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Radio-Frequency Human Exposure Assessment: From Deterministic to Stochastic Methods

Radio-Frequency Human Exposure Assessment: From Deterministic to Stochastic Methods

Joe Wiart

ISBN: 978-1-119-28513-7

Mar 2016

196 pages



Nowadays approximately 6 billion people use a mobile phone and they now take a central position within our daily lives. The 1990s saw a tremendous increase in the use of wireless systems and the democratization of this means of communication.

To allow the communication of millions of phones, computers and, more recently, tablets to be connected, millions of access points and base station antennas have been extensively deployed. Small cells and the Internet of Things with the billions of connected objects will reinforce this trend.

This growing use of wireless communications has been accompanied by a perception of risk to the public from exposure to radio frequency (RF) electromagnetic field (EMF). To address this concern, biomedical research has been conducted. It has also been important to develop and improve dosimetry methods and protocols that could be used to evaluate EMF exposure and check compliance with health limits. To achieve this, much effort has was made in the 1990s and 2000s. Experimental and numerical methods, including statistical methods, have been developed.

This book provides an overview and description of the basic and advanced methods that have been developed for human RF exposure assessment. It covers experimental, numerical, deterministic and stochastic methods.

Preface vii

Chapter 1. Human RF Exposure and Communication Systems 1

1.1 Introduction 1

1.2 Metric and limits relative to human exposure 3

1.3 European standards and regulation framework 36

1.4 Conclusion 39

Chapter 2. Computational Electromagnetics Applied to Human Exposure Assessment 41

2.1 Introduction 41

2.2 Finite difference in time domain to solve the Maxwell equations 42

2.3 FDTD and human exposure assessment 71

2.4 RF exposure assessment 103

2.5 Conclusion 117

Chapter 3. Stochastic Dosimetry 119

3.1 Motivations 119

3.2 The challenge of variability for numerical dosimetry 120

3.3 Stochastic dosimetry and polynomial chaos expansion 122

3.4 PC and numerical dosimetry 125

3.5 Calculation of the PC coefficients 131

3.6 Design of experiments 135

3.7 Predictive model validation 140

3.8 Surrogate modeling for dosimetry 142

3.9 SA and signature of the PC 150

3.10 Parsimonious quintile estimation 155

3.11 Conclusion 155

Conclusion 157

Bibliography 159

Index 179