1. health and fitness
2. weight loss

LiU-ITN-TEK-G--15/033--SE
Indoor propagation modelling
at microwave frequencies in a
server environment
Andreas Joelsson
Jonathan Ohlsson
2015-06-11
Department of Science and Technology
Linköping University
SE- 6 0 1 7 4 No r r köping , Sw ed en
Institutionen för teknik och naturvetenskap
Linköpings universitet
6 0 1 7 4 No r r köping
LiU-ITN-TEK-G--15/033--SE
Indoor propagation modelling
at microwave frequencies in a
server environment
Examensarbete utfört i Elektroteknik
vid Tekniska högskolan vid
Linköpings universitet
Andreas Joelsson
Jonathan Ohlsson
Handledare Adriana Serban
Examinator Magnus Karlsson
Norrköping 2015-06-11
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© Andreas Joelsson, Jonathan Ohlsson
Abstract
The Linköping site is the first of Ericsson’s three information and communication technology centres. This facility will house the company’s complete portfolio and use the
latest cloud technology in order to enable the research and development engineers to
more efficiently test and develop new technologies. In the test lab environment there is
a high capacity microwave telecommunication system called MINI-LINK. These systems
operate at much higher frequencies than more traditional telecommunication systems.
In the test lab these systems are communicating with a cable interface instead of its
intended air interface. The purpose of this thesis is to evaluate the potential leakage of
this system in the test lab environment.
The evaluation of the leakage in the test lab is done by developing an empirical path
loss model for the desired frequencies used by the equipment in the test lab. This model
is later implemented in a leakage simulation tool designed in Matlab, which simulates
and displays the leakage power in a 2D plane. This report mainly focuses on the process
of determining the constants and the implementation of the path loss model.
Acknowledgements
We would like to thank Ericsson for providing the opportunity to make this project with
them. We would also like to thank our supervisors and others involved by providing
support and feedback along the way.
Contents
1 Introduction
1.1 Background . . . . . . . . . . . . . . . . .
1.1.1 Cellular Networks and MINI-LINK
1.2 Limitations . . . . . . . . . . . . . . . . .
1.3 Requirements . . . . . . . . . . . . . . . .
1.3.1 Pre-study Requirements . . . . . .
1.3.2 Model Requirements . . . . . . . .
1.3.3 Measurement Requirements . . . .
1.3.4 Project Requirements . . . . . . . .
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2 Theoretical Background
2.1 Path Loss . . . . . . . . . . . . . . . . . . . .
2.1.1 Free-space Path Loss . . . . . . . . . .
2.1.2 Simplified Path Loss Model . . . . . .
2.1.3 Empirical Path Loss Models . . . . . .
2.2 Environmental Factors on Radio Propagation
2.2.1 Multipath Propagation . . . . . . . . .
2.2.2 Fading . . . . . . . . . . . . . . . . . .
2.3 Indoor Propagation . . . . . . . . . . . . . . .
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3 Model Development
3.1 Model Selection . . . . . . . . . . . . . . . . . .
3.1.1 Comparison of Models . . . . . . . . . .
3.1.2 Initial Model . . . . . . . . . . . . . . .
3.2 Measurement Equipment . . . . . . . . . . . . .
3.2.1 Interface Loss Characterization . . . . .
3.2.2 SMA Antenna Characterization . . . . .
3.2.3 Equipment Parameters . . . . . . . . . .
3.3 Path Loss Exponent . . . . . . . . . . . . . . .
3.3.1 Path Loss Exponent Measurements . . .
3.4 Rack Attenuation Factor . . . . . . . . . . . . .
3.4.1 Rack Attenuation Factor Measurements
3.4.2 Solid Object Attenuation . . . . . . . . .
3.5 Proposed Model . . . . . . . . . . . . . . . . . .
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June 25, 2015
CONTENTS
4 Model Verification and Correction
4.1 Verification Measurements . . . . . . . . . .
4.1.1 Measurement Setup . . . . . . . . . .
4.1.2 Model Deviation . . . . . . . . . . .
4.2 Model Correction . . . . . . . . . . . . . . .
4.2.1 Path Loss Exponent Correction . . .
4.2.2 Rack Attenuation Factor Correction .
4.2.3 Deviation after Model Correction . .
5 Results
5.1 Final Model . . . . . . . . . . . . . . . . .
5.2 Leakage Simulations . . . . . . . . . . . .
5.2.1 Maximum Allowed Radiated Power
5.2.2 Leakage from MINI-LINK Setup . .
5.2.3 Model Simulations . . . . . . . . .
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6 Discussion and Conclusion
6.1 General Discussion . . . . . . . . . . . . . . .
6.2 Requirement Evaluation . . . . . . . . . . . .
6.2.1 Pre-study Requirement Evaluation . .
6.2.2 Model Requirement Evaluation . . . .
6.2.3 Measurement Requirement Evaluation
6.2.4 Project Requirement Evaluation . . . .
6.3 Conclusion . . . . . . . . . . . . . . . . . . . .
6.4 Future Work . . . . . . . . . . . . . . . . . . .
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Appendices
A Plotted Measured Data
A.1 Open Space Plot for 23.0 GHz . . . .
A.2 Open Space Plot for 18.0 GHz . . . .
A.3 Rack Environment Plot for 23.0 GHz
A.4 Rack Environment Plot for 18.0 GHz
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B Raw data
B.1 Path Loss Exponent Measurements . . .
B.2 Verification Data Measurements . . . . .
B.3 RAF measurements . . . . . . . . . . . .
B.4 Solid Object Attenuation Measurements
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C Leakage Simulation Tool: User Guide
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53
List of Figures
1.1
Illustration of cellular data forwarding . . . . . . . . . . . . . . . . . . .
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2.1
2.2
2.3
Free-space path loss . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Example of multipath components of transmitted signal . . . . . . . . . .
Illustration of destructive and constructive interference . . . . . . . . . .
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3.2
3.3
3.4
3.5
3.6
3.7
3.8
3.9
3.10
3.11
3.12
3.13
Comparison of path loss models . . . . . . . . . . . . . . . . . . . . . . .
Conversion connector loss characterization . . . . . . . . . . . . . . . . .
Loss characterization of Sucoflex 104 cable . . . . . . . . . . . . . . . . .
Characterization with reference antenna . . . . . . . . . . . . . . . . . .
Characterization with antenna under test . . . . . . . . . . . . . . . . . .
Measurement setup for determining the path loss exponent . . . . . . . .
Measured path loss for an open space environment at 23.0 GHz . . . . .
Measured path loss for an open space environment at 18.0 GHz . . . . .
Measurement setup for determining the rack attenuation factor . . . . . .
Line-of-Sight and Non-Line-of-Sight components in the RAF measurements
Measurement setup solid object attenuation seen from above . . . . . . .
Estimated path loss for open space at 23.0 GHz . . . . . . . . . . . . . .
Estimated path loss for open space at 18.0 GHz . . . . . . . . . . . . . .
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4.1
4.2
Verification measurement locations in the test lab environment . . . . . .
Deviating points . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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5.1
5.2
Single source simulation . . . . . . . . . . . . . . . . . . . . . . . . . . .
Multiple source simulation . . . . . . . . . . . . . . . . . . . . . . . . . .
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A.1
A.2
A.3
A.4
Measured
Measured
Measured
Measured
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C.1 Default layout of the leakage simulation tool . . . . . . . . . . . . . . . .
C.2 Simulation environment configuration in progress . . . . . . . . . . . . .
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data
data
data
data
for
for
for
for
open space at 23.0 GHz . . . .
open space at 18.0 GHz . . . .
rack environment at 23.0 GHz
rack environment at 18.0 GHz
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List of Tables
1.1
1.2
1.3
1.4
1.5
Definition of requirement priority
Pre-study requirements . . . . .
Model requirements . . . . . . .
Measurement requirements . . .
Project requirements . . . . . . .
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3.1
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3.3
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3.6
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3.11
Simulation parameters . . . . . . . . . . . . . . . . . . . . . . . . . .
Interface losses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Component properties at 23.0 GHz . . . . . . . . . . . . . . . . . . .
Component properties at 18.0 GHz . . . . . . . . . . . . . . . . . . .
Path loss exponents in different scenarios at 23.0 GHz . . . . . . . .
Path loss exponents in different scenarios at 18.0 GHz . . . . . . . .
Definition of rack densities . . . . . . . . . . . . . . . . . . . . . . .
Rack attenuation factor for different rack densities at 23.0 GHz . . .
Rack attenuation factor for different rack densities at 18.0 GHz . . .
Solid object attenuation for different separation distances at 23.0 GHz
Solid object attenuation for different separation distances at 18.0 GHz
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4.2
4.3
4.4
4.5
4.6
Deviation of the LOS components . . . . . .
Deviation of the NLOS components . . . . .
K for 23.0 GHz model . . . . . . . . . . . . .
K for 18.0 GHz model . . . . . . . . . . . . .
Corrected deviation of the LOS components .
Corrected deviation of the NLOS components
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5.1
Measured power of the leakage scenarios . . . . . . . . . . . . . . . . . .
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6.2
6.3
6.4
Analysis
Analysis
Analysis
Analysis
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Pre-study requirements . .
Model requirements . . . .
Measurement requirements
Project requirements . . .
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List of Abbreviations
AF
Antenna Factor
AUT
Antenna Under Test
EMC ElectroMagnetic Compatibility
EMI
ElectroMagnetic Interference
FAF
Floor Attenuation Factor
GSM Global System for Mobile communication
ICT
Information and Communication Technology
LOS
Line Of Sight
LTE
Long-Term Evolution
NLOS Non Line Of Sight
PCB
Printed Circuit Board
RAF
Rack Attenuation Factor
RF
Radio Frequency
Rx
Reception
Tx
Transmission
WAF Wall Attenuation Factor
Chapter 1
Introduction
In this chapter the background, limitations and requirements of the project will be presented.
1.1
Background
The Ericsson facility in Linköping is in the process of completing the construction of its
test lab, which is the first of three global test centers. Ericsson’s reason for collecting its
entire portfolio of products in three locations is to allow the engineers to develop and test
new solutions remotely, while Ericsson estimate that they will reduce their total energy
consumption of their test facilities with 40 %, with the aim for a more sustainable future.
[8]
Since the equipment in the test lab is operated remotely, the engineer using the
equipment in the lab need to know that it is working as intended. The test environment engineer are responsible of safely integrating new equipment and maintaining the
hardware in the test lab, in order to prevent potential problems.
Problems facing the test environment engineers when integrating new equipment is
generally concerning leakages from the equipment in the lab. Since a large portion of
the products in the Ericsson portfolio is designed to operate in an outdoor environment,
the RF leakages need to be characterized and controlled to be able to guarantee a fully
functional test environment. These leakages, if the signal strength is large enough, can
also provide a possible undesired access point to the system. The leakage can also pose
a health risk to the test lab employees if the emitted energy is too high.
Accurately modelling and evaluating potential problems in any leakage scenario is important when sensitive equipment is placed close to each other. This potential problem
is more relevant when outdoor equipment is placed in an indoor test environment, using
cables, connectors and waveguides instead of using the intended air interface. Knowledge on how to troubleshoot potential problems before they occur is critical knowledge
when maintaining a large amount of equipment. Knowledge about the possible leakage
scenarios and the ability to evaluate different equipment placement is a valuable asset
for engineers responsible for maintaining the system.
This project seeks to develop a tool for engineers to evaluate different leakage sce1
June 25, 2015
CHAPTER 1. INTRODUCTION
narios, leakage strength and its propagation characteristics in a server environment. The
tool will give engineers the ability to plan the placement of the equipment and increase
awareness where different leakage scenarios will potentially cause a problem.
1.1.1
Cellular Networks and MINI-LINK
To be able to transmit data from one remote location to another, a connection between
the two points are required. Since the devices may not be located in the same area, the
transmitted data will be forwarded via a microwave link and/or Ethernet/fiber in order
to connect the devices.
The increased demand for high data rates and availability of modern communication
systems requires high performance forwarding for nodes in the communication network.
The MINI-LINK system from Ericsson offers the possibility for high capacity transfer
when forwarding data between network nodes. This system allows technologies such
as 4G and LTE to be implemented in a cost efficient way, while preparing the wireless
network for future technologies. [10]
In the following subsections the procedure of connecting the wireless device to the
Internet will be explained. The forwarding procedure is illustrated in Figure 1.1.
Figure 1.1: Illustration of cellular data forwarding
Wireless Device to Base Station:
The transmitting device connects to a base station in the telecommunication network
using 4G or any other applicable technology. The data is sent from the transmitting
device and received by the base stations antenna. The data is collected and repackaged
from several devices connected to the same base station.
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June 25, 2015
CHAPTER 1. INTRODUCTION
Base Station to Base Station Controller:
The collected data from several connected wireless devices is sent via microwave transmission to the base station controller. The base station controller is responsible of collecting
transmissions from several base stations and repackaging the data.
Base Station Controller to Switching Center:
The data from several base stations are collected and repackaged. This data is forwarded
in the same way as between the base station and the base station controller, but may be
forwarded to a switching center. The switching center sends the data to its destination
using either Ethernet or optical fiber. [2]
1.2
Limitations
The main purpose of this project is to evaluate leakage power levels of the MINI-LINK
setup in the test environment at the Ericsson test lab in Linköping. When investigating
different leakage scenarios, a simulation model can be created to estimate leakage levels
in the environment. There are several ways to construct and implement a model to be
able to represent the specific scenario needed. The signal propagation can be modelled
either by a deterministic or an empirical approach.
A deterministic approach uses the description of the physical material in the modelling
environment. In order to get an accurate model, material parameters such as relative
permittivity, permeability and conductivity has to be specified for the environment. This
approach requires a huge amount of data to describe the modelling environment and a
huge computational effort to determine the loss contribution from the environment.
An empirical approach is based on measurements instead of physical properties of
the materials. This approach can generate models with less computational effort but
with the drawback of being limited to the environment and parameters used in the data
acquisition. [11]
Using this knowledge a model can be formed and appropriate measurements be executed to be able to verify the model. Since the model will be used to determine signal
levels for leakage evaluation, the level of accuracy needed does not warrant a deterministic model. An empirical modelling approach will be used to determine the signal levels
since it can be verified and used to evaluate the leakage in a shorter time frame.
In the list below the limitations of the project is summarized. Furthermore, the
requirements of the project is presented in section 1.3.
• The project duration is 20 weeks
• The model will be based on a empirical modelling method
• The quality and quantity of empirical data will lay the foundation of the model
• The model will only be verified for a maximum of two operating frequencies
• The model will only be verified in the Ericsson test lab in Linköping
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June 25, 2015
CHAPTER 1. INTRODUCTION
• The quality of the model will be determined with standard deviation calculation
compared to verification measurements
• The model will only be simulated in a 2D environment
1.3
Requirements
During the project certain criteria have to be met for the project. The requirements will
be presented and ranked on a priority scale as seen in Table 1.1.
Table 1.1: Definition of requirement priority
Priority
1
2
3
1.3.1
Description
Critical importance
High importance
Low importance
Pre-study Requirements
During the pre-study, knowledge will be acquired in order to fully understand the problem. This knowledge will be used to derive and implement an empirical model. The
requirements for the pre-study can be seen in Table 1.2.
Table 1.2: Pre-study requirements
No.
1
2
3
4
5
Description
Appropriate knowledge about signal leakage
Appropriate knowledge of current EMC standards
Evaluation of indoor propagation models & methods
Measurement techniques at microwave frequencies
Appropriate knowledge of Matlab programming
Priority
1
2
1
1
1
4
June 25, 2015
1.3.2
CHAPTER 1. INTRODUCTION
Model Requirements
In order to create an appropriate tool that implements the simulation model, several
aspects of the model need to be considered. The requirements for the model can be seen
in Table 1.3.
Table 1.3: Model requirements
No.
6
7
8
9
10
11
12
13
14
1.3.3
Description
Model will be implemented in Matlab
Tuning of model parameters in different environments
Tuning of model parameters at appropriate frequencies
Environment mapping for simulation model
Multiple assignable leakage sources in model
Random variance consideration of model
Simulation will alert if signal level will cause potential security risk
Simulation will alert if signal level is above recommended levels
Simulation implementation will have a graphical interface
Priority
1
1
1
1
1
3
2
2
2
Measurement Requirements
A series of measurements need to be performed during the project in order to be able to
implement the empirical simulation model. The requirements for the measurements can
be seen in Table 1.4.
Table 1.4: Measurement requirements
No.
15
16
17
18
1.3.4
Description
Measurements will be performed with appropriate equipment
Orientation of measurement and equipment will be considered
Height of measurement will be considered
Multiple frequencies will be measured
Priority
1
1
2
2
Project Requirements
A number of documents, meetings and presentations will be performed during the project.
The requirements for the project can be seen in Table 1.5.
Table 1.5: Project requirements
No.
19
20
21
22
Description
Deliver a written report at the end of the project
Weekly meetings with supervisor at Ericsson
Monthly written report to supervisor at Ericsson
Present the project at Ericsson and LiU
Priority
1
1
1
1
5
Chapter 2
Theoretical Background
In this chapter, the theoretical background of the project will be presented. The theory
will be used in order to understand and implement the requirements of the project.
2.1
Path Loss
The path loss of a transmitted signal is the energy reduction of the propagating electromagnetic wave. Understanding and accurately modelling the path loss of a propagating
wave is important to be able to plan and evaluate the range of communications systems.
This project uses path loss modelling to determine the leakage power at a certain distance
from the source.
2.1.1
Free-space Path Loss
The simplest way to model path loss is where only the free-space path loss is taken
into account. The free-space path loss model does not consider the environment it is
propagating in, since the model is based on waves propagating in free-space. The freespace path loss is usually used as a starting point when forming a path loss model when
only the line-of-sight component is required. The free-space path loss can be seen in (2.1)
and (2.2).
PL (d) =
λ2
(4πd)2
PL (d) dB = 20 log10 (d) + 20 log10 (f ) − 27.55
(2.1)
(2.2)
where λ is the wavelength of the carrier frequency in meters, f is the carrier frequency
in MHz and d is the distance in meter between the transmitter and receiver [1]. A plot
of the free-space path loss for a source with an operational frequency of 23.0 GHz can be
seen in Figure 2.1.
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June 25, 2015
CHAPTER 2. THEORETICAL BACKGROUND
Figure 2.1: Free-space path loss
2.1.2
Simplified Path Loss Model
Modelling path loss in complex environments, such as dense urban areas, offices or other
indoor environments, requires a adjustable model for accurate path loss modelling. The
simplified path loss model uses adjustable factors which can be obtained with both empirical and deterministic modelling methods. This gives the simplified path loss model a
wide range of applicable scenarios. The simplified path loss model is shown in (2.3).
d
λ
+ 10γ log10
+ ψdB
(2.3)
PL (d) dB = −20 log10
4πd0
d0
where λ is the wavelength of the carrier frequency, d0 is the reference distance for the
model in meters, γ is the path loss exponent tuned for a specific environment and ψdB is
a Gaussian distributed random variable. This variable is used to describe the variance of
the model caused by environmental effects. These variations will be explained in section
2.2. The reference distance d0 is typically set to 1 m for indoor environments, and γ is
typically in the range of 1.6 to 3 for an indoor environment. [2]
2.1.3
Empirical Path Loss Models
Accurately modelling path loss in complex environments requires more than only freespace path loss. There are several path loss models based on empirical data collected for
specific model parameters such as frequency and environment. In this section, a selection
of these models are presented.
7
June 25, 2015
CHAPTER 2. THEORETICAL BACKGROUND
Hata model
The Hata model is an empirical model typically used for estimating path loss in outdoor
urban environments. The Hata model is widely used since its able to model propagation
of modern cellular systems with smaller cell sizes and higher frequencies [2]. The Hata
model is described by (2.4).
PL,urban (d) dB = 69.55 + 26.16 log10 (fc ) − 13.82 log10 (ht )
−a(hr ) + 44.9 − 6.55 log10 (ht ) log10 (d)
(2.4)
where fc is the carrier frequency, ranging from 150 MHz to 1500 MHz, hr and ht are
the height of the receiving and transmitting antenna, ranging from 1-10 m for hr and
30-200 m for ht . The distance d ranges from 1 km to 100 km, a(hr ) is the correction
factor, which for small and medium sized cities is given by (2.5) and for larger cities given
by (2.6). [2]
a(hr ) dB = 1.1 log10 (fc ) − 0.7 hr − 1.56 log10 (fc ) − 0.8
(2.5)
a(hr ) dB = 3.2
log10 (11.75hr )
2
− 4.97
(2.6)
COST 231 extension to Hata model
Since the Hata model does not cover frequencies over 1.5 GHz, the European cooperative
for scientific and technical research extended the model to cover an higher range of
frequencies. The model is described by (2.7).
PL,urban (d) dB = 46.3 + 33.9 log10 (fc ) − 13.82 log10 (ht )
−a(hr ) + 44.9 − 6.55 log10 (ht ) log10 (d) + CM
(2.7)
where fc is the frequency, ranging from 1.5 GHz to 2 GHz, hr and ht are the height
of the receiving and transmitting antenna, ranging from 1-10 m for hr and 30-200 m for
ht . The distance d ranges from 1 to 10 km and a(hr ) is the correction factor as in the
Hata model, as seen in (2.5) and (2.6). CM is a correction factor for the model with the
value of 0 dB for medium dense cities and 3 dB for metropolitan areas. [2]
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June 25, 2015
CHAPTER 2. THEORETICAL BACKGROUND
COST 231 Multi Wall
The COST 231 Multi Wall path loss model provides a path loss estimation for indoor
environments and is applicable for frequencies between 900 MHz and 1800 MHz. Included
in the model is a linear attenuation factor for the number of walls in the propagating
path, as described by (2.8).
PL (d) dB = L0 + 10n log10 (d) + Lc +
W X
NW,i · WAFW,i
i=1
(2.8)
where L0 is the path loss in dB at 1 m for the modelled frequency, Lc is an empirically
derived constants depending on the environment in dB and n is the power decay index.
NW,i is the number of walls in the transmitting path and WAFW,i is the wall attenuation
factor. The WAF is typically set to 3.4 dB for light walls and 6.9 dB for heavy walls.
[4][13]
ITU-R path loss model
The radio section of the International Telecommunication Union, ITU-R, implements a
combination of average path loss and site specific data for estimating path loss. Included
in the model is floor attenuation to the transmitted signal. The basic ITU-R model is
described by (2.9).
PL (d) dB = 20 log10 (f ) + N log10 (d) + Lf (n) − 28
(2.9)
where f is the frequency in MHz, N is the power loss coefficient ranging from 22 to
33 in an office environment in the frequency range of 700 MHz to 70 GHz. The floor loss
factor, Lf , ranges from 9 dB at 900 MHz to 22 dB at 5.8 GHz for single floor loss. [12]
WINNER II model
In the WINNER II channel models, models for both indoor and outdoor environments
are derived. The model for indoor environments is described by (2.10) for the line-of-sight
component and (2.11) for the non-line-of-sight. [14]
f
PL,LOS (d) dB = 46.8 + 18.7 log10 (d) + 20 log10
5
f
PL,N LOS (d) dB = 46.4 + 18.7 log10 (d) + 20 log10
+ WAF · NW
5
(2.10)
(2.11)
where f is given in GHz between 2 and 6 GHz and d is the distance ranging from 3
to 100 m. WAF is the wall attenuation factor in dB and NW is the number of walls in
the propagating path.
9
June 25, 2015
2.2
CHAPTER 2. THEORETICAL BACKGROUND
Environmental Factors on Radio Propagation
An propagating electromagnetic wave may be subjected to several propagation effects,
such as reflection, diffraction, scattering and object attenuation. These aspects need to
be considered when developing propagation models. This section will look into these
factors.
2.2.1
Multipath Propagation
In urban and indoor environments, the signal has several additional paths of propagation
besides the line-of-sight component. Reflection of objects, diffraction and scattering
will affect the signal strength at the receiver. This phenomena is known as multipath
propagation. In Figure 2.2, the diffraction and reflection multipath components are
illustrated.
Figure 2.2: Example of multipath components of transmitted signal
The multipath propagation problems can be solved using Maxwell’s equations, but
the computational effort is generally to great for a practical implementation. Instead,
the electromagnetic waves are represented as simple particles, thus reducing the computational complexity needed. Diffraction, reflection and scattering problems are solved
with geometrical equations instead of solving the partial differential equations used in
Maxwell’s equations. [2]
2.2.2
Fading
Transmitted signals usually suffer from random variations in the signal level at the receiver. Shadow fading, or slow fading, is caused by reflection and scattering of objects in
the signal path. Generally, when considering shadow fading in outdoor and urban environments, the objects causing the fading are large and the shadowing effect is considered
constant over a given number of wavelengths. [7]
The most common model used is the log-normal shadowing model. It has been
empirically confirmed to accurately model variation in received power for indoor and
outdoor environments. When calculating the variance of the shadow fading, the difference
10
June 25, 2015
CHAPTER 2. THEORETICAL BACKGROUND
between the model and measured values at several distances is needed. The variance can
then be calculated using (2.12). For outdoor environments, σψdB is typically in the range
of 4 dB to 13 dB. [2]
σψ2 dB
2
N 1 X
Mmeasured (di ) − Mmodel (di )
=
N i=1
(2.12)
Fast fading variations behave in the same way as slow fading, but are generally caused
by minor variation closer to the receiving antenna due to multipath components from the
transmitter. The multipath components cause destructive or constructive interference,
as seen in Figure 2.3, affecting the received signal power, due to the relative phase of the
electromagnetic waves. For indoor environments, the fading can be considered to have
fast fading characteristics. [7]
Figure 2.3: Illustration of destructive and constructive interference
2.3
Indoor Propagation
When modelling path loss, free-space path loss is not sufficient to accurately model the
actual path loss in an indoor environment. The propagation environment is generally
more complex with object causing attenuation, reflections and diffractions of the transmitted electromagnetic waves.
For indoor propagation there are three major ways to model the propagating wave;
ray tracing, dominant path and direct path. Ray tracing is the most complex of the
methods, as it often uses a deterministic modelling approach. The ray tracing method
approximates the electromagnetic waves as rays to be able to determine the contribution
11
June 25, 2015
CHAPTER 2. THEORETICAL BACKGROUND
of each multipath component. Modelling path loss using ray tracing methods requires
more data and is more computationally demanding, but yields a more accurate result.
Direct path models are the most computational efficient, since the model only considers the direct path between the transmitter and receiver. Models using the direct
path method does not only consider free-space loss, but may also consider loss caused
by objects in the propagation path. Typically propagation through walls and floors is
considered in these models, as described by (2.13).
PL,total = PL (d) +
Nf
X
i=1
FAFi +
Nw
X
WAFi
(2.13)
i=1
where FAF is the floor attenuation factor, WAF is the wall attenuation factor and
PL (d) is the path loss from any given path loss model.
When analyzing different typical scenarios for propagation, it has been found that in
many cases there are one path of propagation that has the largest contribution to the
received signal strength. The dominant path models calculates the path loss contribution
for a series of propagation paths. The model then disregards all paths but the dominant
one. The dominant path models are less computational demanding than the ray tracing
models and are more accurate than the direct path models.
12
Chapter 3
Model Development
In this chapter, models described in section 2.1 will be compared. Then, an initial model
adapted to the project specifications will be presented.
3.1
Model Selection
In the requirements previously presented in section 1.3.2, the model needs to work at
specified frequencies. Since the main operational frequency of the MINI-LINK system
used in the test lab is 23 GHz, the model need to be able to handle this frequency. A
secondary frequency of 18 GHz was selected in order to extend the usage of the model.
18 GHz was selected since it is an operational frequency being used by some of the
MINI-LINK radio units in the test lab.
3.1.1
Comparison of Models
In order to be able to select a model to implement, a preliminary simulation of the models
in section 2.1 was performed. The parameters used for the simulations can be seen in
Table 3.1. The simulations have all been performed with a carrier frequency of 23 GHz.
Table 3.1: Simulation parameters
Model
Simplified Path loss model
ITU-R
Hata & COST 231 ext. to Hata
COST 231 Multi Wall
13
Parameter
d0
γ
N
ht
hr
Cm
Value
1m
2.5
25
1m
1m
0
L0
20 log10
LC
0
λ
4π
June 25, 2015
CHAPTER 3. MODEL DEVELOPMENT
A path loss comparison of the selected models can be seen in Figure 3.1. The comparison only consider the line-of-sight component in the models.
Figure 3.1: Comparison of path loss models
The free-space model is accurate when the line-of-sight component is dominant and
reflection is negligible. This model is not suitable in an indoor environment, since it does
not take reflections, diffusion and object attenuation into account, which is not negligible
in this kind of indoor environment.
The Hata and COST 231 extension to Hata models may be very useful for cellular
coverage estimation for larger areas with the frequencies covered, but is not suited for
modelling systems at the frequencies nor the environment needed for this project. This
can be seen in Figure 3.1, as the path loss is significantly higher than for the compared
models.
The COST 231 Multi Wall, ITU-R model and WINNER II gives an idea how indoor
path loss models are designed. These models generally give environment properties for
general cases but not for the environment required for this project.
The simplified path loss model is adjustable for any frequency and environment, and
such is suitable for an indoor propagation model at a generic frequency as required by
this project. Object attenuation needs to be taken into consideration when implementing
the final model, which the basic simplified path loss model does not.
14
June 25, 2015
3.1.2
CHAPTER 3. MODEL DEVELOPMENT
Initial Model
Using the conclusions of section 3.1.1, an initial model can be selected. The model is based
on the simplified path loss model, with a RAF (Rack Attenuation Factor ) for attenuation
due to objects in the propagation path. For indoor environments the reference distance
is set to d0 = 1 m. The path loss and object attenuation will be empirically determined
for the model. The initial model is described by (3.1).
PL = −20 log10
3.2
λ
4πd0
+ 10γ log10
d
d0
+ RAF + ψdB
(3.1)
Measurement Equipment
To determine the path loss component and the RAF, the measured values need to be
adjusted for gain and losses in the measurement equipment. The gains and losses will
be characterized in section 3.2.1 and 3.2.2. The following measurement equipment was
used:
• Signal Analyzer, Keysight PXA N9030A
• Signal Generator, Keysight MXG N5183B
• Horn Antenna 18.0 - 26.5 GHz, A.H. Systems SAS-587
• PCB SMA connector (transmitter antenna), Rosenberger
• Low loss cable, A.H. Systems SAC-26G
• RF cable, HUBER+SUHNER Sucoflex 104
• Precision 2.4 mm to SMA converters
The signal analyzer has a displayed noise floor of -100 dBm with a configured analysis
and video bandwidth of 1 kHz. Using a bandwidth of 1 kHz allows the transmitted signal
to be separated from adjacent signals, while accurately representing the received power.
These settings will be used for all the measurements.
3.2.1
Interface Loss Characterization
To be able to determine the gain offset of the measurements, the equipment losses need
to be characterized. This factor specified as LM easure in (3.5).
For the measurements, the SAC-26G cable was used as a reference since it has characterization data provided by A.H. Systems Inc. An illustration of the measurement
setup can be seen in Figure 3.2 for the conversion connector loss characterization, and
in Figure 3.3 for the characterization of the Sucoflex cable. The loss for each setup was
determined by subtracting the transmitted power with the received power and the know
losses. The measurement results are summarized in Table 3.2.
15
June 25, 2015
CHAPTER 3. MODEL DEVELOPMENT
Figure 3.2: Conversion connector loss characterization
Figure 3.3: Loss characterization of Sucoflex 104 cable
Table 3.2: Interface losses
Component
SAC-26G
Precision 2.4 mm to SMA converter
Sucoflex 104
3.2.2
23.0 GHz
1.90 dB
1.13 dB
0.81 dB
18.0 GHz
1.61 dB
0.86 dB
0.66 dB
SMA Antenna Characterization
To compare the results as predicted by the proposed model to the measured results, the
antenna gains need to be characterized. The receiver antenna is a standard gain horn
antenna, which has been characterized and calibrated by A.H. Systems Inc [6]. As a
transmitter antenna, a PCB SMA connector was used. However, its gain is unknown
and need to be characterized. The gain of the transmitter antenna can be characterized
with a method called the gain comparison method. This method requires three antennas
in order to calculate the gain of the Antenna Under Test (AUT).
The gain comparison method can be utilized by using a spectrum analyzer and a
signal generator. First the reference antenna is connected to the spectrum analyzer
and the ”Don’t Care”-antenna, marked as X in Figure 3.4, is connected to the signal
generator. The ”Don’t Care”-antenna is an antenna which gain is not required for the
characterization, but has to have a sufficient dynamic range in order to transmit to the
16
June 25, 2015
CHAPTER 3. MODEL DEVELOPMENT
AUT. The reference antenna is removed and the AUT is connected to the spectrum
analyzer as shown in Figure 3.5. [16]
Figure 3.4: Characterization with reference antenna
Figure 3.5: Characterization with antenna under test
The received power for the described measurements is given by (3.2).
Pr,dBm = Pt,dBm − PL + Gt,dBi + Gr,dBi − LM easure
(3.2)
where Pr,dBm and Pt,dBm are the received and transmitted power, PL is the path loss
between the transmitter and receiver, Gt,dBi and Gr,dBi are the transmitter and receiver
gains and LM easure is the interface losses.
Since the measurements will be carried out in the same environment and with the
same interface losses, the equation from the two measurement setups can be subtracted
to obtain the gain of the AUT, as shown in (3.3).
GAU T = Pr,REF − Pr,AU T + GREF
(3.3)
where Pr,REF and Pr,AU T is the received power for the respective measurement. GREF
is the gain of the reference antenna, and GAU T is the gain of the AUT. The results of
the antenna characterization are summarized in section 3.2.3.
17
June 25, 2015
3.2.3
CHAPTER 3. MODEL DEVELOPMENT
Equipment Parameters
Using the methods described in section 3.2.1 and 3.2.2, the component parameters were
determined. The interface and antenna parameters for an operational frequency of 23.0
GHz are presented in Table 3.3 and in Table 3.4 for 18.0 GHz.
Table 3.3: Component properties at 23.0 GHz
Component
Horn antenna
Signal Analyzer cables and connectors
SMA Antenna
Signal Generator cables and connectors
Gain
15.3 dBi
-3.03 dB
1.2 dBi
-1.97 dB
Table 3.4: Component properties at 18.0 GHz
Component
Horn antenna
Signal Analyzer cables and connectors
SMA Antenna
Signal Generator cables and connectors
3.3
Gain
14.0 dBi
-2.47 dB
2.3 dBi
-1.52 dB
Path Loss Exponent
The path loss exponent of the initial model in (3.1) determines the rate the power decreases over distance. Measurements need to be performed in different scenarios to be
able to determine the environmental factor of the path loss. The path loss exponent will
be determined for the following scenarios:
• Open space
• Populated rack environment
During the measurements, the transmitter antenna had a fixed position in the environment, while the receiving antenna will be placed at different distances from the
transmitting antenna. The measurements were performed in small in small enough spacial intervals for an accurate estimation of path loss characteristics. An illustration of
the measurement method is shown in Figure 3.6.
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June 25, 2015
CHAPTER 3. MODEL DEVELOPMENT
Figure 3.6: Measurement setup for determining the path loss exponent
When performing measurements for the path loss exponent, additional factors need
to be considered in the measurements. The following parameters need to be considered:
• Loss in cable interface
• Gain of receiver antenna
• Gain of transmitter antenna
• Orientation/polarization of the antennas
The collected data will be adjusted for relative gain of the measurement equipment
and then plotted in Matlab.
3.3.1
Path Loss Exponent Measurements
The path loss exponent is assumed to be a scaling factor for a logarithmic function, as
seen in (3.1). The measurements were performed with a distance interval of 0.5 m and
a range of 1-10 m for the open space measurements and 1-6 m in the rack environment.
Five series of measurements were performed for each frequency in order to give a good
approximation of the path loss exponent.
The fit used to approximate the path loss exponent is based on least-square method,
which fits a linear curve to the data as it minimizes the summed square of the residuals.
The least-square linear fit is implemented in Matlab with the Curve Fitting Toolbox
software. The equation for determining the sum of the squared residuals can be seen in
(3.4). [18]
S =
n X
i=1
yi − ybi
2
(3.4)
where S is the square sum of the residuals, yi is i:th data point and ybi is the fitted
data point for the i:th value.
In Figures 3.7 and 3.8, the path loss calculated by (3.5) is represented by a black dot.
The calculated average path loss is represented by a red star, and the fitted line curve
is represented by a blue line. The fitted curve is represented as a linear function in the
presentation of the measured values because of the logarithmic scaled axes.
PL = Pt,dBm − Pr,dBm − Gr,dBi − Gt,dBi + LM easure
(3.5)
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June 25, 2015
CHAPTER 3. MODEL DEVELOPMENT
Using the method described in [17] gives the ability to extract the path loss exponent
for the different scenarios. The measured data for the rack environment is calculated in
the same way as the open space measurements. The plotted received power can be seen
in Appendix A and the raw data can be found in Appendix B.
Path loss exponent at 23.0 GHz
The plotted data for the open space measurement for 23.0 GHz can be viewed in Figure
3.7 and are summarized in Table 3.5.
Figure 3.7: Measured path loss for an open space environment at 23.0 GHz
Table 3.5: Path loss exponents in different scenarios at 23.0 GHz
Scenario
Open space
Rack environment
γ
1.86
1.82
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June 25, 2015
CHAPTER 3. MODEL DEVELOPMENT
Path loss exponent at 18.0 GHz
The plotted data for the open space measurement for 18.0 GHz can be viewed in Figure
3.8 and are summarized in Table 3.6.
Figure 3.8: Measured path loss for an open space environment at 18.0 GHz
Table 3.6: Path loss exponents in different scenarios at 18.0 GHz
Scenario
Open space
Rack environment
3.4
γ
1.97
1.83
Rack Attenuation Factor
The RAF introduced in section 3.1.2, is initially assumed to be linearly proportional to
the distance propagated through the rack. The RAF is also assumed to depend on the
density of the server racks, where a more dense rack will attenuate the signal more than
a lower dense rack. The initial RAF equation is given by (3.6).
RAF =
NR
X
ρi · d i
(3.6)
i=i
where ρi is the attenuation constant depending on the rack density, and di is the
distance in meters the signal travels through a rack and NR is the number of racks in the
propagation path.
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June 25, 2015
CHAPTER 3. MODEL DEVELOPMENT
To determine the RAF, a series of measurement have to be performed for different
scenarios. The measurement scenarios to determine the attenuation constant ρ is illustrated in Figure 3.9. The receiver antenna will be displaced vertically along the server
rack. This combined with the path loss of the environment will determine the final
estimate values for the RAF.
The measurement scenarios to determine the attenuation constant ρ is illustrated in
Figure 3.9.
Figure 3.9: Measurement setup for determining the rack attenuation factor
This measurement will be performed in the different density cases, since the server
racks in the test lab are not equally populated. The population density will be a factor
since the separation between the rack equipment will determine if the signal will have a
line-of-sight component or not when propagating through the rack. Four different server
rack densities have been defined to more accurately model de object attenuation, as
shown in Table 3.7.
Table 3.7: Definition of rack densities
Scenario
Lightly populated rack
Medium populated rack
Heavily populated rack
Solid object
3.4.1
Population percentage
10 - 40 %
40 - 70 %
70 - 90 %
90 - 100 %
Rack Attenuation Factor Measurements
To obtain an estimate value for the losses, measurements were carried out as illustrated in
Figure 3.10. Three series of measurements with different receiver heights were performed
for each rack density. The object attenuation was derived by subtracting the the equivalent open space path loss for each measurement. The use of different receiver heights is to
22
June 25, 2015
CHAPTER 3. MODEL DEVELOPMENT
enable both line-of-sight and non-line-of-sight components to affect the average received
power. This will give a more accurate average attenuation for the different rack densities.
Figure 3.10: Line-of-Sight and Non-Line-of-Sight components in the RAF measurements
Rack attenuation factor at 23.0 GHz
The calculated average values for the ρ in dB/m at 23.0 GHz can be seen in Table 3.8.
Table 3.8: Rack attenuation factor for different rack densities at 23.0 GHz
Scenario
Light rack density
Medium rack density
High rack density
ρ
4.5
6.0
19.0
Rack attenuation factor at 18.0 GHz
The calculated average values for the ρ in dB/m at 18.0 GHz are shown in Table 3.9.
Table 3.9: Rack attenuation factor for different rack densities at 18.0 GHz
Scenario
Light rack density
Medium rack density
High rack density
ρ
8.4
11.2
17.6
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June 25, 2015
3.4.2
CHAPTER 3. MODEL DEVELOPMENT
Solid Object Attenuation
In the case of propagation through a solid object, there will not be any line-of-sight
component available, as illustrated in Figure 3.10. Therefore, the measurement setup
was changed compared to the setup used in section 3.4.1. Instead of moving the receiving
antenna vertically it is moved horizontally along the object. This method is used since
the are no line-of-sight components available for the receiving antenna, as shown in
Figure 3.10. In addition, the measurement were performed with three different separation
distances, as seen in Figure 3.11. Different separation distances will indicate how the
multipath components affect the received power. These measurements will be used in
order to estimate a loss factor for solid objects.
For each separation distance a series of measurements were performed. The average
attenuation value was calculated for each series of measurements. The results of the
measurements are shown in Table 3.10 and 3.11.
Figure 3.11: Measurement setup solid object attenuation seen from above
Rack attenuation factor for solid object at 23.0 GHz
The calculated average values for the ρ in dB/m for 23.0 GHz can be seen in Table 3.10.
Table 3.10: Solid object attenuation for different separation distances at 23.0 GHz
Separation
2.9 m
4.9 m
6.9 m
ρ
32.0
30.2
22.4
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June 25, 2015
CHAPTER 3. MODEL DEVELOPMENT
Rack attenuation factor for solid object at 18.0 GHz
The calculated average values for the ρ in dB/m for 18.0 GHz are shown in Table 3.11.
Table 3.11: Solid object attenuation for different separation distances at 18.0 GHz
Separation
2.9 m
4.9 m
6.9 m
ρ
27.7
26.1
19.7
The decreed object attenuation with increased separation distance can be explained
by the multipath properties of indoor propagation. The increased number of available
multipath components at the receiver will reduce the apparent attenuation of the solid
object.
3.5
Proposed Model
After performing the necessary measurements, the initial model in (3.1) was modified
in order to include the measured values in section 3.3 and 3.4. Moreover the model is
rewritten to be frequency dependent instead of wavelength dependent as seen in (3.7).
PL = 20 log10 (f ) + 10γ log10 (d) − 20 log10
c
4π
+ RAF + ψdB
(3.7)
where c is the speed of light in m/s and f is the operational frequency in Hz.
The path loss model can be reduced further as shown in (3.8). With the obtained
results for the path loss exponent, the model can be compared with the fitted curve from
the measurements in section 3.3.1. The comparison can be seen in Figure 3.12 for 23.0
GHz and Figure 3.13 for 18.0 GHz.
PL = 20 log10 (f ) + 10γ log10 (d) − 147.5 + RAF + ψdB
(3.8)
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June 25, 2015
CHAPTER 3. MODEL DEVELOPMENT
Figure 3.12: Estimated path loss for open space at 23.0 GHz
Figure 3.13: Estimated path loss for open space at 18.0 GHz
This model will initially be used in the simulation model and and it will be further
processed and evaluated in chapter 4.
26
Chapter 4
Model Verification and Correction
In this chapter the preliminary model will be evaluated and optimized in order to create
a more accurate model. Verification measurements were performed in order to evaluate
and correct the path loss model.
4.1
Verification Measurements
In order to evaluate the accuracy of the model, verification measurements were performed
in the test lab environment. This section will describe how the measurements were
collected and show the deviation of the preliminary model described in (3.8).
4.1.1
Measurement Setup
The leakage simulation tool will implement the path loss model using a direct path
modelling method. The verification measurements were performed using the direct path
component of the transmitted signal. This method was used in order to more accurately
represent the direct path modelling method. The verification measurements were performed for both LOS and NLOS locations in the test lab. This allows the final path
loss model to be adjusted more accurately. The measurement locations are placed in a 2
meter by 2 meter grid in the test environment, illustrated in Figure 4.1.
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June 25, 2015
CHAPTER 4. MODEL VERIFICATION AND CORRECTION
Figure 4.1: Verification measurement locations in the test lab environment
4.1.2
Model Deviation
In order to evaluate the accuracy of the model the deviation of the model needs to be
calculated. The deviation of the model is assumed to be normally distributed with a
mean of µ = 0 [2].
The normal distribution is symmetrical and has the property of containing a percentage of its values within a set number of standard deviations from its mean. Within 2σ
above and below the mean, 95% of the possible outcomes will be included in the distribution [5]. This characteristic will be used to evaluate the possible worst case scenario
for the signal leakage levels.
Calculating the standard deviation for the LOS and NLOS components separately
will indicate where the model needs to be corrected. The calculated deviation for the
model can be seen in Table 4.1 for the LOS components and Table 4.2 for the NLOS
components.
Table 4.1: Deviation of the LOS components
Frequency
23.0 GHz
18.0 GHz
σ
3.91 dB
4.81 dB
µ
1.27 dB
0.36 dB
MAX
11.29 dB
12.25 dB
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June 25, 2015
CHAPTER 4. MODEL VERIFICATION AND CORRECTION
Table 4.2: Deviation of the NLOS components
Frequency
23.0 GHz
18.0 GHz
4.2
σ
16.11 dB
14.22 dB
µ
-4.13 dB
-8.70 dB
MAX
43.10 dB
56.10 dB
Model Correction
Comparing the deviation between the LOS and NLOS components, it can be seen that
the model is less accurate in the NLOS case. This is due to larger residual values in the
calculation of the standard deviation. The modelled path loss combined with the object
attenuations are higher than the measured path loss in the NLOS cases. The residuals
exceeding 15 dB is represented with a blue circle in Figure 4.2.
Figure 4.2: Deviating points
The large deviation of the NLOS case can be partially explained by the result which
were obtained in section 3.4.2. It indicated that with increased transmitter-receiver
separation the apparent attenuation of the object is reduced. Alternatively this can be
explanation by the dominant path aspect of the propagating signal.
29
June 25, 2015
4.2.1
CHAPTER 4. MODEL VERIFICATION AND CORRECTION
Path Loss Exponent Correction
The simulation of the preliminary path loss model, seen in (3.8), does not fully represent
the data fit as seen in Figure 3.12 and 3.13. This offset can be explained by the mean
value of the deviation calculations seen in Table 4.1, as the µ 6= 0. This offset is 3.4
dB for the 23.0 GHz model and 1.0 dB for the 18.0 GHz model. This offset is assumed
to be frequency dependent, however with only two modelled frequencies this can not be
further investigated.
The offset between the preliminary model and the data fit could be decreased by
adjusting the value of the path loss exponent. This adjustment will reduce the mean error
for shorter distance, however this adjustment will reduce the validity of the model with
increased simulation distances. Since the standard deviation for the model is below 5.0
dB with the current implementation, the validity of the LOS components are considered
to be acceptable. With these factors considered, the path loss exponent will not be
adjusted in the final implementation of the path loss model.
4.2.2
Rack Attenuation Factor Correction
In the simulations of the preliminary implementation of the path loss model it can be
seen that the deviation of the NLOS components are considerably larger than the LOS
components. This can be seen in the standard deviation and the maximum deviation in
Table 4.2.
The initial assumption of the linear property of the RAF may cause this increased
deviation. The most troublesome locations are where there are multiple objects obstructing the path between the transmitter and receiver. Observations on multiple floor losses
shows that the apparent attenuation of consecutive floors are not linear compared to a
single floor loss. In an office environment the attenuation of the second floor is roughly
30% of the first floor [12]. Adjusting for this observation in the calculation of the RAF
may reduce the deviation of the NLOS components. The new implementation of the
RAF calculations can be seen in (4.1).
RAF = ρ1 d1 + K ·
NR
X
ρi d i
(4.1)
i=2
The optimal value for K is derived by calculating the standard deviation and the
mean deviation of the NLOS components with different K values. The results of these
calculations can be seen in Table 4.3 for 23.0 GHz and Table 4.4 for 18.0 GHz. The
initial implementation of the RAF calculations corresponds to K = 1 used in (4.1).
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June 25, 2015
CHAPTER 4. MODEL VERIFICATION AND CORRECTION
Table 4.3: K for 23.0 GHz model
K
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
4.2.3
σ
9.05 dB
8.37 dB
8.04 dB
8.09 dB
8.51 dB
9.27 dB
10.27 dB
11.47 dB
12.80 dB
14.22 dB
µ
4.10 dB
3.18 dB
2.27 dB
1.36 dB
0.44 dB
-0.47 dB
-1.39 dB
-2.30 dB
-3.21 dB
-4.13 dB
MAX
18.47 dB
18.47 dB
18.47 dB
18.47 dB
18.47 dB
23.86 dB
27.17 dB
32.48 dB
37.79 dB
43.10 dB
Table 4.4: K for 18.0 GHz model
K
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
σ
8.38 dB
7.99 dB
8.02 dB
8.46 dB
9.26 dB
10.33 dB
11.60 dB
13.01 dB
14.53 dB
16.11 dB
µ
0.70 dB
-0.35 dB
-1.39 dB
-2.44 dB
-3.50 dB
-4.52 dB
-5.57 dB
-6.61 dB
-7.65 dB
-8.69 dB
MAX
18.60 dB
18.60 dB
18.60 dB
23.95 dB
27.64 dB
33.33 dB
39.02 dB
44.71 dB
50.40 dB
56.10 dB
Deviation after Model Correction
Changing the definition of the RAF improves the overall accuracy of the model. The
results of introducing K can be seen on the µ and σ values in Table 4.3 and 4.4.
The final path model will be implemented using the originally derived path loss exponents and attenuation constants for the RAF calculations. The implementation of the
RAF has been reworked from (3.6) to (4.1). Selecting a K value of 0.3 for the RAF
calculations gives the best compromise between the standard and mean deviations for
both frequencies, as shown in Table 4.3 and 4.4. The deviations for the final path loss
model can be seen in Table 4.5 and 4.6.
Table 4.5: Corrected deviation of the LOS components
Frequency
23.0 GHz
18.0 GHz
σ
3.91 dB
4.81 dB
µ
1.27 dB
0.36 dB
MAX
11.29 dB
12.25 dB
Table 4.6: Corrected deviation of the NLOS components
Frequency
23.0 GHz
18.0 GHz
σ
8.04 dB
8.02 dB
µ
2.27 dB
-1.39 dB
MAX
18.47 dB
18.60 dB
31
Chapter 5
Results
This chapter will present the results of the final model and its implementation. The
aspects of different leakage scenarios will be investigated and simulated using the final
path loss model.
5.1
Final Model
In the leakage simulation tool, the path loss model will be implemented in order to
calculate the potential received power at any point in a 2D space. Using the leakage
power and the path loss model will give the received power at any point in the 2D space.
The simulation model can be seen in (5.1).
Pr (d) = Pleakage − 20 log10 (f ) − 10γ log10 (d) + 147.5 −
ρ1 d1 + 0.3
NR
X
i=2
ρi d i
!
(5.1)
where Pr is the received power and Pleakage is the leakage power. The remaining
components are from the preliminary path loss model in (3.8).
In the worst case scenario the standard deviation of the NLOS case will be used to
evaluate the signal strength. The standard deviation of the NLOS case is roughly 8.0
dB for both the 23.0 GHz and the 18.0 GHz model. Currently there are no known commercially used indoor path loss model at the microwave frequencies used in this report.
Hence the implemented path loss model are compared with results from models designed
for significantly lower frequencies. The resulting standard deviation for the NLOS components is roughly 8.0 dB for both 18.0 and 23.0 GHz, this result is be compared with
standard deviations that ranges between 7 and 17 dB retrieved in [12][24][25]. Since the
obtained standard deviation is in the lower range in that comparison, the final propagation model is assumed to be valid and can be applied to evaluate possible leakage
scenarios.
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June 25, 2015
5.2
CHAPTER 5. RESULTS
Leakage Simulations
The simulation model in (5.1) will be used to evaluate different leakage scenarios in the
MINI-LINK setup used in the test lab. The worst case leakage power will be used to
evaluate the possible scenarios.
5.2.1
Maximum Allowed Radiated Power
Evaluating the worst case leakage scenarios, the maximum allowed radiated power is
required. The maximum exposure limit set by the responsible authority (Strålsäkerhetsmyndigheten) in the frequency range between 2 GHz and 300 GHz is 10 W/m2 , or
a field strength of 155.7 dBµV/m [19]. According to the MIL-STD-461F the radiated
susceptibility of ground equipment in the frequency range 18-40 GHz is set to be able to
handle 50 V/m, or a 154 dBµV/m [15]. This level is below the maximum level set by
Strålsäkerhetsmyndigheten and will be used to calculate the maximum allowed power.
Using the characterization data of the SAS-587 reference antenna and a 50 Ω system
impedance, the maximum power can be calculated as seen i (5.2) [20].
PM AX = VLim − 107 − AF + LM easure − Gr
(5.2)
where PM AX is the maximum allowed power in dBm, VLim is the maximum allowed
field strength in dBµV/m, AF is the antenna factor of the antenna in dB/m, LM easure is
the interface loss in dB and Gr is the gain of the antenna in dBi.
The maximum allowed radiated power is -8.5 dBm for 23.0 GHz and -6.7 dBm for
18.0 GHz.
5.2.2
Leakage from MINI-LINK Setup
In order to understand the potential leakage scenarios, the equipment connecting the
MINI-LINK radio units will be evaluated. The following equipment is used for transmitting the signals between the MINI-LINK radio units in the test lab:
• Waveguide
• Waveguide to coaxial converter
• Coaxial cable
• Attenuators
The connection between the majority of the MINI-LINK radio units uses a Sucoflex
104 cable as listed in section 3.2. The shield used in this cable is a silver-plated copper
tape with an additional silver-plated copper braid. This shield setup has a leakage
attenuation of about 95 dB [21]. Some of the MINI-LINK radio units are connected with
a waveguide instead of the Sucoflex cable. Typically, with gaskets and proper assembly,
the waveguide has a leakage attenuation of about 90 dB [22]. This leaves the connector
of the cable as the major leakage contributor [23].
33
June 25, 2015
CHAPTER 5. RESULTS
Evaluating the leakage from the SMA connector, a 50 Ω termination was connected
to the end of the Sucoflex cable. The power was measured with a transmitted power of
30 dBm at a distance of 2λ from the connector. This power was used since the maximum
transmitted power of the MINI-LINK units is in the 30 dBm range. The measured power
of this test can be seen in Table 5.1. The reference torque is 90 N cm with a Rosenberger
32W100-016 torque wrench.
Table 5.1: Measured power of the leakage scenarios
Scenario
Torque wrench
Finger tight
1/4 revolution loosened
1/2 revolution loosened
23.0
-53.4
-49.3
-41.6
-29.5
GHz
dBm
dBm
dBm
dBm
18.0
-50.3
-54.9
-41.1
-34.1
GHz
dBm
dBm
dBm
dBm
With the measured power adjusted for the gain and losses in the measurement equipment, the leakage power is found to be roughly 70 dB below the transmitted power for
the scenario with the connector 1/2 revolution loosened. This leakage level is 20 dB higher
than the leakage from the shield and waveguide. This leakage scenario will be used for
the leakage simulations in the test environment.
5.2.3
Model Simulations
Simulating the leakage in the test environment requires the simulation tool to accurately
represent the actual power levels. The implemented leakage simulation tool is regulated
by the requirements in Table 1.3.
In Figure 5.1 the environment layout used in section 4.1.1 is recreated in the simulation
tool. A single leakage source of 0 dBm at 23.0 GHz is configured to replicate this scenario.
This configuration was used in order to replicate the verification measurements.
34
June 25, 2015
CHAPTER 5. RESULTS
Figure 5.1: Single source simulation
In Figure 5.2 the environment is the same as in Figure 5.1. Three leakage sources is
configured with a frequency of 18.0 GHz and leakage power of -40 dBm. This leakage
power of -40 dBm corresponds to a radio unit transmitting with a power of 30 dBm with
the SMA connector loosened half a revolution, as seen in section 5.2.2.
Figure 5.2: Multiple source simulation
A user guide of the simulation tool and its features can be found in Appendix C.
35
Chapter 6
Discussion and Conclusion
The primary purpose of the project was to investigate and evaluate potential leakage
scenarios in the test lab. Two primary aspects of the leakage needed to be evaluated;
the security and the health aspects. These parts are of critical importance to the test
environment engineers to ensure the operational capability of the test lab.
6.1
General Discussion
During the process of developing the path loss model there have been no available studies
or literature that cover the specific frequencies and environment used in this thesis.
Hence, while deriving the path loss model comparisons were made with models designed
for other frequencies and environments.
From section 3.3 it can be seen that the derived path loss exponent results in a reduced
loss over a certain distance compared to free space loss. This indicates that there are
lower losses at higher frequencies, compared to typical telecommunication frequencies,
which is something that are not always observed or easily explained. Typically signals at
higher frequencies are more affected by object attenuations, but less obstruction in the
transmission path may lead to lower losses [12]. Comparing the derived path loss exponent with results from other path loss models designed for high microwave frequencies
gives an indication of the same characteristics [12]. With this aspect the derived path
loss exponents from section 3.3 is considered to be applicable in the desired environment.
Modelling the attenuation of objects in the transmission path proved to result in a
much higher deviation compared to the measurements conducted in the test lab. Initially
the attenuations were assumed to be linear to the distance travelled through the object.
This created large model deviations compared to the performed verification measurements. Adjustments of the particular attenuations and the path loss exponent proved
to have a much higher impact on the characteristics of the model with only small improvements to the overall accuracy. Scaling the object attenuation after the first object
improved the standard deviation of the model. The ρ value for the specific rack densities
is not changed in the current implementation of the RAF modelling method.
Some problems still remains, such as the mean of the deviation are not fully centred
around zero. Since the amount of data used for these calculations are limited, performing
36
June 25, 2015
CHAPTER 6. DISCUSSION AND CONCLUSION
additional verifications measurements could solve this problem. Although this is considered to be less relevant due to the relative small deviation and it will not be needed for
the evaluation of the leakage levels. The final standard deviation of the model is in an
acceptable range compared to other models [12][24][25].
In the final implementation of the leakage simulation tool, multiple leakage sources
are implemented. These leakages are simulated separately and combined with fully constructive interference in order to evaluate the largest potential signal power at any given
point of the simulated environment.
6.2
Requirement Evaluation
At the start of the project, requirements were set in order to evaluate the results. This
section will evaluate the requirements.
6.2.1
Pre-study Requirement Evaluation
In Table 6.1 the requirements of the pre-study are evaluated.
Table 6.1: Analysis of Pre-study requirements
No.
1
2
3
4
5
Comment
The major leakage contributors were investigated in order to simulate the leakage.
The MIL-STD-461F standard and guidelines from Strålsäkerhetsmyndigheten
were used to evaluate potential risks of the leakage.
Indoor propagation models and modelling methods were investigated. A direct
path modelling method was used to implement the path loss model.
Appropriate measurement methods were used to determine the aspects needed
for the model.
The Matlab programming was investigated when needed and applied in the
leakage simulation tool.
37
June 25, 2015
6.2.2
CHAPTER 6. DISCUSSION AND CONCLUSION
Model Requirement Evaluation
In Table 6.2 the requirements of the model are evaluated.
Table 6.2: Analysis of Model requirements
No.
6
7
8
9
10
11
12
13
14
6.2.3
Comment
The model was implemented in the leakage simulation tool using Matlab.
The leakage simulation tool has adjustable parameters for different environments.
The leakage simulation tool has adjustable frequency setting.
A user mappable environment has been implemented in the leakage simulation
tool.
The leakage simulation tool is able to assign three independent leakage sources
at one given frequency.
An analysis of the verification measurements has been performed to give the
total accuracy of the given model. This is not implemented in the leakage
simulation tool.
The leakage simulation tool does not alert the user when there is a potential
security risk. This feature has not been implemented.
The leakage simulation tool will alert the user when the signal strength is above
a set level.
The leakage simulation tool is implemented with a graphical user interface with
all appropriate assignable parameters.
Measurement Requirement Evaluation
In Table 6.3 the requirements of the measurements are evaluated.
Table 6.3: Analysis of Measurement requirements
No.
15
16
17
18
Comment
The equipment used for the measurements are of high quality and precision.
The orientation and placement of the measurement equipment have been considered and is defined in the individual experiments.
The elevation of the measurement equipment have been considered and the
method is defined in the individual experiments.
Two frequencies have been investigated for the model.
38
June 25, 2015
6.2.4
CHAPTER 6. DISCUSSION AND CONCLUSION
Project Requirement Evaluation
In Table 6.4 the requirements of the project are evaluated.
Table 6.4: Analysis of Project requirements
No.
19
20
21
22
Comment
Written report is in the form of the current document.
Weekly meetings have not been performed, but meeting has been performed per
need basis during the project.
Monthly written report have not been performed, but reports have been performed per need basis during the project.
Presentation of the results and the leakage simulation have been scheduled at
both Ericsson and LiU.
39
June 25, 2015
6.3
CHAPTER 6. DISCUSSION AND CONCLUSION
Conclusion
The purpose of the project was to investigate the leakage from the MINI-LINK setup in
the Ericsson test lab. This was accomplished with an empirical path loss model for the
lab environment. This model is adjusted for frequencies and an environment that has
not earlier been documented, as indicated by the initial pre-study. The path loss model
is adapted to the environment with an empirical derived characteristics of the path loss
and object attenuation.
Path loss modelling is an appropriate method to evaluate different leakage scenarios,
if the model is able to accurately represent the environment. The deviation of the model
used is important when the worst case scenarios are being evaluated. In the worst case
scenario the simulated power will have to be increased by 2σ, or 16 dB for the path loss
models constructed by this project. This additional contribution will cover over 95% of
the possible leakage levels that the model will provide and give an accurate representation
of the worst case scenario.
It was found that the most likely component to cause the majority of the signal leakage
was the SMA connectors of the MINI-LINK radio units. In the worst case scenario it was
found that the radiated power was below the limit by both Strålsäkerhetsmyndigheten
and the MIL-STD-461F standard. Additionally a signal at this frequency attenuates
significantly over distance and will not pose a potential security risk. However the simulation tool will alert the user if the signal level is above a set limit anywhere in the
simulation environment.
Signal transfer at microwave frequencies are more sensitive. In order to prevent signal leakage from the systems using microwave frequency signals, proper assembly with
appropriate tools are essential. It was shown that not connecting the equipment appropriately may cause increased signal leakage and additional RF problems such as impedance
mismatch and signal reflection.
40
June 25, 2015
6.4
CHAPTER 6. DISCUSSION AND CONCLUSION
Future Work
Evaluating the fitted data compared to the final model, it was found that there was
an offset. Investigating an additional frequency in the 18.0 to 26.5 GHz range would
give more information how to introduce an adjustment factor to the model. Collecting
additional data for each experiment will likely improve the overall accuracy of the model.
The measurements can be performed in different test lab layout to further increase the
validity of the model.
Additional development of the leakage simulation tool can be performed to improve
the usability. Implementing features such as creating and recalling user defined presets
and layouts is a possible future development.
41
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[3] S. Haykin, M. Moher, Modern Wireless Communications, Pearson Prentice Hall,
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978-91-523-0718-2
[6] A.H. Systems Inc., Antenna Factor Data, Calibration and parameter data document
[7] I. Dey, G. Messier, S. Magierowski, Joint Fading and Shadowing Model for Large
Office Indoor WLAN Environments, IEEE Transactions on Antennas and Propagation, Vol. 62, No. 4, April 2014, Online: http://ieeexplore.ieee.org/stamp/
stamp.jsp?tp=&arnumber=6710174, Read: 2015-03-09
[8] Ericsson AB, Ericsson to build three Global ICT Centers, Press Release 2013, Online:
http://www.ericsson.com/news/1726568, Read: 2015-03-02
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net/service/internet/picov/get?DocNo=19/28701-FGB101004&Lang=EN&
HighestFree=Y, Read: 2015-03-09
[10] Ericsson AB, Technical Description MINI-LINK PT 2020 ETSI, 2014, Internal Ericsson document
[11] AWE Communications, Indoor Ray Optical Propagation Models, Online: http://
awe-communications.com/Propagation/Indoor/RayOptical/index.htm, Read:
2015-03-09
[12] International Telecommunication Union, Propagation data and prediction methods
for the planning of indoor radiocommunication systems and radio local area networks
in the frequency range 900 MHz to 100 GHz, 2012, Online: http://www.itu.int/
42
June 25, 2015
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dms_pubrec/itu-r/rec/p/R-REC-P.1238-7-201202-I!!PDF-E.pdf, Read: 201503-02
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[14] Information Society Technologies, WINNER II interim channel models, 2007,
Online: http://www.cept.org/files/1050/documents/winner2%20-%20final%
20report.pdf, Read: 2015-03-02
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FOR THE CONTROL OF ELECTROMAGNETIC INTERFERENCE CHARACTERISTICS OF SUBSYSTEMS AND EQUIPMENT, Online: http://snebulos.
mit.edu/projects/reference/MIL-STD/MIL-STD-461F.pdf, Read: 2015-03-02
[16] Measurementtest.com, How To Measure Antenna Gain, 2010, Online: http://www.
measurementest.com/2010/09/how-to-measure-antenna-gain-part-1-gain_
08.html, Read: 2015-04-02
[17] Ohio University, Curve Fitting, Loglog Plots, and Semilog Plots, 2003,
Online:
https://www.math.ohiou.edu/courses/matlab/math266a/
266A-fitting-logplot.pdf, Read: 2015-04-09
[18] Mathworks, Least-Squares Fitting, Online: http://se.mathworks.com/help/
curvefit/least-squares-fitting.html?refresh=true, Read: 2015-04-09
[19] Strålsäkerhetsmyndigheten, Strålsäkerhetsmyndighetens författningssamling ISSN
2000-0987, Online:
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Publikationer/Forfattning/SSMFS/2008/SSMFS2008-18.pdf, Read: 2015-04-24
[20] A.H. Systems Inc., TYPICAL CONVERSION FORMULAS, Online: http://www.
ahsystems.com/notes/TYPICAL_CONVERSION_FORMULAS.pdf, Read: 2015-04-24
[21] Harbour Industries, Shielding Effectiveness Test Method, Online:
//harbourind.com/harbourdev/images/technical_pdfs/shielding_
effectiveness_test_method.pdf, Read: 2015-05-05
http:
[22] Tect Electronics,
The Waveguide Solution,
Online:
http://www.
tect-electronics.com/uploads/files/TWS/Flexible_Waveguide.pdf, Read:
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[23] Applied Engineering Products, SMA Series Subminiature RF Connectors, p. 3, Online: http://www.radiall.com/media/AEP%20SMA%20127-1.pdf, Read: 2015-0507
[24] K. Cheung, J. Sau, R. D. Murch, A New Empirical Model for Indoor Propagation
Prediction, IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 47,
NO. 3, AUGUST 1998, Online: http://ieeexplore.ieee.org/stamp/stamp.jsp?
arnumber=704854, Read: 2015-05-22
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[25] A. Valcarce, J.Zhang, Empirical Indoor-to-Outdoor Propagation Model for Residential Areas at 0.9–3.5 GHz, IEEE ANTENNAS AND WIRELESS PROPAGATION
LETTERS, VOL. 9, 2010, Online: http://ieeexplore.ieee.org/stamp/stamp.
jsp?arnumber=5510104, Read: 2015-05-22
44
Appendices
45
Appendix A
Plotted Measured Data
A.1
Open Space Plot for 23.0 GHz
Figure A.1: Measured data for open space at 23.0 GHz
46
June 25, 2015
A.2
APPENDIX A. PLOTTED MEASURED DATA
Open Space Plot for 18.0 GHz
Figure A.2: Measured data for open space at 18.0 GHz
A.3
Rack Environment Plot for 23.0 GHz
Figure A.3: Measured data for rack environment at 23.0 GHz
47
June 25, 2015
A.4
APPENDIX A. PLOTTED MEASURED DATA
Rack Environment Plot for 18.0 GHz
Figure A.4: Measured data for rack environment at 18.0 GHz
48
Appendix B
Raw data
B.1
1
Path Loss Exponent Measurements
%Path Loss Exponent Measurements
2
3
4
%D i s t a n c e
d = [1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8 8.5 9 9.5 10];
5
6
7
8
9
10
11
12
13
% C o l l e c t e d data
%Measurement s e r i e s 1−5
%18 GHz
S1 = [ −48.2 −51.7 −53.2 −53.5 −56.6 −58.1 −56.4 −60.9
−60.8 −65.4 −62.3 −62.3 −64.7 −65.0 −69.1 − 6 4 . 8 ] ;
S2 = [ −47.3 −50.7 −52.7 −54.1 −55.6 −57.3 −56.7 −57.6
−60.6 −64.5 −62.6 −62.3 −63.7 −67.0 −68.0 − 6 7 . 4 ] ;
S3 = [ −45.5 −50.0 −52.7 −52.9 −53.8 −57.6 −56.7 −61.3
−61.0 −62.0 −62.0 −60.8 −63.2 −67.1 −63.8 − 6 7 . 8 ] ;
S4 = [ −46.3 −49.3 −50.4 −52.4 −53.6 −56.4 −56.0 −58.2
−60.4 −62.6 −62.0 −60.8 −61.5 −65.2 −64.3 − 7 0 . 8 ] ;
S5 = [ −47.0 −49.9 −50.3 −51.6 −53.4 −54.7 −54.4 −55.4
−61.7 −64.1 −63.0 −59.6 −66.2 −61.0 −64.2 − 7 1 . 5 ] ;
−59.3 −61.9 −61.0
−60.8 −66.5 −65.4
−58.2 −59.6 −62.8
−61.7 −62.4 −61.8
−57.6 −58.2 −59.2
14
15
16
17
18
19
20
%23 GHz
S1 = [ −51.0 −55.7 −60.3 −61.2 −61.5 −63.2 −62.1 −63.0
−69.8 −65.0 −69.3 −72.4 −73.8 −76.9 −72.3 − 7 1 . 6 ] ;
S2 = [ −51.4 −56.0 −58.1 −63.6 −61.4 −61.0 −62.9 −64.7
−66.4 −71.3 −68.8 −67.8 −69.7 −66.6 −67.2 − 6 9 . 3 ] ;
S3 = [ −48.9 −51.6 −52.9 −59.9 −60.2 −57.9 −59.1 −61.4
−67.8 −66.9 −66.4 −66.7 −73.3 −63.5 −65.7 − 6 7 . 8 ] ;
S4 = [ −47.8 −51.8 −53.9 −56.4 −59.0 −58.0 −60.8 −62.1
−64.3 −61.4 −68.9 −62.7 −65.0 −64.3 −64.9 − 6 5 . 6 ] ;
S5 = [ −47.6 −52.6 −54.3 −55.6 −59.5 −59.3 −60.0 −59.9
−65.3 −63.4 −62.5 −64.4 −63.6 −62.8 −67.4 − 6 6 . 8 ] ;
49
−65.0 −68.0 −64.7
−66.0 −67.0 −70.0
−62.4 −67.8 −65.2
−64.0 −63.1 −65.4
−65.6 −60.9 −64.6
June 25, 2015
B.2
1
2
APPENDIX B. RAW DATA
Verification Data Measurements
%V e r i f i c a t i o n Data Measurements
%R e c e i v e d power measurements with Pt = 0 dBm, 2 m between each p o i n t i n t h e
matrix
3
4
5
6
7
8
9
10
11
12
13
14
15
%23 GHz
S1 = [ −72.7
−77.0
−64.3
−60.2
−69.6
−56.8
−59.6
−66.3
−64.6
−81.9
−82.2
NA
−72.7
−66.8
−68.7
−55.8
−64.2
−66.3
NA
−82.6
−79.0
NA
NA
NA
RAU
−56.2
−56.8
−57.6
NA
−74.4
−68.7
−69.8
−65.3
−57.7
−66.3
−57.5
−59.7
−73.0
−66.1
−66.4
−70.3
NA
NA
NA
NA
NA
−63.0
−58.7
NA
−66.8
−86.0
NA
−75.2
−72.7
−75.0
−65.3
−64.8
−62.8
NA
−78.2
−79.0;
−75.6;
−83.2;
−85.4;
−80.5;
−77.6;
−77.3;
−73.8;
−71.5;
−87.0;];
%18 GHz
S2 = [ −67.4
−65.0
−68.7
−59.3
−65.4
−60.9
−57.5
−75.9
−63.7
−79.7
−83.0
NA
−73.9
−65.0
−67.0
−52.5
−55.5
−65.8
NA
−83.2
−75.0
NA
NA
NA
RAU
−50.8
−56.8
−60.7
NA
−71.9
−77.9
−65.1
−63.1
−62.1
−62.3
−57.7
−66.0
−60.2
−60.9
−67.9
−79.9
NA
NA
NA
NA
NA
−63.9
−62.7
NA
−67.4
−86.7
NA
−72.1
−70.9
−71.3
−67.6
−65.9
−63.4
NA
−75.2
−86.5;
−82.8;
−86.5;
−86.5;
−86.5;
−80.3;
−79.9;
−78.0;
−76.8;
−83.5;];
16
17
18
19
20
21
22
23
24
25
26
27
50
June 25, 2015
B.3
1
APPENDIX B. RAW DATA
RAF measurements
%RAF Measurements
2
3
4
5
6
7
%Measuring c o n d i t i o n s
Wr = 1 . 2 ;
Sep = 2 . 0 ;
Ht = 1 . 0 9 ;
Hr = [ 0 . 6 0 . 7 0 . 8 0 . 9 1 . 0 1 . 1 1 . 2 1 . 3 1 . 4 1 . 5 1 . 6 ] ;
%r a c k width
%RX−TX s e p a r a t i o n
%t r a n s m i t t e r h e i g h t
%r e c e i v e r h e i g h t
8
9
10
%Measured v a l u e s
%X SN [ i ] c o r r e s p o n d s t o measured v a l u e a t h e i g h t Hr [ i ]
11
12
13
14
15
16
% 23
%Pr ,
L S1
L S2
L S3
GHz
l i g h t l y densed
= [ −63.9 −64.1
= [ −67.8 −72.9
= [ −71.2 −60.6
%Pr ,
M S1
M S2
M S3
medium densed r a c k
= [ −74.5 −58.0 −60.3 −63.5 −63.4 −57.1 −55.8 −52.9 −56.8 −57.2 − 5 8 . 6 ] ;
= [ −65.6 −60.8 −60.3 −64.5 −59.1 −58.4 −58.8 −60.0 −57.0 −61.4 − 7 2 . 0 ] ;
= [ −83.3 −74.4 −79.3 −76.5 −61.9 −63.1 −65.0 −69.2 −59.6 −61.2 − 6 3 . 9 ] ;
%Pr ,
H S1
H S2
H S3
heavy densed r a c k
= [ −86.5 −83.0 −81.5 −82.6 −85.5 −80.2 −83.5 −80.0 −79.5 −83.5 − 7 5 . 8 ] ;
= [ −82.5 −89.5 −87.0 −82.5 −82.5 −76.2 −90.0 −77.2 −75.9 −76.1 − 7 6 . 7 ] ;
= [ −71.3 −77.9 −75.8 −81.5 −80.8 −75.3 −71.8 −67.9 −76.9 −71.4 − 6 5 . 9 ] ;
% 18
%Pr ,
L S1
L S2
L S3
GHz
l i g h t l y densed
= [ −58.2 −58.3
= [ −70.5 −60.8
= [ −61.3 −68.5
%Pr ,
M S1
M S2
M S3
medium densed r a c k
= [ −76.0 −66.9 −69.5 −61.0 −65.1 −58.2 −69.8 −62.8 −64.9 −58.9 − 6 5 . 0 ] ;
= [ −64.8 −77.5 −62.6 −56.4 −59.8 −70.0 −66.0 −65.0 −60.1 −59.8 − 6 7 . 0 ] ;
= [ −69.5 −75.5 −69.5 −68.5 −57.8 −65.8 −66.5 −68.3 −69.5 −63.3 − 6 1 . 9 ] ;
%Pr ,
H S1
H S2
H S3
heavy densed r a c k
= [ −68.5 −70.5 −81.5 −70.9 −65.0 −63.4 −65.2 −67.1 −83.2 −71.5 − 6 0 . 3 ] ;
= [ −64.0 −72.7 −69.5 −67.8 −72.5 −73.0 −76.0 −88.5 −80.5 −75.0 − 7 3 . 8 ] ;
= [ −87.0 −71.5 −82.5 −77.5 −74.0 −69.5 −82.0 −73.8 −74.0 −78.0 − 7 1 . 5 ] ;
rack
−58.7 −56.2 −54.6 −56.7 −57.3 −60.3 −61.2 −68.5 − 6 5 . 0 ] ;
−63.8 −56.5 −60.0 −61.2 −61.4 −57.3 −57.0 −56.9 − 6 2 . 9 ] ;
−70.0 −57.4 −63.4 −63.1 −59.6 −61.5 −58.0 −54.2 − 5 7 . 9 ] ;
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
rack
−58.4 −52.2 −58.6 −62.9 −60.3 −58.3 −64.9 −65.0 − 7 4 . 5 ] ;
−58.4 −53.3 −66.8 −51.9 −56.8 −57.0 −56.0 −52.0 − 5 7 . 2 ] ;
−69.8 −65.9 −56.8 −59.3 −67.5 −66.5 −66.7 −63.0 − 6 5 . 2 ] ;
33
34
35
36
37
38
39
40
41
42
51
June 25, 2015
B.4
1
APPENDIX B. RAW DATA
Solid Object Attenuation Measurements
%S o l i d Object A t t e n u a t i o n Measurements
2
3
4
5
6
7
8
%Measuring c o n d i t i o n s
Wct = 0 . 9 ;
%c o o l i n g tower width
Sep1 = 2 . 0 + Wct ;
%RX−TX s e p a r a t i o n
Sep2 = 4 . 0 + Wct ;
%RX−TX s e p a r a t i o n
Sep3 = 6 . 0 + Wct ;
%RX−TX s e p a r a t i o n
Disp = [ −1.5 −1.2 −0.9 −0.6 −0.3 0 . 0 0 . 3 0 . 6 0 . 9 1 . 2 1 . 5 ] ; %RX−TX
displacement
9
10
11
12
13
14
15
% 23 GHz
%measured r e c e i v e d power , SN measurement c o r r e s p o n d t o SepN
%SN [ i ] t o d i s p [ i ]
S1 = [ −85.6 −85.0 −91.0 −96.0 −92.0 −85.9 −88.3 −91.2 −93.1
S2 = [ −91.0 −94.0 −91.0 −90.0 −92.0 −93.0 −93.0 −90.0 −89.6
S3 = [ −83.6 −86.0 −93.0 −86.5 −84.0 −83.7 −90.0 −85.0 −91.0
and
−88.7 − 9 1 . 0 ] ;
−90.8 − 8 5 . 7 ] ;
−86.7 − 7 9 . 5 ] ;
16
17
18
19
20
21
22
% 18 GHz
%measured r e c e i v e d power , SN measurement c o r r e s p o n d t o SepN
%SN [ i ] t o d i s p [ i ]
S1 = [ −75.6 −76.9 −80.5 −83.0 −86.0 −87.0 −84.0 −79.0 −82.5
S2 = [ −80.0 −84.3 −79.0 −85.0 −82.7 −85.6 −91.0 −82.0 −87.0
S3 = [ −74.2 −77.3 −74.8 −82.6 −86.0 −84.0 −79.6 −77.9 −80.0
and
−79.6 − 8 5 . 9 ] ;
−85.7 − 7 7 . 8 ] ;
−81.6 − 8 7 . 0 ] ;
52
Appendix C
Leakage Simulation Tool: User
Guide
Introduction
The Leakage Simulation Tool allows the user to simulate and evaluate potential leakage
levels in a 2D environment. The simulation can be defined by the user by using the
customizable options or use one of the the predefined options. The layout of the leakage
simulation tool can be seen in Figure C.1.
Figure C.1: Default layout of the leakage simulation tool
53
June 25, 2015
APPENDIX C. LEAKAGE SIMULATION TOOL: USER GUIDE
Simulation Setup
This section will define the different simulation options available in the leakage simulation
tool.
Preset Model
The preset mode allows the user to quickly simulate different leakage scenarios, allowing
the user to focus on their simulation environment. The preset mode is limited to two
frequency configurations, which can be selected from the pop-down menu in the Preset Model -panel. The preset mode contains empirically derived constants for the given
frequencies.
User Defined Model
Simulating frequencies other than the ones found in the Preset mode can be done in the
User configurable mode. The frequency, path loss exponent and the attenuation constants
can be defined. The frequency is defined in GHz, and the RAF constants is defined in
dB/m.
Room Properties
The simulation environment is defined by the Room Properties panel. Configuring the
size of the simulation environment is done by defining the length, width and resolution
of the environment. The length and width are defined in meters and the resolution can
be set to a 0.3x0.3 or a 1.0x1.0 meter grid resolution.
Leakage Source Properties
The leakage source properties allows the user to define one to three leakage sources by
selecting the number of sources from the pop-down menu. The location of each source is
done by configuring its x- and y-coordinates in the simulation environment. Each leakage
power can be configured individually and is defined in dBm.
54
June 25, 2015
APPENDIX C. LEAKAGE SIMULATION TOOL: USER GUIDE
Layout Generation
After the configurable parameters have been set the environment can be generated by
pressing the Generate Simulation Condition-button. The simulation environment will be
updated and the user can configure the placement of the different objects. Firstly the
lightly populated racks are placed in the environment by left-clicking in the configured
grid. When all locations are marked for each specific density press the Enter key and
the marked points in the grid will turn gray. This procedure is now repeated for medium
and heavily populated rack and finally for solid objects. An environment with light and
medium racks already configured and the heavy rack being marked can be seen in Figure
C.2.
Figure C.2: Simulation environment configuration in progress
With all the objects placed, the program will simulate the configured leakage scenario
and display it in the simulation environment. If multiple sources are simulated the leakage
power contribution from each source is assumed to be fully constructive. If the leakage
levels at any location exceed -10 dBm the program will alert it with a warning in a pupup window. This is an indication that the signal leakage might interfere with equipment
in the vicinity. The user must keep in mind the standard deviation of the model used in
order to properly evaluate the leakage levels, since the leakage simulation tool does not
consider the deviation.
55