 Atmospheric and Weather Effects
50(1)
3.4 Small-Scale Propagation Effects
51(9)
3.4.1 Time Selectivity and Doppler Spread
52(2)
3.4.2 Frequency Selectivity and Delay Spread
54(2)
3.4.3 Spatial Selectivity and Angular Spread
56(2)
3.4.4 Envelope and Power Distributions
58(2)
3.5 Waveform Design
60(7)
3.5.1 Waveform Basics
60(2)
3.5.2 Orthogonal Frequency Division Multiplexing
62(2)
3.5.3 Direct Sequence Spread Spectrum
64(1)
3.5.4 Continuous Phase Modulation
65(2)
3.6
Chapter Summary
67(1)
4 Performance Analysis and Tradeoffs
68(22)
4.1 UAV Network Modeling: Challenges and Tools
68(2)
4.2 Downlink Performance Analysis for UAV BS
70(19)
4.2.1 System Model
70(3)
4.2.2 Network with a Static UAV
73(6)
4.2.3 Mobile UAV BS Scenario
79(4)
4.2.4 Representative Simulation Results
83(6)
4.3
Chapter Summary
89(1)
5 Deployment of UAVs for Wireless Communications
90(33)
5.1 Analytical Tools for UAV Deployment
91(3)
5.1.1 Centralized Optimization Theory
91(3)
5.2 Deployment of UAV BSs for Optimized Coverage
94(6)
5.2.1 Deployment Model
94(2)
5.2.2 Deployment Analysis
96(3)
5.2.3 Representative Simulation Results
99(1)
5.2.4 Summary
100(1)
5.3 Deployment of UAV BSs for Energy-Efficient Uplink Data Collection
100(12)
5.3.1 System Model and Problem Formulation
101(1)
5.3.2 Ground-to-Air Channel Model
102(1)
5.3.3 Activation Model of IoT devices
102(1)
5.3.4 UAV BS Placement and Device Association with Power Control
103(3)
5.3.5 Update Time Analysis
106(1)
5.3.6 Representative Simulation Results
107(4)
5.3.7 Summary
111(1)
5.4 Proactive Deployment with Caching
112(10)
5.4.1 Model
112(4)
5.4.2 Optimal Deployment and Content Caching for UAV BSs
116(2)
5.4.3 Representative Simulation Results
118(4)
5.4.4 Summary
122(1)
5.5
Chapter Summary
122(1)
6 Wireless-Aware Path Planning for UAV Networks
123(22)
6.1 Need for. Wireless-Aware Path Planning
123(1)
6.2 Wireless-Aware Path Planning for UAV UEs: Model and Problem Formulation
124(4)
6.2.1 Problem Formulation
126(2)
6.3 Self-Organizing Wireless-Aware Path Planning for UAV UEs
128(3)
6.3.1 Path Planning as a Game
128(2)
6.3.2 Equilibrium of the UAV UE Path Planning Game
130(1)
6.4 Deep Reinforcement Learning for Online Path Planning and Resource Management
131(5)
6.4.1 Deep ESN Architecture
131(2)
6.4.2 Deep ESN-Based UAV UE Update Rule
133(1)
6.4.3 Deep RL for Wireless-Aware Path Planning
134(2)
6.5 Representative Simulation Results
136(8)
6.6
Chapter Summary
144(1)
7 Resource Management for UAV Networks
145(36)
7.1 Cell Association in UAV-Assisted Wireless Networks under Hover Times Constraints
145(14)
7.1.1 System Model
146(3)
7.1.2 Optimal and Fair Cell Partitioning for Data Service Maximization under Hover Time Constraints
149(4)
7.1.3 Extensive Simulations and Numerical Results
153(5)
7.1.4 Summary
158(1)
7.2 Resource Planning and Cell Association for 3D Wireless Cellular Networks
159(10)
7.2.1 A Rigorous Model for 3D Cellular Networks
159(2)
7.2.2 3D Deployment of a Cellular Network with UAV BSs: A Truncated Octahedron Structure
161(3)
7.2.3 Latency-Minimal 3D Cell Association
164(2)
7.2.4 Representative Simulation Results
166(2)
7.2.5 Summary
168(1)
7.3 Managing Licensed and Unlicensed Spectrum Resources in Wireless Networks with UAVs
169(11)
7.3.1 Model of an LTE-U UAV BS Network
170(2)
7.3.2 Models for Data Rates and Queuing
172(2)
7.3.3 Resource Management Problem Formulation and Solution
174(2)
7.3.4 Representative Simulation Results
176(3)
7.3.5 Summary
179(1)
7.4
Chapter Summary
180(1)
8 Cooperative Communications in UAV Networks
181(26)
8.1 CoMP Transmission in Wireless Systems with Cellular-Connected UAV UEs
183(9)
8.1.1 A Model for CoMP in Networks with Aerial UAV UEs
183(1)
8.1.2 Probabilistic Caching Placement and Serving Distance Distributions
183(2)
8.1.3 Channel Model
185(1)
8.1.4 Analysis of Coverage Probability
186(3)
8.1.5 Representative Simulation Results
189(2)
8.1.6 Summary
191(1)
8.2 Reconfigurable Antenna Arrays of UAVs: UAV BS Scenario
192(13)
8.2.1 UAV-Based Antenna Array in the Sky: A Basic Model
193(2)
8.2.2 Transmission Time Minimization: Optimizing UAV Positions within the Array
195(4)
8.2.3 Control Time Minimization: Time-Optimal Control of UAVs
199(3)
8.2.4 Representative Simulation Results
202(2)
8.2.5 Summary
204(1)
8.3
Chapter Summary
205(2)
9 From LTE to 5G NR-Enabled UAV Networks
207(33)
9.1 Mobile Technologies-Enabled UAVs
208(2)
9.1.1 Connectivity Aspects
208(1)
9.1.2 Services beyond Connectivity
209(1)
9.2 Introduction to LTE
210(6)
9.2.1 Design Principles
211(1)
9.2.2 System Architecture
212(1)
9.2.3 Radio Interface Protocols
213(2)
9.2.4 Physical Layer Time-Frequency Structure
215(1)
9.3 UAV as LTE UE
216(10)
9.3.1 Coverage
216(1)
9.3.2 Interference
217(3)
9.3.3 Mobility Support
220(3)
9.3.4 Latency and Reliability
223(3)
9.4 UAV as LTE BS
226(1)
9.5 3GPP Standardization on Connected UAV
227(7)
9.5.1 3GPP Release-15 Study Item on LTE-Connected UAV
228(3)
9.5.2 3GPP Release-15 Work Item on LTE-Connected UAV
231(1)
9.5.3 3GPP Release-16 Study Item on Remote UAV Identification
232(2)
9.6 Towards 5G NR-Enabled UAVs
234(4)
9.6.1 A Primer on 5G NR
234(2)
9.6.2 Superior Connectivity Performance
236(1)
9.6.3 Service Differentiation with Network Slicing
237(1)
9.6.4 Network Intelligence
238(1)
9.7
Chapter Summary
238(2)
10 Security of UAV Networks
240(18)
10.1 Overview on UAV Security Problems
240(3)
10.2 Security of UAV UEs in Delivery Systems
243(14)
10.2.1 Modeling the Security of a UAV Delivery System
244(2)
10.2.2 UAV Security as a Network Interdiction Game
246(4)
10.2.3 Security of UAV Delivery Systems in Presence of Human Decision Makers
250(3)
10.2.4 Representative Simulation Results
253(3)
10.2.5 Summary
256(1)
10.3 Concluding Remarks on UAV Security
257(1)
References 258(21)
Index 279
Walid Saad is a Professor of Electrical and Computer Engineering at Virginia Tech and an IEEE Fellow. Mehdi Bennis is an Associate Professor at the University of Oulu, Finland. Mohammad Mozaffari is an Experienced Researcher at Ericsson Research Silicon Valley. Xingqin Lin is a Senior Researcher at Ericsson Research Silicon Valley.