Performance Evaluation of WiGig in an indoor Off-Body Communication

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60 GHz Wireless Communications

In the past years, millimeter wave (mm-wave) technology has mainly been used for military applications. However, with the progress in manufacturing and in low-cost integration solutions, a great deal of work has been done towards mm-wave communications for commercial applications [7]. More particularly, the recent breakthrough in silicon-based complementary metal-oxide semiconductor (CMOS) processes and the gate length of transistors reaching sizes below 50 nm allow the development of highly integrated transmitters and receivers [8]. One of the main advantage is the huge unlicensed bandwidth (up to 7 GHz) allocated in 2001 by the Federal Communications Commission (FCC). A summary of the most recent global regulatory results is  presented in Table 1.1.

The Saleh-Valenzuela Impulse Response

Wideband systems implies frequency-dependent channel. The description of the channel is usually done in the delay-domain by considering an impulse response made up several propagation paths. The Saleh- Valenzuela impulse response model is the most commonly used. An example of measured and schematic impulse response is shown in Fig. 2.1. Discrete time models are based on the channel impulse response: h() = XN k=1 k( − k) (2.2).
where k is the complex amplitude on path k, is the excess delay, k is the delay of path k, N is the number of multipath components (MPCs) and (·) stands for the Dirac function. The Saleh-Valenzuela channel model goes further by describing each path by a cluster which is made of several multipath components. (2.2) is then modified as: h() = XC i=0 XLi j=0 i,j( − Ti − i,j).

Electric Properties of human body tissues

The human body is considered as a highly heterogeneous and irregular medium from an electromagnetic point of view. The body is made up several layers of skin, muscle, blood, … and each layer possesses its own  electrical properties. This creates complex electric field distributions at the tissue scale. However, in this thesis, only effects of electromagnetic fields around the human body are of interest and not inside it.
Biological tissues are mathematically described by lossy dielectric media. Such media are described by their complex permittivity  » which depends on the angular frequency !: « (!) = « 0(!) − j (!) ! (2.9).
where is the conductivity and « 0 is the real part of permittivity. It is important to notice that the magnetic permeability of tissues is equal to the permeability of free space μ0. [3] references the electric properties of most of the human tissues for frequencies ranging from 10 Hz to 100 GHz. The real part of the permittivity and the conductivity of the human skin are presented over the V-band (from 50 to 75 GHz) in Fig. 2.3.

Propagation Models and Results

Since human blockage has been identified as one of the most critical aspect of 60 GHz indoor communications [56], several groups have been focused on it in order to be taken into account in the IEEE 802.11ad standard. In [57], a combination of a random walk model and knife edge diffraction has been intended to describe human movements.
This has been used in order to provide probability of blockage of clusters which can be easily implemented in the standard. In [58], measurements have been conducted in an indoor environment aiming to determine the maximum attenuation caused by human blockage. It has been shown that losses with and without body blockage can exceed 40 dB. Further, in [59], link blockage probability has been assessed for a ceiling-mounted transmitter. As expected, it has been shown that the blockage probability of the line-of-sight increase when bodies move towards the receiver and when human density increases. The channel capacity has been assessed accordingly. More recently, cylindrical models of the human body have been proposed and studied in [60]. It is shown that the human body can be approximated by a PEC cylinder and no significant difference has been observed between circular and elliptic cylinders. Simulations have shown a Doppler shift due to human activity which has been easily suppressed using directive antennas.

Elevation Angle Measurement Campaign

This experimental campaign has been conducted with the same experimental set-up as the previous one. Three values of i have been chosen:  25°, 55°and 90°. The measurements have been performed for both polarizations for three values of elevation angle. Time gating has been performed to increase the dynamic range. It was centered on the predicted time of arrival of the creeping wave. The results in Fig. 3.13 show that the analytical creeping wave models (3.18) and (3.26) fit the measurements.
As can be seen, the TE mode has a higher dynamic range and, consequently, measurements are obtained up to higher values of .

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Real Human Measurement Campaign

The second set of experiments was conducted on a real human body. The human body is compared with a dielectric (« 0 r = 7.9753 and = 36.397 S/m [3]) cylinder having with the same perimeter.

Indoor Off-Body Channel model

In an off-body scenario, each ray in (3.1)-(3.2) is perturbed by the presence of the human body near the receiver. In order to extend the model to an off-body scenario, the idea is to convert each ray in (3.1)-(3.2) into a wave diffracted by a circular cylinder with a radius a and an antenna located at (, 0) position.
The proposed model allows one to study a variety of parameters for an off-body communication. First, it permits to study the effect of the environment on the received power, the orientation of the user with respect to the transmit antenna and the polarization of the transmitted waves. Since the model is ray based, the effect of the antennas can be easily taken into account by introducing radiation patterns. Indeed, by measuring or simulating with commercial software the radiation pattern of the receive antenna located close to the body, it allows one to conduct more accurate simulations. In the following, the antennas will be assumed to be isotropic and omni-directional. The aim of this model is to give quick and averaged quantities for a specific scenario. It is not claimed to be a high accuracy model. Indeed, the circular cylinder model has been widely used in the field of BANs but it is a simplified shape. It does not permit to change the posture of the body or to move some parts of it. Also, it is shown above that the creeping wave formula on the cylinder shows a maximum 3 dB error on the received power on a real human torso. Another limitation of the model is the simple reflection created in the lit region. The factof having a more complex body shape (roughness, irregularities, body parts,…) would probably generate a reflected cluster instead of a wave.
This can be evaluated through extensive measurement but it is not the scope of this chapter. The validity of this model is related to the chosen indoor channel model. In fact, the diffraction model is valid over a large frequency range while the indoor channel model is based on measurements conducted on the frequency range from 55 to 65 GHz which limits the frequency range of the model proposed in the section.

Table of contents :

Abstract
List of Figures
List of Tables
Acronyms
1 Context 
1.1 Wireless Body Environment Networks
1.2 60 GHz Wireless Communications
1.3 Thesis Contribution and Outline
2 Body Area Networks Channel Modeling 
2.1 Body Area Channels
2.1.1 The radio channel
2.1.2 The Saleh-Valenzuela Impulse Response
2.1.3 On-Body Channels
2.1.4 Off-Body Channels
2.2 60 GHz Body Area Networks
2.2.1 Electric Properties of human body tissues
2.2.2 Propagation Models and Results
2.3 Conclusion
3 Off-Body Propagation and Communication 
3.1 Objectives and Scenario definition
3.2 Propagation Model assessment
3.2.1 Analytical model
3.2.2 Numerical results
3.2.3 Experimental Results
3.3 Indoor Off-Body Channel model
3.3.1 Model Generation
3.3.2 Channel Simulations
3.3.3 Experimental Assessment
3.4 Performance Evaluation of WiGig in an indoor Off-Body Communication
3.4.1 Simulation Results
3.4.2 Spatial and Polarization Diversity
3.5 Summary
4 On-body channel characterization 
4.1 On Torso Propagation
4.1.1 Flat Body Propagation model
4.1.2 Simulation Results
4.1.3 Experimental validation
4.1.4 On-Torso Path Loss
4.2 Around Torso Propagation
4.2.1 Introduction
4.2.2 Cylindrical Body model
4.2.3 Simulation Results
4.2.4 Path Gain
4.2.5 Measurements
4.2.6 Velocity of Creeping Waves
4.3 Millington Effect for Propagation enhancement
4.3.1 Objective
4.3.2 Analytical Model
4.3.3 Experimental Results
4.3.4 Numerical Study and Discussion
4.4 Summary
5 Near-Body Propagation 
5.1 Introduction
5.2 Indoor Near Body Channel Implementation
5.2.1 Geometry and Spatial Regions
5.2.2 Diffraction Model
5.2.3 Indoor Channel Implementation
5.3 Mean Attenuation
5.3.1 Front Region Distribution
5.3.2 Back Region Distribution
Contents vii
5.4 Experimental Comparison
5.5 Summary
6 Conclusion 
Bibliography 

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