UAV Communications for 5G and Beyond
Wiley - IEEE
1. Auflage Dezember 2020
464 Seiten, Hardcover
Wiley & Sons Ltd
ISBN:
978-1-119-57569-6
John Wiley & Sons
Weitere Versionen
Explore foundational and advanced issues in UAV cellular communications with this cutting-edge and timely new resource
UAV Communications for 5G and Beyond delivers a comprehensive overview of the potential applications, networking architectures, research findings, enabling technologies, experimental measurement results, and industry standardizations for UAV communications in cellular systems. The book covers both existing LTE infrastructure, as well as future 5G-and-beyond systems.
UAV Communications covers a range of topics that will be of interest to students and professionals alike. Issues of UAV detection and identification are discussed, as is the positioning of autonomous aerial vehicles. More fundamental subjects, like the necessary tradeoffs involved in UAV communication are examined in detail.
The distinguished editors offer readers an opportunity to improve their ability to plan and design for the near-future, explosive growth in the number of UAVs, as well as the correspondingly demanding systems that come with them. Readers will learn about a wide variety of timely and practical UAV topics, like:
* Performance measurement for aerial vehicles over cellular networks, particularly with respect to existing LTE performance
* Inter-cell interference coordination with drones
* Massive multiple-input and multiple-output (MIMO) for Cellular UAV communications, including beamforming, null-steering, and the performance of forward-link C&C channels
* 3GPP standardization for cellular-supported UAVs, including UAV traffic requirements, channel modeling, and interference challenges
* Trajectory optimization for UAV communications
Perfect for professional engineers and researchers working in the field of unmanned aerial vehicles, UAV Communications for 5G and Beyond also belongs on the bookshelves of students in masters and PhD programs studying the integration of UAVs into cellular communication systems.
List of Contributors xvii
Acronyms xxi
Part I Fundamentals of UAV Communications 1
1 Overview 3
Qingqing Wu, Yong Zeng, and Rui Zhang
1.1 UAV Definitions, Classes, and Global Trend 3
1.2 UAV Communication and Spectrum Requirement 4
1.3 Potential Existing Technologies for UAV Communications 6
1.3.1 Direct Link 6
1.3.2 Satellite 7
1.3.3 Ad-Hoc Network 8
1.3.4 Cellular Network 8
1.4 Two Paradigms in Cellular UAV Communications 9
1.4.1 Cellular-Connected UAVs 9
1.4.2 UAV-Assisted Wireless Communications 10
1.5 New Opportunities and Challenges 11
1.5.1 High Altitude 11
1.5.2 High LoS Probability 12
1.5.3 High 3D Mobility 12
1.5.4 SWAP Constraints 13
1.6 Chapter Summary and Main Organization of the Book 13
References 15
2 A Survey of Air-to-Ground Propagation Channel Modeling for Unmanned Aerial Vehicles 17
Wahab Khawaja, Ismail Guvenc, David W. Matolak, Uwe-Carsten Fiebig, and Nicolas Schneckenberger
2.1 Introduction 17
2.2 Literature Review 20
2.2.1 Literature Review on Aerial Propagation 20
2.2.2 Existing Surveys on UAV AG Propagation 21
2.3 UAV AG Propagation Characteristics 22
2.3.1 Comparison of UAV AG and Terrestrial Propagation 22
2.3.2 Frequency Bands for UAV AG Propagation 23
2.3.3 Scattering Characteristics for AG Propagation 24
2.3.4 Antenna Configurations for AG Propagation 24
2.3.5 Doppler Effects 25
2.4 AG Channel Measurements: Configurations, Challenges, Scenarios, and Waveforms 25
2.4.1 Channel Measurement Configurations 26
2.4.2 Challenges in AG Channel Measurements 29
2.4.3 AG Propagation Scenarios 29
2.4.3.1 Open Space 31
2.4.3.2 Hilly/Mountainous 31
2.4.3.3 Forest 32
2.4.3.4 Water/Sea 32
2.4.4 Elevation Angle Effects 32
2.5 UAV AG Propagation Measurement and Simulation Results in the Literature 33
2.5.1 Path Loss/Shadowing 33
2.5.2 Delay Dispersion 36
2.5.3 Narrowband Fading and Ricean K-factor 36
2.5.4 Doppler Spread 37
2.5.5 Effects of UAV AG Measurement Environment 37
2.5.5.1 Urban/Suburban 38
2.5.5.2 Rural/Open Field 38
2.5.5.3 Mountains/Hilly, Over Sea, Forest 39
2.5.6 Simulations for Channel Characterization 40
2.6 UAV AG Propagation Models 41
2.6.1 AG Propagation Channel Model Types 41
2.6.2 Path-Loss and Large-Scale Fading Models 42
2.6.2.1 Free-Space Path-Loss Model 43
2.6.2.2 Floating-Intercept Path-Loss Model 43
2.6.2.3 Dual-Slope Path-Loss Model 43
2.6.2.4 Log-Distance Path-Loss Model 45
2.6.2.5 Modified FSPL Model 45
2.6.2.6 Two-Ray PL Model 45
2.6.2.7 Log-Distance FI Model 45
2.6.2.8 LOS/NLOS Mixture Path-Loss Model 46
2.6.3 Airframe Shadowing 47
2.6.4 Small-Scale Fading Models 47
2.6.5 Intermittent MPCs 48
2.6.6 Effect of Frequency Bands on Channel Models 51
2.6.7 MIMO AG Propagation Channel Models 52
2.6.8 Comparison of Different AG Channel Models 54
2.6.8.1 Large-Scale Fading Models 54
2.6.8.2 Small-Scale Fading Models 54
2.6.9 Comparison of Traditional Channel Models with UAV AG Propagation Channel Models 55
2.6.10 Ray Tracing Simulations 56
2.6.11 3GPP Channel Models for UAVs 58
2.7 Conclusions 60
References 60
3 UAV Detection and Identification 71
Martins Ezuma, Fatih Erden, Chethan Kumar Anjinappa, Ozgur Ozdemir, Ismail Guvenc, and David Matolak
3.1 Introduction 71
3.2 RF-Based UAV Detection Techniques 75
3.2.1 RF Fingerprinting Technique 76
3.2.2 WiFi Fingerprinting Technique 76
3.3 Multistage UAV RF Signal Detection 77
3.3.1 Preprocessing Step: Multiresolution Analysis 78
3.3.2 The Naive Bayesian Decision Mechanism for RF Signal Detection 82
3.3.3 Detection of WiFi and Bluetooth Interference 84
3.4 UAV Classification Using RF Fingerprints 89
3.4.1 Feature Selection Using Neighborhood Components Analysis (NCA) 91
3.5 Experimental Results 92
3.5.1 Experimental Setup 92
3.5.2 Detection Results 94
3.5.3 UAV Classification Results 95
3.6 Conclusion 100
Acknowledgments 100
References 100
Part II Cellular-Connected UAV Communications 103
4 Performance Analysis for Cellular-Connected UAVs 105
M. Mahdi Azari, Fernando Rosas, and Sofie Pollin
4.1 Introduction 105
4.1.1 Motivation 105
4.1.2 Related Works 107
4.1.3 Contributions and Chapter Structure 108
4.2 Modelling Preliminaries 109
4.2.1 Stochastic Geometry 109
4.2.2 Network Architecture 110
4.2.3 Channel Model 111
4.2.4 Blockage Modeling and LoS Probability 112
4.2.5 User Association Strategy and Link SINR 112
4.3 Performance Analysis 112
4.3.1 Exact Coverage Probability 113
4.3.2 Approximations for UAV Coverage Probability 115
4.3.2.1 Discarding NLoS and Noise Effects 116
4.3.2.2 Moment Matching 116
4.3.3 Achievable Throughput and Area Spectral Efficiency Analysis 118
4.4 System Design: Study Cases and Discussion 119
4.4.1 Analysis of Accuracy 119
4.4.2 Design Parameters 120
4.4.2.1 Impact of UAV Altitude 120
4.4.2.2 Impact of UAV Antenna Beamwidth 121
4.4.2.3 Impact of UAV Antenna Tilt 123
4.4.2.4 Impact of Different Types of Environment 123
4.4.3 Heterogeneous Networks - Tier Selection 125
4.4.4 Network Densification 127
4.5 Conclusion 129
References 136
5 Performance Enhancements for LTE-Connected UAVs: Experiments and Simulations 139
Rafhael Medeiros de Amorim, Jeroen Wigard, István Z. Kovács, and Troels B. Sørensen
5.1 Introduction 139
5.2 LTE Live Network Measurements 140
5.2.1 Downlink Experiments 141
5.2.2 Path-Loss Model Characterization 145
5.2.3 Uplink Experiments 145
5.3 Performance in LTE Networks 149
5.4 Reliability Enhancements 150
5.4.1 Interference Cancellation 151
5.4.2 Inter-Cell Interference Control 152
5.4.3 CoMP 152
5.4.4 Antenna Beam Selection 153
5.4.5 Dual LTE Access 155
5.4.6 Dedicated Spectrum 158
5.4.7 Discussion 158
5.5 Summary and Outlook 159
References 160
6 3GPP Standardization for Cellular-Supported UAVs 163
Helka-Liina Määttänen
6.1 Short Introduction to LTE and NR 163
6.1.1 LTE Physical Layer and MIMO 165
6.1.2 NR Physical Layer and MIMO 166
6.2 Drones Served by Mobile Networks 167
6.2.1 Interference Detection and Mitigation 168
6.2.2 Mobility for Drones 170
6.2.3 Need for Drone Identification and Authorization 171
6.3 3GPP Standardization Support for UAVs 172
6.3.1 Measurement Reporting Based on RSRP Level of Multiple Cells 172
6.3.2 Height, Speed, and Location Reporting 174
6.3.3 Uplink Power Control Enhancement 175
6.3.4 Flight Path Signalling 175
6.3.5 Drone Authorization and Identification 176
6.4 Flying Mode Detection in Cellular Networks 177
References 179
7 Enhanced Cellular Support for UAVs with Massive MIMO 181
Giovanni Geraci, Adrian Garcia-Rodriguez, Lorenzo Galati Giordano, and David López-Pérez
7.1 Introduction 181
7.2 System Model 181
7.2.1 Cellular Network Topology 183
7.2.2 System Model 184
7.2.3 Massive MIMO Channel Estimation 186
7.2.4 Massive MIMO Spatial Multiplexing 186
7.3 Single-User Downlink Performance 187
7.3.1 UAV Downlink C&C Channel 187
7.4 Massive MIMO Downlink Performance 190
7.4.1 UAV Downlink C&C Channel 190
7.4.2 UAV-GUE Downlink Interplay 192
7.5 Enhanced Downlink Performance 194
7.5.1 UAV Downlink C&C Channel 195
7.5.2 UAV-GUE Downlink Interplay 196
7.6 Uplink Performance 197
7.6.1 UAV Uplink C&C Channel and Data Streaming 197
7.6.2 UAV-GUE Uplink Interplay 198
7.7 Conclusions 199
References 200
8 High-Capacity Millimeter Wave UAV Communications 203
Nuria González-Prelcic, Robert W. Heath, Cristian Rusu, and Aldebaro Klautau
8.1 Motivation 203
8.2 UAV Roles and Use Cases Enabled by Millimeter Wave Communication 206
8.2.1 UAV Roles in Cellular Networks 206
8.2.2 UAV Use Cases Enabled by High-Capacity Cellular Networks 207
8.3 Aerial Channel Models at Millimeter Wave Frequencies 208
8.3.1 Propagation Considerations for Aerial Channels 208
8.3.1.1 Atmospheric Considerations 208
8.3.1.2 Blockages 210
8.3.2 Air-to-Air Millimeter Wave Channel Model 211
8.3.3 Air-to-Ground Millimeter Wave Channel Model 212
8.3.4 Ray Tracing as a Tool to Obtain Channel Measurements 214
8.4 Key Aspects of UAV MIMO Communication at mmWave Frequencies 215
8.5 Establishing Aerial mmWave MIMO Links 219
8.5.1 Beam Training and Tracking for UAV Millimeter Wave Communication 219
8.5.2 Channel Estimation and Tracking in Aerial Environments 219
8.5.3 Design of Hybrid Precoders and Combiners 221
8.6 Research Opportunities 222
8.6.1 Sensing at the Tower 222
8.6.2 Joint Communication and Radar 222
8.6.3 Positioning and Mapping 223
8.7 Conclusions 223
References 223
Part III UAV-Assisted Wireless Communications 231
9 Stochastic Geometry-Based Performance Analysis of Drone Cellular Networks 233
Morteza Banagar, Vishnu V. Chetlur, and Harpreet S. Dhillon
9.1 Introduction 233
9.2 Overview of the System Model 235
9.2.1 Spatial Model 235
9.2.2 3GPP-Inspired Mobility Model 236
9.2.3 Channel Model 237
9.2.4 Metrics of Interest 237
9.3 Average Rate 238
9.4 Handover Probability 242
9.5 Results and Discussion 246
9.5.1 Density of Interfering DBSs 247
9.5.2 Average Rate 247
9.5.3 Handover Probability 249
9.6 Conclusion 250
Acknowledgment 251
References 251
10 UAV Placement and Aerial-Ground Interference Coordination 255
Abhaykumar Kumbhar and Ismail Guvenc
10.1 Introduction 255
10.2 Literature Review 256
10.3 UABS Use Case for AG-HetNets 259
10.4 UABS Placement in AG-HetNet 260
10.5 AG-HetNet Design Guidelines 264
10.5.1 Path-Loss Model 265
10.5.1.1 Log-Distance Path-Loss Model 265
10.5.1.2 Okumura-Hata Path-Loss Model 266
10.6 Inter-Cell Interference Coordination 266
10.6.1 UE Association and Scheduling 269
10.7 Simulation Results 270
10.7.1 5pSE with UABSs Deployed on Hexagonal Grid 270
10.7.1.1 5pSE with Log-Normal Path-Loss Model 270
10.7.1.2 5pSE with Okumura-Hata Path-Loss Model 271
10.7.2 5pSE with GA-Based UABS Deployment Optimization 273
10.7.2.1 5pSE with Log-Normal Path-Loss Model 273
10.7.2.2 5pSE with Okumura-Hata Path-Loss model 275
10.7.3 Performance Comparison Between Fixed (Hexagonal) and Optimized UABS Deployment with eICIC and FeICIC 276
10.7.3.1 Influence of LDPLM on 5pSE 277
10.7.3.2 Influence of OHPLM on 5pSE 277
10.7.4 Comparison of Computation Time for Different UABS Deployment Algorithms 277
10.8 Concluding remarks 279
References 279
11 Joint Trajectory and Resource Optimization 283
Yong Zeng, Qingqing Wu, and Rui Zhang
11.1 General Problem Formulation 283
11.2 Initial Path Planning via the Traveling Salesman and Pickup-and-Delivery Problems 285
11.2.1 TSP without Return 286
11.2.2 TSP with Given Initial and Final Locations 287
11.2.3 TSP with Neighborhood 287
11.2.4 Pickup-and-Delivery Problem 288
11.3 Trajectory Discretization 290
11.3.1 Time Discretization 290
11.3.2 Path Discretization 291
11.4 Block Coordinate Descent 291
11.5 Successive Convex Approximation 292
11.6 Unified Algorithm 295
11.7 Summary 296
References 296
12 Energy-Efficient UAV Communications 299
Yong Zeng and Rui Zhang
12.1 UAV Energy Consumption Model 299
12.1.1 Fixed-Wing Energy Model 300
12.1.1.1 Forces on a UAV 300
12.1.1.2 Straight and Level Flight 301
12.1.1.3 Circular Flight 302
12.1.1.4 Arbitrary Level Flight 303
12.1.1.5 Arbitrary 3D Flight 304
12.1.2 Rotary-Wing Energy Model 304
12.2 Energy Efficiency Maximization 306
12.3 Energy Minimization with Communication Requirement 310
12.4 UAV-Ground Energy Trade-off 312
12.5 Chapter Summary 312
References 313
13 Fundamental Trade-Offs for UAV Communications 315
Qingqing Wu, Liang Liu, Yong Zeng, and Rui Zhang
13.1 Introduction 315
13.2 Fundamental Trade-offs 317
13.2.1 Throughput-Delay Trade-Off 317
13.2.2 Throughput-Energy Trade-Off 318
13.2.3 Delay-Energy Trade-Off 319
13.3 Throughput-Delay Trade-Off 319
13.3.1 Single-UAV-Enabled Wireless Network 319
13.3.2 Multi-UAV-Enabled Wireless Network 321
13.4 Throughput-Energy Trade-Off 323
13.4.1 UAV Propulsion Energy Consumption Model 323
13.4.2 Energy-Constrained Trajectory Optimization 324
13.5 Further Discussions and Future Work 325
13.6 Chapter Summary 327
References 327
14 UAV-Cellular Spectrum Sharing 329
Chiya Zhang and Wei Zhang
14.1 Introduction 329
14.1.1 Cognitive Radio 329
14.1.1.1 Overlay Spectrum Sharing 329
14.1.1.2 Underlay Spectrum Sharing 330
14.1.2 Drone Communication 330
14.1.2.1 UAV Spectrum Sharing 331
14.1.2.2 UAV Spectrum Sharing with Exclusive Regions 332
14.1.3 Chapter Overview 333
14.2 SNR Meta-Distribution of Drone Networks 333
14.2.1 Stochastic Geometry Analysis 333
14.2.2 Characteristic Function of the SNR Meta-Distribution 334
14.2.3 LOS Probability 338
14.3 Spectrum Sharing of Drone Networks 338
14.3.1 Spectrum Sharing in Single-Tier DSCs 339
14.3.2 Spectrum Sharing with Cellular Network 342
14.4 Summary 345
References 346
Part IV Other Advanced Technologies for UAV Communications 349
15 Non-Orthogonal Multiple Access for UAV Communications 351
Tianwei Hou, Yuanwei Liu, and Xin Sun
15.1 Introduction 351
15.1.1 Motivation 352
15.2 User-Centric Strategy for Emergency Communications 352
15.2.1 System Model 354
15.2.1.1 Far user case 354
15.2.1.2 Near user case 355
15.2.2 Coverage Probability of the User-Centric Strategy 356
15.3 UAV-Centric Strategy for Offloading Actions 359
15.3.1 SINR Analysis 360
15.3.2 Coverage Probability of the UAV-Centric Strategy 361
15.4 Numerical Results 364
15.4.1 User-Centric Strategy 365
15.4.2 UAV-Centric Strategy 367
15.5 Conclusions 369
References 369
16 Physical Layer Security for UAV Communications 373
Nadisanka Rupasinghe, Yavuz Yapici, Ismail Guvenc, Huaiyu Dai, and Arupjyoti Bhuyan
16.1 Introduction 373
16.2 Breaching Security in Wireless Networks 374
16.2.1 Denial-of-Service Attacks 374
16.2.2 Masquerade Attacks 374
16.2.3 Message Modification Attacks 374
16.2.4 Eavesdropping Intruders 375
16.2.5 Traffic Analysis 375
16.3 Wireless Network Security Requirements 375
16.3.1 Authenticity 375
16.3.2 Confidentiality 376
16.3.3 Integrity 376
16.3.4 Availability 376
16.4 Physical Layer Security 376
16.4.1 Physical Layer versus Upper Layers 377
16.4.2 Physical Layer Security Techniques 377
16.4.2.1 Artificial Noise 378
16.4.2.2 Cooperative Jamming 378
16.4.2.3 Protected Zone 378
16.5 Physical Layer Security for UAVs 379
16.5.1 UAV Trajectory Design to Enhance PLS 379
16.5.2 Cooperative Jamming to Enhance PLS 381
16.5.3 Spectral- and Energy-Efficient PLS Techniques 382
16.6 A Case Study: Secure UAV Transmission 383
16.6.1 System Model 383
16.6.1.1 Location Distribution and mmWave Channel Model 385
16.6.2 Protected Zone Approach for Enhancing PLS 385
16.6.3 Secure NOMA for UAV BS Downlink 386
16.6.3.1 Secrecy Outage and Sum Secrecy Rates 386
16.6.3.2 Shape Optimization for Protected Zone 388
16.6.3.3 Numerical Results 389
16.6.3.4 Location of the Most Detrimental Eavesdropper 389
16.6.3.5 Impact of the Protected Zone Shape on Secrecy Rates 390
16.6.3.6 Variation of Secrecy Rates with Altitude 391
Summary 392
References 393
17 UAV-Enabled Wireless Power Transfer 399
Jie Xu, Yong Zeng, and Rui Zhang
17.1 Introduction 399
17.2 System Model 401
17.3 Sum-Energy Maximization 402
17.4 Min-Energy Maximization under Infinite Charging Duration 403
17.4.1 Multi-Location-Hovering Solution 404
17.5 Min-Energy Maximization Under Finite Charging Duration 407
17.5.1 Successive Hover-and-Fly Trajectory Design 407
17.5.1.1 Flying Distance Minimization to Visit Gamma Hovering Locations 407
17.5.1.2 Hovering Time Allocation When T >= Tfly 408
17.5.1.3 Trajectory Refinement When T fly 409
17.5.2 SCA-Based Trajectory Design 409
17.6 Numerical Results 411
17.7 Conclusion and Future Research Directions 413
References 415
18 Ad-Hoc Networks in the Sky 417
Kamesh Namuduri
18.1 Communication Support for UAVs 417
18.1.1 Satellite Connectivity 418
18.1.2 Cellular Connectivity 420
18.1.3 Aerial Connectivity 420
18.2 The Mobility Challenge 421
18.2.1 UAS-to-UAS Communication 421
18.2.2 Mobility Models 422
18.3 Establishing an Ad-Hoc Network 423
18.3.1 Network Addressing 424
18.3.2 Routing 425
18.4 Standards 426
18.4.1 ASTM: Remote ID for UAS 426
18.4.2 EUROCAE: Safe, Secure, and Efficient UAS Operations 426
18.4.3 3GPP: 4G LTE and 5G Support for Connected UAS Operations 426
18.4.4 IEEE P1920.1: Aerial Communications and Networking Standards 427
18.4.5 IEEE P1920.2: Vehicle-to-Vehicle Communications Standard for UAS 427
18.5 Technologies and Products 427
18.5.1 Silvus Streamcaster 427
18.5.2 goTenna 427
18.5.3 MPU5 and Wave Relay from Persistent Systems 428
18.5.4 Kinetic Mesh Networks from Rajant 428
18.6 Software-Defined Network as a Solution for UAV Networks 428
18.7 Summary 429
References 429
Index 433
Acronyms xxi
Part I Fundamentals of UAV Communications 1
1 Overview 3
Qingqing Wu, Yong Zeng, and Rui Zhang
1.1 UAV Definitions, Classes, and Global Trend 3
1.2 UAV Communication and Spectrum Requirement 4
1.3 Potential Existing Technologies for UAV Communications 6
1.3.1 Direct Link 6
1.3.2 Satellite 7
1.3.3 Ad-Hoc Network 8
1.3.4 Cellular Network 8
1.4 Two Paradigms in Cellular UAV Communications 9
1.4.1 Cellular-Connected UAVs 9
1.4.2 UAV-Assisted Wireless Communications 10
1.5 New Opportunities and Challenges 11
1.5.1 High Altitude 11
1.5.2 High LoS Probability 12
1.5.3 High 3D Mobility 12
1.5.4 SWAP Constraints 13
1.6 Chapter Summary and Main Organization of the Book 13
References 15
2 A Survey of Air-to-Ground Propagation Channel Modeling for Unmanned Aerial Vehicles 17
Wahab Khawaja, Ismail Guvenc, David W. Matolak, Uwe-Carsten Fiebig, and Nicolas Schneckenberger
2.1 Introduction 17
2.2 Literature Review 20
2.2.1 Literature Review on Aerial Propagation 20
2.2.2 Existing Surveys on UAV AG Propagation 21
2.3 UAV AG Propagation Characteristics 22
2.3.1 Comparison of UAV AG and Terrestrial Propagation 22
2.3.2 Frequency Bands for UAV AG Propagation 23
2.3.3 Scattering Characteristics for AG Propagation 24
2.3.4 Antenna Configurations for AG Propagation 24
2.3.5 Doppler Effects 25
2.4 AG Channel Measurements: Configurations, Challenges, Scenarios, and Waveforms 25
2.4.1 Channel Measurement Configurations 26
2.4.2 Challenges in AG Channel Measurements 29
2.4.3 AG Propagation Scenarios 29
2.4.3.1 Open Space 31
2.4.3.2 Hilly/Mountainous 31
2.4.3.3 Forest 32
2.4.3.4 Water/Sea 32
2.4.4 Elevation Angle Effects 32
2.5 UAV AG Propagation Measurement and Simulation Results in the Literature 33
2.5.1 Path Loss/Shadowing 33
2.5.2 Delay Dispersion 36
2.5.3 Narrowband Fading and Ricean K-factor 36
2.5.4 Doppler Spread 37
2.5.5 Effects of UAV AG Measurement Environment 37
2.5.5.1 Urban/Suburban 38
2.5.5.2 Rural/Open Field 38
2.5.5.3 Mountains/Hilly, Over Sea, Forest 39
2.5.6 Simulations for Channel Characterization 40
2.6 UAV AG Propagation Models 41
2.6.1 AG Propagation Channel Model Types 41
2.6.2 Path-Loss and Large-Scale Fading Models 42
2.6.2.1 Free-Space Path-Loss Model 43
2.6.2.2 Floating-Intercept Path-Loss Model 43
2.6.2.3 Dual-Slope Path-Loss Model 43
2.6.2.4 Log-Distance Path-Loss Model 45
2.6.2.5 Modified FSPL Model 45
2.6.2.6 Two-Ray PL Model 45
2.6.2.7 Log-Distance FI Model 45
2.6.2.8 LOS/NLOS Mixture Path-Loss Model 46
2.6.3 Airframe Shadowing 47
2.6.4 Small-Scale Fading Models 47
2.6.5 Intermittent MPCs 48
2.6.6 Effect of Frequency Bands on Channel Models 51
2.6.7 MIMO AG Propagation Channel Models 52
2.6.8 Comparison of Different AG Channel Models 54
2.6.8.1 Large-Scale Fading Models 54
2.6.8.2 Small-Scale Fading Models 54
2.6.9 Comparison of Traditional Channel Models with UAV AG Propagation Channel Models 55
2.6.10 Ray Tracing Simulations 56
2.6.11 3GPP Channel Models for UAVs 58
2.7 Conclusions 60
References 60
3 UAV Detection and Identification 71
Martins Ezuma, Fatih Erden, Chethan Kumar Anjinappa, Ozgur Ozdemir, Ismail Guvenc, and David Matolak
3.1 Introduction 71
3.2 RF-Based UAV Detection Techniques 75
3.2.1 RF Fingerprinting Technique 76
3.2.2 WiFi Fingerprinting Technique 76
3.3 Multistage UAV RF Signal Detection 77
3.3.1 Preprocessing Step: Multiresolution Analysis 78
3.3.2 The Naive Bayesian Decision Mechanism for RF Signal Detection 82
3.3.3 Detection of WiFi and Bluetooth Interference 84
3.4 UAV Classification Using RF Fingerprints 89
3.4.1 Feature Selection Using Neighborhood Components Analysis (NCA) 91
3.5 Experimental Results 92
3.5.1 Experimental Setup 92
3.5.2 Detection Results 94
3.5.3 UAV Classification Results 95
3.6 Conclusion 100
Acknowledgments 100
References 100
Part II Cellular-Connected UAV Communications 103
4 Performance Analysis for Cellular-Connected UAVs 105
M. Mahdi Azari, Fernando Rosas, and Sofie Pollin
4.1 Introduction 105
4.1.1 Motivation 105
4.1.2 Related Works 107
4.1.3 Contributions and Chapter Structure 108
4.2 Modelling Preliminaries 109
4.2.1 Stochastic Geometry 109
4.2.2 Network Architecture 110
4.2.3 Channel Model 111
4.2.4 Blockage Modeling and LoS Probability 112
4.2.5 User Association Strategy and Link SINR 112
4.3 Performance Analysis 112
4.3.1 Exact Coverage Probability 113
4.3.2 Approximations for UAV Coverage Probability 115
4.3.2.1 Discarding NLoS and Noise Effects 116
4.3.2.2 Moment Matching 116
4.3.3 Achievable Throughput and Area Spectral Efficiency Analysis 118
4.4 System Design: Study Cases and Discussion 119
4.4.1 Analysis of Accuracy 119
4.4.2 Design Parameters 120
4.4.2.1 Impact of UAV Altitude 120
4.4.2.2 Impact of UAV Antenna Beamwidth 121
4.4.2.3 Impact of UAV Antenna Tilt 123
4.4.2.4 Impact of Different Types of Environment 123
4.4.3 Heterogeneous Networks - Tier Selection 125
4.4.4 Network Densification 127
4.5 Conclusion 129
References 136
5 Performance Enhancements for LTE-Connected UAVs: Experiments and Simulations 139
Rafhael Medeiros de Amorim, Jeroen Wigard, István Z. Kovács, and Troels B. Sørensen
5.1 Introduction 139
5.2 LTE Live Network Measurements 140
5.2.1 Downlink Experiments 141
5.2.2 Path-Loss Model Characterization 145
5.2.3 Uplink Experiments 145
5.3 Performance in LTE Networks 149
5.4 Reliability Enhancements 150
5.4.1 Interference Cancellation 151
5.4.2 Inter-Cell Interference Control 152
5.4.3 CoMP 152
5.4.4 Antenna Beam Selection 153
5.4.5 Dual LTE Access 155
5.4.6 Dedicated Spectrum 158
5.4.7 Discussion 158
5.5 Summary and Outlook 159
References 160
6 3GPP Standardization for Cellular-Supported UAVs 163
Helka-Liina Määttänen
6.1 Short Introduction to LTE and NR 163
6.1.1 LTE Physical Layer and MIMO 165
6.1.2 NR Physical Layer and MIMO 166
6.2 Drones Served by Mobile Networks 167
6.2.1 Interference Detection and Mitigation 168
6.2.2 Mobility for Drones 170
6.2.3 Need for Drone Identification and Authorization 171
6.3 3GPP Standardization Support for UAVs 172
6.3.1 Measurement Reporting Based on RSRP Level of Multiple Cells 172
6.3.2 Height, Speed, and Location Reporting 174
6.3.3 Uplink Power Control Enhancement 175
6.3.4 Flight Path Signalling 175
6.3.5 Drone Authorization and Identification 176
6.4 Flying Mode Detection in Cellular Networks 177
References 179
7 Enhanced Cellular Support for UAVs with Massive MIMO 181
Giovanni Geraci, Adrian Garcia-Rodriguez, Lorenzo Galati Giordano, and David López-Pérez
7.1 Introduction 181
7.2 System Model 181
7.2.1 Cellular Network Topology 183
7.2.2 System Model 184
7.2.3 Massive MIMO Channel Estimation 186
7.2.4 Massive MIMO Spatial Multiplexing 186
7.3 Single-User Downlink Performance 187
7.3.1 UAV Downlink C&C Channel 187
7.4 Massive MIMO Downlink Performance 190
7.4.1 UAV Downlink C&C Channel 190
7.4.2 UAV-GUE Downlink Interplay 192
7.5 Enhanced Downlink Performance 194
7.5.1 UAV Downlink C&C Channel 195
7.5.2 UAV-GUE Downlink Interplay 196
7.6 Uplink Performance 197
7.6.1 UAV Uplink C&C Channel and Data Streaming 197
7.6.2 UAV-GUE Uplink Interplay 198
7.7 Conclusions 199
References 200
8 High-Capacity Millimeter Wave UAV Communications 203
Nuria González-Prelcic, Robert W. Heath, Cristian Rusu, and Aldebaro Klautau
8.1 Motivation 203
8.2 UAV Roles and Use Cases Enabled by Millimeter Wave Communication 206
8.2.1 UAV Roles in Cellular Networks 206
8.2.2 UAV Use Cases Enabled by High-Capacity Cellular Networks 207
8.3 Aerial Channel Models at Millimeter Wave Frequencies 208
8.3.1 Propagation Considerations for Aerial Channels 208
8.3.1.1 Atmospheric Considerations 208
8.3.1.2 Blockages 210
8.3.2 Air-to-Air Millimeter Wave Channel Model 211
8.3.3 Air-to-Ground Millimeter Wave Channel Model 212
8.3.4 Ray Tracing as a Tool to Obtain Channel Measurements 214
8.4 Key Aspects of UAV MIMO Communication at mmWave Frequencies 215
8.5 Establishing Aerial mmWave MIMO Links 219
8.5.1 Beam Training and Tracking for UAV Millimeter Wave Communication 219
8.5.2 Channel Estimation and Tracking in Aerial Environments 219
8.5.3 Design of Hybrid Precoders and Combiners 221
8.6 Research Opportunities 222
8.6.1 Sensing at the Tower 222
8.6.2 Joint Communication and Radar 222
8.6.3 Positioning and Mapping 223
8.7 Conclusions 223
References 223
Part III UAV-Assisted Wireless Communications 231
9 Stochastic Geometry-Based Performance Analysis of Drone Cellular Networks 233
Morteza Banagar, Vishnu V. Chetlur, and Harpreet S. Dhillon
9.1 Introduction 233
9.2 Overview of the System Model 235
9.2.1 Spatial Model 235
9.2.2 3GPP-Inspired Mobility Model 236
9.2.3 Channel Model 237
9.2.4 Metrics of Interest 237
9.3 Average Rate 238
9.4 Handover Probability 242
9.5 Results and Discussion 246
9.5.1 Density of Interfering DBSs 247
9.5.2 Average Rate 247
9.5.3 Handover Probability 249
9.6 Conclusion 250
Acknowledgment 251
References 251
10 UAV Placement and Aerial-Ground Interference Coordination 255
Abhaykumar Kumbhar and Ismail Guvenc
10.1 Introduction 255
10.2 Literature Review 256
10.3 UABS Use Case for AG-HetNets 259
10.4 UABS Placement in AG-HetNet 260
10.5 AG-HetNet Design Guidelines 264
10.5.1 Path-Loss Model 265
10.5.1.1 Log-Distance Path-Loss Model 265
10.5.1.2 Okumura-Hata Path-Loss Model 266
10.6 Inter-Cell Interference Coordination 266
10.6.1 UE Association and Scheduling 269
10.7 Simulation Results 270
10.7.1 5pSE with UABSs Deployed on Hexagonal Grid 270
10.7.1.1 5pSE with Log-Normal Path-Loss Model 270
10.7.1.2 5pSE with Okumura-Hata Path-Loss Model 271
10.7.2 5pSE with GA-Based UABS Deployment Optimization 273
10.7.2.1 5pSE with Log-Normal Path-Loss Model 273
10.7.2.2 5pSE with Okumura-Hata Path-Loss model 275
10.7.3 Performance Comparison Between Fixed (Hexagonal) and Optimized UABS Deployment with eICIC and FeICIC 276
10.7.3.1 Influence of LDPLM on 5pSE 277
10.7.3.2 Influence of OHPLM on 5pSE 277
10.7.4 Comparison of Computation Time for Different UABS Deployment Algorithms 277
10.8 Concluding remarks 279
References 279
11 Joint Trajectory and Resource Optimization 283
Yong Zeng, Qingqing Wu, and Rui Zhang
11.1 General Problem Formulation 283
11.2 Initial Path Planning via the Traveling Salesman and Pickup-and-Delivery Problems 285
11.2.1 TSP without Return 286
11.2.2 TSP with Given Initial and Final Locations 287
11.2.3 TSP with Neighborhood 287
11.2.4 Pickup-and-Delivery Problem 288
11.3 Trajectory Discretization 290
11.3.1 Time Discretization 290
11.3.2 Path Discretization 291
11.4 Block Coordinate Descent 291
11.5 Successive Convex Approximation 292
11.6 Unified Algorithm 295
11.7 Summary 296
References 296
12 Energy-Efficient UAV Communications 299
Yong Zeng and Rui Zhang
12.1 UAV Energy Consumption Model 299
12.1.1 Fixed-Wing Energy Model 300
12.1.1.1 Forces on a UAV 300
12.1.1.2 Straight and Level Flight 301
12.1.1.3 Circular Flight 302
12.1.1.4 Arbitrary Level Flight 303
12.1.1.5 Arbitrary 3D Flight 304
12.1.2 Rotary-Wing Energy Model 304
12.2 Energy Efficiency Maximization 306
12.3 Energy Minimization with Communication Requirement 310
12.4 UAV-Ground Energy Trade-off 312
12.5 Chapter Summary 312
References 313
13 Fundamental Trade-Offs for UAV Communications 315
Qingqing Wu, Liang Liu, Yong Zeng, and Rui Zhang
13.1 Introduction 315
13.2 Fundamental Trade-offs 317
13.2.1 Throughput-Delay Trade-Off 317
13.2.2 Throughput-Energy Trade-Off 318
13.2.3 Delay-Energy Trade-Off 319
13.3 Throughput-Delay Trade-Off 319
13.3.1 Single-UAV-Enabled Wireless Network 319
13.3.2 Multi-UAV-Enabled Wireless Network 321
13.4 Throughput-Energy Trade-Off 323
13.4.1 UAV Propulsion Energy Consumption Model 323
13.4.2 Energy-Constrained Trajectory Optimization 324
13.5 Further Discussions and Future Work 325
13.6 Chapter Summary 327
References 327
14 UAV-Cellular Spectrum Sharing 329
Chiya Zhang and Wei Zhang
14.1 Introduction 329
14.1.1 Cognitive Radio 329
14.1.1.1 Overlay Spectrum Sharing 329
14.1.1.2 Underlay Spectrum Sharing 330
14.1.2 Drone Communication 330
14.1.2.1 UAV Spectrum Sharing 331
14.1.2.2 UAV Spectrum Sharing with Exclusive Regions 332
14.1.3 Chapter Overview 333
14.2 SNR Meta-Distribution of Drone Networks 333
14.2.1 Stochastic Geometry Analysis 333
14.2.2 Characteristic Function of the SNR Meta-Distribution 334
14.2.3 LOS Probability 338
14.3 Spectrum Sharing of Drone Networks 338
14.3.1 Spectrum Sharing in Single-Tier DSCs 339
14.3.2 Spectrum Sharing with Cellular Network 342
14.4 Summary 345
References 346
Part IV Other Advanced Technologies for UAV Communications 349
15 Non-Orthogonal Multiple Access for UAV Communications 351
Tianwei Hou, Yuanwei Liu, and Xin Sun
15.1 Introduction 351
15.1.1 Motivation 352
15.2 User-Centric Strategy for Emergency Communications 352
15.2.1 System Model 354
15.2.1.1 Far user case 354
15.2.1.2 Near user case 355
15.2.2 Coverage Probability of the User-Centric Strategy 356
15.3 UAV-Centric Strategy for Offloading Actions 359
15.3.1 SINR Analysis 360
15.3.2 Coverage Probability of the UAV-Centric Strategy 361
15.4 Numerical Results 364
15.4.1 User-Centric Strategy 365
15.4.2 UAV-Centric Strategy 367
15.5 Conclusions 369
References 369
16 Physical Layer Security for UAV Communications 373
Nadisanka Rupasinghe, Yavuz Yapici, Ismail Guvenc, Huaiyu Dai, and Arupjyoti Bhuyan
16.1 Introduction 373
16.2 Breaching Security in Wireless Networks 374
16.2.1 Denial-of-Service Attacks 374
16.2.2 Masquerade Attacks 374
16.2.3 Message Modification Attacks 374
16.2.4 Eavesdropping Intruders 375
16.2.5 Traffic Analysis 375
16.3 Wireless Network Security Requirements 375
16.3.1 Authenticity 375
16.3.2 Confidentiality 376
16.3.3 Integrity 376
16.3.4 Availability 376
16.4 Physical Layer Security 376
16.4.1 Physical Layer versus Upper Layers 377
16.4.2 Physical Layer Security Techniques 377
16.4.2.1 Artificial Noise 378
16.4.2.2 Cooperative Jamming 378
16.4.2.3 Protected Zone 378
16.5 Physical Layer Security for UAVs 379
16.5.1 UAV Trajectory Design to Enhance PLS 379
16.5.2 Cooperative Jamming to Enhance PLS 381
16.5.3 Spectral- and Energy-Efficient PLS Techniques 382
16.6 A Case Study: Secure UAV Transmission 383
16.6.1 System Model 383
16.6.1.1 Location Distribution and mmWave Channel Model 385
16.6.2 Protected Zone Approach for Enhancing PLS 385
16.6.3 Secure NOMA for UAV BS Downlink 386
16.6.3.1 Secrecy Outage and Sum Secrecy Rates 386
16.6.3.2 Shape Optimization for Protected Zone 388
16.6.3.3 Numerical Results 389
16.6.3.4 Location of the Most Detrimental Eavesdropper 389
16.6.3.5 Impact of the Protected Zone Shape on Secrecy Rates 390
16.6.3.6 Variation of Secrecy Rates with Altitude 391
Summary 392
References 393
17 UAV-Enabled Wireless Power Transfer 399
Jie Xu, Yong Zeng, and Rui Zhang
17.1 Introduction 399
17.2 System Model 401
17.3 Sum-Energy Maximization 402
17.4 Min-Energy Maximization under Infinite Charging Duration 403
17.4.1 Multi-Location-Hovering Solution 404
17.5 Min-Energy Maximization Under Finite Charging Duration 407
17.5.1 Successive Hover-and-Fly Trajectory Design 407
17.5.1.1 Flying Distance Minimization to Visit Gamma Hovering Locations 407
17.5.1.2 Hovering Time Allocation When T >= Tfly 408
17.5.1.3 Trajectory Refinement When T fly 409
17.5.2 SCA-Based Trajectory Design 409
17.6 Numerical Results 411
17.7 Conclusion and Future Research Directions 413
References 415
18 Ad-Hoc Networks in the Sky 417
Kamesh Namuduri
18.1 Communication Support for UAVs 417
18.1.1 Satellite Connectivity 418
18.1.2 Cellular Connectivity 420
18.1.3 Aerial Connectivity 420
18.2 The Mobility Challenge 421
18.2.1 UAS-to-UAS Communication 421
18.2.2 Mobility Models 422
18.3 Establishing an Ad-Hoc Network 423
18.3.1 Network Addressing 424
18.3.2 Routing 425
18.4 Standards 426
18.4.1 ASTM: Remote ID for UAS 426
18.4.2 EUROCAE: Safe, Secure, and Efficient UAS Operations 426
18.4.3 3GPP: 4G LTE and 5G Support for Connected UAS Operations 426
18.4.4 IEEE P1920.1: Aerial Communications and Networking Standards 427
18.4.5 IEEE P1920.2: Vehicle-to-Vehicle Communications Standard for UAS 427
18.5 Technologies and Products 427
18.5.1 Silvus Streamcaster 427
18.5.2 goTenna 427
18.5.3 MPU5 and Wave Relay from Persistent Systems 428
18.5.4 Kinetic Mesh Networks from Rajant 428
18.6 Software-Defined Network as a Solution for UAV Networks 428
18.7 Summary 429
References 429
Index 433
Yong Zeng is a Professor at the National Mobile Communications Research Laboratory, Southeast University, China, and also with the Purple Mountain Laboratories, Nanjing, China. He is recognized as a Highly Cited Researcher by Web of Science Group. He is the recipient of IEEE Communications Society Asia-Pacific Outstanding Young Researcher Award and IEEE Marconi Prize Paper Award in Wireless Communications.
Ismail Guvenc is a Professor at North Carolina State University in the United States. He formerly worked with DOCOMO Innovations, Florida International University, and Mitsubishi Electric Research Labs. His recent research interests include 5G/6G wireless systems, aerial communications for UTM/AAM, and mmWave communications.
Rui Zhang is a Professor with the National University of Singapore. His current research interests include wireless information and power transfer, drone communication, and reconfigurable MIMO.
Giovanni Geraci is an Assistant Professor at Universitat Pompeu Fabra, Barcelona. He was previously with Nokia Bell Labs and holds a Ph.D. from UNSW Sydney. He is a "la Caixa" Junior Leader and a "Ramón y Cajal" Fellow, and the recipient of the IEEE ComSoc Europe, Middle East, and Africa Outstanding Young Researcher Award.
David W. Matolak is Professor at the University of South Carolina in the United States. He has over 20 years of experience in communication systems research, development, design, and deployment. He has worked with private firms, government institutions, and academic labs.
Ismail Guvenc is a Professor at North Carolina State University in the United States. He formerly worked with DOCOMO Innovations, Florida International University, and Mitsubishi Electric Research Labs. His recent research interests include 5G/6G wireless systems, aerial communications for UTM/AAM, and mmWave communications.
Rui Zhang is a Professor with the National University of Singapore. His current research interests include wireless information and power transfer, drone communication, and reconfigurable MIMO.
Giovanni Geraci is an Assistant Professor at Universitat Pompeu Fabra, Barcelona. He was previously with Nokia Bell Labs and holds a Ph.D. from UNSW Sydney. He is a "la Caixa" Junior Leader and a "Ramón y Cajal" Fellow, and the recipient of the IEEE ComSoc Europe, Middle East, and Africa Outstanding Young Researcher Award.
David W. Matolak is Professor at the University of South Carolina in the United States. He has over 20 years of experience in communication systems research, development, design, and deployment. He has worked with private firms, government institutions, and academic labs.
