Integrated Wireless Propagation Models
[BOOK DESCRIPTION]
This is fully integrated solutions for managing wireless network coverage, capacity, and costs. Cowritten by Dr. William C. Y. Lee, one of the original pioneers of wireless technology at Bell Labs, this in-depth guide presents accurate, efficient propagation prediction models to meet the growing demands of next-generation wireless networks. All relevant factors, including terrain, atmospheric conditions, buildings, antenna height, indoor environments, and more, are considered. Integrated Wireless Propagation Models discusses popular prediction models and provides complete details on the Lee macrocell, microcell, and in-building models. The final chapter ties the three Lee models together to produce an integrated Lee model that can be applied to all mobile environments. Throughout the book, complex mathematical models are translated into practical, easy-to-implement solutions.Coverage includes: introduction to modeling mobile signals in wireless communications; Macrocell prediction models - area-to-area and point-to-point models; Microcell prediction models for both empirical and deterministic methods; in-building (picocell) prediction models; integrating the three Lee models into the Lee comprehensive model.
[TABLE OF CONTENTS]
Preface xiii
Acknowledgments xvii
1 Introduction to Modeling Mobile Signals in 1 (50)
Wireless Communications
1.1 Why Write This Book? 1 (1)
1.2 Differences Between Free Space 1 (1)
Communications and Mobile Communications in
Propagation
1.3 Treatment of Mobile Signals 2 (1)
1.4 History of Developing the Lee Model 2 (1)
1.5 Basic System Operations 3 (1)
1.6 Mobile Radio Signal: Fading Signal 4 (10)
1.6.1 Conditions of Mobile Signal Reception 4 (1)
1.6.2 Types of Signal Fading 5 (1)
1.6.3 Attributes of Signal Fading 6 (5)
1.6.4 Flat Fading 11 (1)
1.6.5 Signal Fading Caused by Time-Delay 12 (1)
Spread: Frequency-Selective Fading
1.6.6 Fading Signal Caused by Doppler Spread 13 (1)
1.6.7 Short-Term and Long-Term Fading Signal 14 (1)
1.7 Co-Channel Interference Created from the 14 (8)
Frequency Reuse Scheme
1.7.1 Basic Concepts 14 (3)
1.7.2 Simulation Model 17 (1)
1.7.3 Simulation Result 18 (4)
1.8 Propagation Fading Models 22 (6)
1.8.1 Rayleigh Fading Model-Short-Term 22 (1)
Fading Model
1.8.2 Log-Normal Fading Model-Long-Term 23 (1)
Fading Model
1.8.3 Estimating Unbiased Average Noise 24 (3)
Level
1.8.4 Rician Distribution 27 (1)
1.9 Three Basic Propagation Mechanisms 28 (14)
1.9.1 Reflection 28 (6)
1.9.2 Diffraction 34 (8)
1.9.3 Scattering 42 (1)
1.10 Applications of the Prediction Models 42 (4)
1.10.1 Classification of Prediction Models 42 (1)
1.10.2 Prediction Models for Propagating in 43 (1)
Areas of Different Sizes
1.10.3 Aspects for Predicting the Signal 43 (2)
Strengths in a General Environment
1.10.4 Predicting the Interference Signals 45 (1)
1.11 Summary 46 (1)
References 46 (2)
Additional References 48 (3)
2 Macrocell Prediction Models-Part 1: 51 (48)
Area-to-Area Models
2.1 Free Space Loss 51 (1)
2.2 Plane Earth Model 52 (1)
2.3 Young Model 53 (2)
2.4 Bullington Monograms 55 (3)
2.4.1 Fading, Refraction from Tropospheric 56 (1)
Transmission, and Diffraction
2.4.2 Effects of Buildings and Trees 57 (1)
2.5 Egli Model-One of the Clutter Factor 58 (2)
Models
2.6 The JRC Method 60 (1)
2.7 Terrain-Integrated Rough-Earth Model 61 (4)
2.7.1 Description of TIREM 61 (1)
2.7.2 Summary of Land Propagation Formulas 62 (3)
2.8 Carey Model 65 (1)
2.9 CCIR Model 66 (2)
2.9.1 Description of the Model 66 (2)
2.10 Blomquist-Ladell and Edwards-Durkin 68 (2)
Models
2.11 Ibrahim-Parsons Model 70 (5)
2.11.1 Findings from the Empirical Data 70 (3)
2.11.2 Two Proposed Models 73 (2)
2.12 Okumara-Hata and the Cost 231 Hata Models 75 (6)
2.12.1 Okumura Method Hata Model 75 (5)
2.12.2 Cost 231 Hata Model 80 (1)
2.13 Walfisch-Bertoni Model 81 (2)
2.14 Ikegami Model 83 (1)
2.15 Walfisch-Ikegami Model 84 (3)
2.16 Flat-Edge Model 87 (2)
2.17 ITU Model 89 (5)
2.17.1 ITU-R Recommendation P.1546 90 (2)
2.17.2 Recommendation ITU-R P.530-9 92 (2)
2.18 On-Body Model 94 (1)
2.18.1 Model 1 94 (1)
2.18.2 Model 2 94 (1)
2.19 Summary 95 (1)
References 95 (4)
3 Macrocell Prediction Models-Part 2: 99 (88)
Point-to-Point Models
3.1 The Lee Model 99 (58)
3.1.1 Implementation of the Lee Macrocell 100 (1)
Model
3.1.2 The Lee Single Breakpoint Model: A 101 (15)
Point-to-Point Model
3.1.3 Variations of the Lee Model 116 (3)
3.1.4 Effects of Terrain Elevation on the 119 (3)
Signal Strength Prediction
3.1.5 Effects of Morphology on the Signal 122 (9)
Strength Prediction
3.1.6 Water Enhancement 131 (7)
3.1.7 Effect of Antenna Orientation 138 (17)
3.1.8 Prediction Data Files 155 (2)
3.2 Fine-Tuning the Lee Model 157 (12)
3.2.1 The Terrain Normalization Method 158 (1)
3.2.2 Measurement Data Characteristics 159 (1)
3.2.3 Comparison of Measured and Predicted 160 (1)
Curve for the Nonobstructive Case
3.2.4 Comparison of Measured and Predicted 161 (7)
Curves for the Obstructive Paths
3.2.5 Conclusion 168 (1)
3.3 Enhanced Lee Macrocell Prediction Model 169 (6)
3.3.1 Introduction 169 (1)
3.3.2 The Algorithm 169 (1)
3.3.3 Measured versus Predicted Data 170 (4)
3.3.4 Conclusion 174 (1)
3.4 Longley-Rice Model 175 (3)
3.4.1 Point-to-Point Model Prediction 175 (1)
3.4.2 Area Model Prediction 175 (3)
3.5 Summary 178 (5)
3.5.1 Ways of Implementation of Models 181 (1)
3.5.2 Features Among Models 181 (2)
References 183 (4)
4 Microcell Prediction Models 187 (74)
4.1 Introduction 187 (1)
4.2 The Basic Lee Microcell Prediction Model 188 (35)
4.2.1 Basic Principle and Algorithm 188 (11)
4.2.2 Input Data for Microcell Prediction 199 (6)
4.2.3 The Effect of Buildings on Microcell 205 (2)
Prediction
4.2.4 The Terrain Effect 207 (3)
4.2.5 Prediction Model with Four Situations 210 (2)
4.2.6 Characteristics of the Measured Data 212 (2)
4.2.7 Validation of the Model: Measured 214 (5)
versus Predicted
4.2.8 Integrating Other Attributes into the 219 (4)
Model
4.3 Integration of the Microcell Prediction 223 (9)
Model and the Macrocell Prediction Model
4.3.1 The Algorithms for Integrating the 224 (2)
Two Models
4.3.2 Treatment of Measured Data 226 (4)
4.3.3 Validation of the Model: Measured 230 (2)
versus Predicted
4.4 Tuning the Model for a Particular Area 232 (6)
4.4.1 Before Tuning the Lee Microcell Model 232 (1)
4.4.2 The Tuning Algorithm of the Lee Model 233 (3)
4.4.3 Verification of the Lee Model 236 (2)
4.5 Other Microcell Prediction Models 238 (17)
4.5.1 Introduction 238 (1)
4.5.2 Empirical (Path Loss) Models 238 (4)
4.5.3 Physical Models 242 (3)
4.5.4 Non-LOS Model 245 (3)
4.5.5 ITU-R P.1411 Model 248 (7)
4.6 Summary 255 (2)
References 257 (4)
5 In-Building (Picocell) Prediction Models 261 (80)
5.1 Introduction 261 (2)
5.1.1 Differences from Other Models 261 (1)
5.1.2 Propagation Impairments and Measure 262 (1)
of Quality in Indoor Radio Systems
5.1.3 The Highlights of the Lee In-Building 262 (1)
Model
5.2 The Lee In-Building Prediction Model 263 (27)
5.2.1 Derivation of Close-In Distance for 263 (6)
the In-Building Model
5.2.2 The Single-Floor (Same Floor) Model 269 (5)
5.2.3 Determining Path-Loss Slope in a Room 274 (1)
5.2.4 Applications of the Lee Model 275 (1)
5.2.5 Characteristics of the Measured Data 275 (2)
5.2.6 Validation of the Model (Measured 277 (2)
versus Predicted)
5.2.7 Balance Between Coverage and 279 (1)
Interference
5.2.8 Analyzing the Lee In-Building 280 (10)
Prediction Model
5.3 Enhanced Lee In-Building Model 290 (29)
5.3.1 Highlight of the Enhanced Lee Model 291 (1)
5.3.2 Studying Measured Data in various 291 (11)
Cases
5.3.3 Comparison of Measured Data and 302 (7)
Predicted Data
5.3.4 Using Measured Data to Customize the 309 (9)
Lee Model
5.3.5 The General Formula of the Enhanced 318 (1)
Lee In-Building Model
5.4 Empirical Path-Loss Models 319 (6)
5.4.1 The Motley-Keenan Model (Empirical) 320 (3)
and a Comparison with the Lee Model
5.4.2 Ericsson Multiple-Breakpoint Model 323 (2)
(Empirical)
5.5 ITU Model 325 (3)
5.5.1 COST 231 Multiwall Model (Empirical) 325 (1)
5.5.2 ITU-R 1238 (Empirical) 326 (2)
5.6 Physical Models-Application of 328 (7)
Geometrical Theory of Diffraction (GTD)
5.6.1 Ray-Tracing Model for In-Building 328 (3)
(Picocell)
5.6.2 FDTD 331 (4)
5.7 Summary and Conclusions 335 (1)
References 336 (5)
6 The Lee Comprehensive Model-Integration of 341 (58)
the Three Lee Models
6.1 Introduction 341 (1)
6.2 Integrating the Three Lee Models 342 (3)
6.2.1 Validation of the Macrocell Model 343 (2)
6.2.2 Validation of the Microcell Model 345 (1)
6.2.3 Validation of the In-Building Model 345 (1)
(Picocell Model)
6.3 System Design Aspects Using Different 345 (19)
Prediction Models
6.3.1 Preparing to Design a System 345 (1)
6.3.2 Design Parameters and Input Data 346 (1)
6.3.3 System Coverage in General 347 (1)
6.3.4 CDMA Coverage 347 (5)
6.3.5 System Design in Special Areas with 352 (12)
New Technologies
6.4 User's Menu of the Lee Comprehensive Model 364 (11)
6.4.1 The Overall System Design Chart from 364 (2)
the Lee Comprehensive Model
6.4.2 In-Building Cell-Point-by-Point 366 (4)
Analysis for the Lee In-Building Model
6.4.3 Microcell-Point-by-Point Analysis for 370 (2)
the Lee Microcell Model
6.4.4 Macrocell-Point-by-Point Analysis for 372 (3)
the Lee Macrocell Model
6.5 How to Use Prediction Tools 375 (6)
6.5.1 Radio Communication Link-The Channel 376 (1)
6.5.2 Types of Noise, Losses, and Gain 376 (1)
6.5.3 Received Signal Power and Noise Power 377 (2)
6.5.4 Required Information for Calculating 379 (1)
Link Budget
6.5.5 Link Budget Analysis 379 (2)
6.6 How to Plan and Design a Good Wireless 381 (2)
System
6.6.1 Understanding the System Requirement 381 (1)
6.6.2 Choosing the Right Prediction Model 381 (2)
6.7 Propagation Prediction on Different 383 (10)
Transmission Media
6.7.1 Prediction of Satellite Communication 383 (3)
Signals
6.7.2 Prediction of Underwater 386 (2)
Communication Signals
6.7.3 Prediction of Aeronautical 388 (4)
Communication Signal
6.7.4 Prediction of Bullet Train 392 (1)
Communication Signal
6.7.5 Millimeter Wave Signal 392 (1)
6.8 Summary and Conclusions 393 (2)
References 395 (4)
Index 399
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