LTE-Advanced and Next Generation Wireless Networks : Channel Modelling and Propagation
ISBN: 9781119976707 | 1119976707
Edition: 1stFormat: Hardcover
Publisher: Wiley
Pub. Date: 11/28/2012
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LTE- A and Next Generation Wireless Networks: Channel Modeling and Performance describes recent advances in propagation and channel modeling necessary for simulating next generation wireless systems. Due to the radio spectrum scarcity, two fundamental changes are anticipated compared to the current status.
This book discusses propagation and channel modeling for LTE Advanced and emerging wireless technologies LTE- Advanced and Next Generation Wireless Networks: Channel Modeling and Propagation describes recent adva... MORE
This book discusses propagation and channel modeling for LTE Advanced and emerging wireless technologies LTE- Advanced and Next Generation Wireless Networks: Channel Modeling and Propagation describes recent adva... MORE
About the Editors xv
List of Contributors xvii
Preface xix
Acknowledgements xxiii
List of Acronyms xxv
Part I BACKGROUND
1 Enabling Technologies for 3GPP LTE-Advanced Networks 3
Narcis Cardona, Jose F. Monserrat and Jorge Cabrejas
1.1 Introduction 4
1.2 General IMT-Advanced Features and Requirements 5
1.2.1 Services 5
1.2.2 Spectrum 5
1.2.3 Technical Performance 6
1.3 Long Term Evolution Advanced Requirements 11
1.3.1 Requirements Related ... MORE
1.3.2 System Performance 13
1.3.3 Deployment 14
1.4 Long Term Evolution Advanced Enabling Technologies 15
1.4.1 Carrier Aggregation 15
1.4.2 Advanced MIMO Techniques 19
1.4.3 Coordinated Multipoint Transmission or Reception 21
1.4.4 Relaying 23
1.4.5 Enhancements for Home eNodeBs 26
1.4.6 Machine-Type Communications 28
1.4.7 Self-Optimizing Networks (SON) 29
1.4.8 Improvements to Latency in the Control and User Plane 30
1.5 Summary 33
References 33
2 Propagation and Channel Modeling Principles 35
Andreas F. Molisch
2.1 Propagation Principles 35
2.1.1 Free-Space Propagation and Antenna Gain 36
2.1.2 Reflection and Transmission 36
2.1.3 Diffraction 37
2.1.4 Scattering 38
2.1.5 Waveguiding 39
2.1.6 Multipath Propagation 40
2.2 Deterministic Channel Descriptions 41
2.2.1 Time Variant Impulse Response 42
2.2.2 Directional Description and MIMO Matrix 44
2.2.3 Polarization 45
2.2.4 Ultrawideband Description 45
2.3 Stochastic Channel Description 46
2.3.1 Pathloss and Shadowing 47
2.3.2 Small-Scale Fading 48
2.3.3 WSSUS 49
2.3.4 Extended WSSUS 51
2.4 Channel Modeling Methods 51
2.4.1 Deterministic Modeling 51
2.4.2 Modeling Hierarchies 52
2.4.3 Clustering 53
2.4.4 Stochastic Modeling 56
2.4.5 Geometry-Based Stochastic Models 58
2.4.6 Diffuse Multipath Components 61
2.4.7 Multi-Link Stochastic Models 61
References 62
Part II RADIO CHANNELS
3 Indoor Channels 67
Jianhua Zhang and Guangyi Liu
3.1 Introduction 67
3.2 Indoor Large Scale Fading 69
3.2.1 Indoor Large Scale Models 69
3.2.2 Summary of Indoor Large Scale Characteristics 72
3.2.3 Important Factors for Indoor Propagation 78
3.3 Indoor Small Scale Fading 83
3.3.1 Geometry-Based Stochastic Channel Model 83
3.3.2 Statistical Characteristics in Delay Domain 84
3.3.3 Statistical Parameter in Angular Domain 87
3.3.4 Cross-Polarization Discrimination (XPD) for Indoor Scenario 88
3.3.5 3-D Modeling for Indoor MIMO Channel 90
3.3.6 Impact of Elevation Angular Distribution 92
References 93
4 Outdoor Channels 97
Petros Karadimas
4.1 Introduction 97
4.2 Reference Channel Model 98
4.3 Small Scale Variations 103
4.3.1 First Order Statistical Characterization 103
4.3.2 Second Order Statistical Characterization 106
4.4 Path Loss and Large Scale Variations 117
4.5 Summary 119
Acknowledgements 120
References 120
5 Outdoor-Indoor Channel 123
Andr´es Alay´on Glazunov, Zhihua Lai and Jie Zhang
5.1 Introduction 123
5.2 Modelling Principles 124
5.3 Empirical Propagation Models 127
5.3.1 Path Loss Exponent Model 128
5.3.2 Path Loss Exponent Model with Mean Building Penetration Loss 128
5.3.3 Partition-Based Outdoor-to-Indoor Model 130
5.3.4 Path Loss Exponent Model with Building Penetration Loss 130
5.3.5 COST 231 Building Penetration Loss Model 131
5.3.6 Excess Path Loss Building Penetration Models 133
5.3.7 Extended COST 231 WI Building Penetration at the LOS Condition 134
5.3.8 WINNER II Outdoor-to-Indoor Path Loss Models 135
5.4 Deterministic Models 137
5.4.1 FDTD 138
5.4.2 Ray-Based Methods 138
5.4.3 Intelligent Ray Launching Algorithm (IRLA) 141
5.5 Hybrid Models 142
5.5.1 Antenna Radiation Pattern 142
5.5.2 Calibration 143
5.5.3 IRLA Case Study: INSA 144
5.5.4 IRLA Case Study: Xinghai 149
Acknowledgements 149
References 149
6 Vehicular Channels 153
Laura Bernad´o, Nicolai Czink, Thomas Zemen, Alexander Paier, Fredrik Tufvesson, Christoph Mecklenbr¨auker and Andreas F. Molisch
6.1 Introduction 153
6.2 Radio Channel Measurements 154
6.2.1 Channel Sounders 155
6.2.2 Vehicular Antennas 157
6.2.3 Vehicular Measurement Campaigns 158
6.3 Vehicular Channel Characterization 160
6.3.1 Time-Variability of the Channel 160
6.3.2 Time-Varying Vehicular Channel Parameters 166
6.3.3 Empirical Results 169
6.4 Channel Models for Vehicular Communications 171
6.4.1 Channel Modeling Techniques 171
6.4.2 Geometry-Based Stochastic Channel Modeling 173
6.4.3 Low-Complexity Geometry-Based Stochastic Channel Model Simulation 177
6.5 New Vehicular Communication Techniques 180
6.5.1 OFDM Physical (PHY) and Medium Access 180
6.5.2 Relaying Techniques 181
6.5.3 Cooperative Coding and Distributed Sensing 182
6.5.4 Outlook 182
References 182
7 Multi-User MIMO Channels 187
Fredrik Tufvesson, Katsuyuki Haneda and Veli-Matti Kolmonen
7.1 Introduction 187
7.2 Multi-User MIMO Measurements 188
7.2.1 General Information About Measurements 188
7.2.2 Measurement Techniques 189
7.2.3 Phase Noise 192
7.2.4 Measurement Antennas 192
7.2.5 Measurement Campaigns 193
7.3 Multi-User Channel Characterization 196
7.4 Multi-User Channel Models 200
7.4.1 Analytical Model 200
7.4.2 General Cluster Model 202
7.4.3 Particular Implementation of Cluster Models 206
References 210
8 Wideband Channels 215
Vit Sipal, David Edward and Ben Allen
8.1 Large Scale Channel Properties 216
8.1.1 Path Gain – Range Dependency 217
8.1.2 Path Gain – Frequency Dependency 217
8.2 Impulse Response of UWB Channel 219
8.2.1 Impulse Response According to IEEE802.15.4a 220
8.2.2 Impact of Antenna Impulse Response in Free Space 221
8.2.3 Manifestation of Antenna Impulse Response in Realistic Indoor Channels 222
8.2.4 New Channel Model For UWB 223
8.2.5 UWB Channel Impulse Response – Simplified Model for Practical Use 225
8.2.6 UWB Channel Impulse Response – Conclusion 225
8.3 Frequency Selective Fading in UWB Channels 226
8.3.1 Fade Depth Scaling 228
8.3.2 Probability Distribution Function of Fading 232
8.4 Multiple Antenna Techniques 239
8.4.1 Wideband Array Descriptors 239
8.4.2 Antenna Arrays – UWB OFDM Systems 241
8.5 Implications for LTE-A 243
References 244
9 Wireless Body Area Network Channels 247
Rob Edwards, Muhammad Irfan Khattak and Lei Ma
9.1 Introduction 247
9.2 Wearable Antennas 249
9.3 Analysis of Antennas Close to Human Skin 251
9.3.1 Complex Permittivity and Equivalent Conductivity of Medium 252
9.3.2 Properties of Human Body Tissue 253
9.3.3 Energy Loss in Biological Tissue 256
9.3.4 Body Effects on the Q Factor and Bandwidth of Wearable Antennas 256
9.4 A Survey of Popular On-Body Propagation Models 259
9.5 Antenna Implants-Possible Future Trends 263
9.6 Summary 265
References 265
Part III SIMULATION AND PERFORMANCE
10 Ray-Tracing Modeling 271
Yves Lostanlen and Thomas K¨urner
10.1 Introduction 271
10.2 Main Physical Phenomena Involved in Propagation 272
10.2.1 Basic Terms and Principles 273
10.2.2 Free Space Propagation 275
10.2.3 Reflection and Transmission 275
10.2.4 Diffraction 276
10.2.5 Scattering 277
10.3 Incorporating the Influence of Vegetation 277
10.3.1 Modeling Diffraction Over the Tree Canopy 278
10.3.2 Modeling Tree Shadowing 278
10.3.3 Modeling Diffuse Scattering from Trees 278
10.4 Ray-Tracing Methods 280
10.4.1 Modeling of the Environment 280
10.4.2 Geometric Computation of the Ray Trajectories 281
10.4.3 Direct Method or Ray-Launching 282
10.4.4 Image Method Ray-Tracing 283
10.4.5 Acceleration Techniques 284
10.4.6 Hybrid Techniques 286
10.4.7 Determination of the Electromagnetic Field Strength and Space-Time Outputs 287
10.4.8 Extension to Ultra-Wideband (UWB) Channel Modeling 287
References 289
11 Finite-Difference Modeling 293
Guillaume de la Roche
11.1 Introduction 293
11.2 Models for Solving Maxwell’s Equations 294
11.2.1 FDTD 295
11.2.2 ParFlow 296
11.3 Practical Use of FD Methods 298
11.3.1 Comparison with Ray Tracing 298
11.3.2 Complexity Reduction 299
11.3.3 Calibration 300
11.3.4 Antenna Pattern Effects 301
11.3.5 3D Approximation 302
11.4 Results 303
11.4.1 Path Loss Prediction 303
11.4.2 Fading Prediction 305
11.5 Perspectives for Finite Difference Models 308
11.5.1 Extension to 3D Models 308
11.5.2 Combination with Ray Tracing Models 309
11.5.3 Application to Wideband Channel Modeling 314
11.6 Summary and Perspectives 314
Acknowledgements 314
References 314
12 Propagation Models for Wireless Network Planning 317
Thomas K¨urner and Yves Lostanlen
12.1 Geographic Data for RNP 317
12.1.1 Terminology 318
12.1.2 Production Techniques 319
12.1.3 Specific Details Required for the Propagation Modeling 320
12.1.4 Raster Multi-Resolution 321
12.1.5 Raster-Vector Multi-Resolution 322
12.2 Categorization of Propagation Models 322
12.2.1 Site-General Path Loss Models 323
12.2.2 Site-Specific Path Loss and Channel Models 323
12.3 Empirical Models 325
12.3.1 Lee’s Model 325
12.3.2 Erceg’s Model 325
12.4 Semi-Empirical Models for Macro Cells 326
12.4.1 A General Formula for Semi-Empirical Models for Macro Cells 327
12.4.2 COST231-Walfisch-Ikegami-Model 330
12.4.3 Other Models 332
12.5 Deterministic Models for Urban Areas 332
12.5.1 Waveguiding in Urban Areas 332
12.5.2 Transitions between Heterogeneous Environments 333
12.5.3 Penetration Inside Buildings 333
12.5.4 Main Principles of Operational Deterministic Models 333
12.5.5 Outdoor-to-Indoor Techniques 339
12.5.6 Calibration of Parameters 339
12.6 Accuracy of Propagation Models for RNP 339
12.6.1 Measurement Campaign 340
12.6.2 Tuning (aka Calibration) Process 341
12.6.3 Model Accuracy 343
12.7 Coverage Probability 344
References 345
13 System-Level Simulations with the IMT-Advanced Channel Model 349
Jan Ellenbeck
13.1 Introduction 349
13.2 IMT-Advanced Simulation Guidelines 350
13.2.1 General System-Level Evaluation Methodology 350
13.2.2 System-Level Performance Metrics 352
13.2.3 Test Environment and Deployment Scenario Configurations 353
13.2.4 Antenna Modeling 356
13.3 The IMT-Advanced Channel Models 357
13.3.1 Large-Scale Link Properties 358
13.3.2 Initialization of Small-Scale Parameters 363
13.3.3 Coefficient Generation 364
13.3.4 Computationally Efficient Time Evolution of CIRs and CTFs 365
13.4 Channel Model Calibration 366
13.4.1 Large-Scale Calibration Metrics 367
13.4.2 Small-Scale Calibration Metrics 368
13.4.3 CIR and CTF Calibrations 370
13.5 Link-to-System Modeling for LTE-Advanced 371
13.5.1 System-Level Simulations vs. Link-Level Simulations 371
13.5.2 Modeling of MIMO Linear Receiver and Precoder Performance 374
13.5.3 Effective SINR Values 376
13.5.4 Block Error Modeling 377
13.6 3GPP LTE-Advanced System-Level Simulator Calibration 379
13.6.1 Downlink Simulation Assumptions 381
13.6.2 Uplink Simulation Assumptions 381
13.6.3 Simulator Calibration Results 382
13.7 Summary and Outlook 385
References 386
14 Channel Emulators for Emerging Communication Systems 389
Julian Webber
14.1 Introduction 389
14.2 Emulator Systems 390
14.3 Random Number Generation 391
14.3.1 Pseudo Random Noise Generator (PRNG) 392
14.3.2 Gaussian Look-Up-Table 392
14.3.3 Sum of Uniform (SoU) Distribution 392
14.3.4 Box-Muller 393
14.4 Fading Generators 394
14.4.1 Gaussian I.I.D. 395
14.4.2 Modified Jakes’ Model 396
14.4.3 Zheng Model 396
14.4.4 Random Walk Model 397
14.4.5 Ricean K-Factor 398
14.4.6 Correlation 399
14.5 Channel Convolution 401
14.6 Emulator Development 403
14.7 Example Transceiver Applications for Emerging Systems 403
14.7.1 MIMO-OFDM 403
14.7.2 Single Carrier Systems 405
14.8 Summary 407
References 408
15 MIMO Over-the-Air Testing 411
Andr´es Alay´on Glazunov, Veli-Matti Kolmonen and Tommi Laitinen
15.1 Introduction 411
15.1.1 Problem Statement 412
15.1.2 General Description of OTA Testing 413
15.2 Channel Modelling Concepts 414
15.2.1 Geometry-Based Modelling 416
15.2.2 Correlation-Based Modelling 418
15.3 DUTs and Usage Definition 418
15.4 Figures-of-Merit for OTA 419
15.5 Multi-Probe MIMO OTA Testing Methods 421
15.5.1 Multi-Probe Systems 421
15.5.2 Channel Synthesis 422
15.5.3 Field Synthesis 423
15.5.4 Two Examples of Field Synthesis Methods 426
15.5.5 Compensation of Near-Field Effects of Probes and Range Reflections 428
15.6 Other MIMO OTA Testing Methods 429
15.6.1 Reverberation Chambers 429
15.6.2 Two-Stage Method 436
15.7 Future Trends 437
References 437
16 Cognitive Radio Networks: Sensing, Access, Security 443
Ghazanfar A. Safdar
16.1 Introduction 443
16.2 Cognitive Radio: A Definition 443
16.2.1 Cognitive Radio and Spectrum Management 444
16.2.2 Cognitive Radio Networks 446
16.2.3 Cognitive Radio and OSI 447
16.3 Spectrum Sensing in CRNs 448
16.3.1 False Alarm and Missed Detection 449
16.3.2 Spectrum Sensing Techniques 450
16.3.3 Types of Spectrum Sensing 451
16.4 Spectrum Assignment–Medium Access Control in CRNs 452
16.4.1 Based on Channel Access 452
16.4.2 Based on Usage of Common Control Channel 453
16.4.3 CR Medium Access Control Protocols 455
16.5 Security in Cognitive Radio Networks 461
16.5.1 Security in CRNs: CCC Security Framework 463
16.5.2 Security in CRNs: CCC Security Framework Steps 466
16.6 Applications of CRNs 468
16.6.1 Commercial Applications 468
16.6.2 Military Applications 468
16.6.3 Public Safety Applications 468
16.6.4 CRNs and LTE 469
16.7 Summary 470
Acknowledgements 470
References 470
17 Antenna Design for Small Devices 473
Tim Brown
17.1 Antenna Fundamentals 474
17.1.1 Directivity, Efficiency and Gain 475
17.1.2 Impedance and Reflection Coefficient 476
17.2 Figures of Merit and their Impact on the Propagation Channel 477
17.2.1 Coupling and S-Parameters 477
17.2.2 Polarization 479
17.2.3 Mean Effective Gain 480
17.2.4 Channel Requirements for MIMO 482
17.2.5 Branch Power Ratio 482
17.2.6 Correlation 483
17.2.7 Multiplexing Efficiency 484
17.3 Challenges in Mobile Terminal Antenna Design 484
17.4 Multiple-Antenna Minaturization Techniques 485
17.4.1 Folded Antennas 486
17.4.2 Ferrite Antennas 487
17.4.3 Neutralization Line 488
17.4.4 Laptop Antennas 489
17.5 Multiple Antennas with Multiple Bands 489
17.6 Multiple Users and Antenna Effects 491
17.7 Small Cell Antennas 492
17.8 Summary 492
References 492
18 Statistical Characterization of Antennas in BANs 495
Carla Oliveira, Michal Mackowiak and Luis M. Correia
18.1 Motivation 495
18.2 Scenarios 496
18.3 Concepts 498
18.4 Body Coupling: Theoretical Models 500
18.4.1 Elementary Source Over a Circular Cylinder 500
18.4.2 Elementary Source Over an Elliptical Cylinder 505
18.5 Body Coupling: Full Wave Simulations 508
18.5.1 Radiation Pattern Statistics for a Static Body 508
18.5.2 Radiation Pattern Statistics for a Dynamic Body 511
18.6 Body Coupling: Practical Experiments 513
18.7 Correlation Analysis for BANs 517
18.7.1 On-Body Communications 517
18.7.2 Off-Body Communications 520
18.8 Summary 522
Acknowledgements 523
References 523
Index 525
Dr. Guillaume de la Roche, University of Bedfordshire, UK
Guillaume de la Roche received the Dipl.-Ing. in telecommunication from the School of Chemistry Physics and Electronics (CPE) Lyon, France, an M.S. degree in signal processing (2003) and a Ph.D. degree in wireless communication (2007) from the National Institute of Applied Sciences (INSA), Lyon, France.
Guillaume de la Roche received the Dipl.-Ing. in telecommunication from the School of Chemistry Physics and Electronics (CPE) Lyon, France, an M.S. degree in signal processing (2003) and a Ph.D. degree in wireless communication (2007) from the National Institute of Applied Sciences (INSA), Lyon, France.
Dr. Andres Alayon-Glazunov, KTH - Royal Institute of Technology, Sweden
Andres Alayon-Glazunov obtained the M.Sc. (Engineer-Researcher) degree in Physical Engineering from Saint Petersburg’s State Polytechnical University, Russia, and the Ph.D. degree in Electrical Engineering from Lund University, Sweden, during 1988-1994 and 2006-2009, respectively.
Prof. Ben Allen, University of Bedfordshire, UK
Ben Allen received his PhD from the University of Bristol in 2001. In 2002 he joined Tait Electronics Ltd, Christchurch, New Zealand, before becoming a Research Fellow with the Centre for Telecommunications Research, King's College London.
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