universiti putra malaysia path loss prediction model …psasir.upm.edu.my/5086/1/fs_2007_59.pdf ·...

UNIVERSITI PUTRA MALAYSIA

PATH LOSS PREDICTION MODEL FOR MOBILE RADIO WAVE PROPAGATION INTO A MULTI-FLOORED BUILDING

ZAINAL HAFIZ BIN RAMLY

FS 2007 59

i


By


Thesis Submitted to the School of Graduate Studies, Universiti Putra Malaysia, in Fulfilment of the Requirements for the Degree of Master of Science

December 2007

ii

To:

My dear beloved family…

Thanks for the encouragement, love and support in fulfilling my endeavour…

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Abstract of thesis presented to the Senate of Universiti Putra Malaysia in fulfilment of the requirement for the degree of Master of Science


By


December 2007

Chairman : Zulkifly Abbas, PhD

Faculty : Science

This thesis presents the development of a new path loss prediction model for

mobile communication field due to wave propagation into multifloored building.

Field strength measurements from four different base transceivers (BTS) located

at Universiti Putra Malaysia (UPM) campus and Taman Desa Serdang were

conducted at two buildings using an Advantest U3641 spectrum analyzer and

AHS519-4 log-periodic antenna. A computer program has been developed to

retrieve the measured field strength data from the spectrum analyzer and convert

the values gained to path loss using Agilent VEE software. Line-of-sight

propagation (for open area) and non-line-of-sight propagation (for building wall

obstruction) have been investigated. The measured path loss data have been

compared with the results obtained using various path loss prediction models such

as COST231 line-of-sight (CLOS), COST231 non-line-of-sight (CNLOS),

Gahleitner-Stochastic (GS), Paulsen-Microcell (PMI) and Paulsen-Macrocell

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(PMA). The results demonstrate poor agreement between the predicted and the

true measured path loss. For line-of-sight case; CLOS, GS, PMI and PMA models

have overestimated the path loss as high as 16.1%, 78%, 8.61% and 35.8%

respectively. For non-line-of-sight case; CNLOS, GS, PMI and PMA models have

overestimated the path loss as high as 14%, 91%, 5.56% and 56.17% respectively

in all measurement frequencies. An improved version of the PMI model has been

developed and tested where the mean error values are found to be approximately

2.5% for all the measurement frequencies. In addition, integrated software

UPMIPL for path loss prediction of wave propagation in both line-of-sight and

non-line-of-sight cases has been developed and implemented using Agilent VEE.

The UPMIPL program provides the utility for calculating the signal characteristics

of radio propagation paths and is realized in the run time version.

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Abstrak tesis yang dikemukakan kepada Senat Universiti Putra Malaysia sebagai memenuhi keperluan untuk ijazah Master Sains

JANGKAAN KEHILANGAN LALUAN UNTUK PERAMBATAN GELOMBANG RADIO PERHUBUNGAN BERGERAK

DI DALAM BANGUNAN PELBAGAI ARAS.

Oleh


Disember 2007

Pengerusi : Zulkifly Abbas, PhD

Fakulti : Sains

Tesis ini memperkenalkan pembangunan model baru kehilangan laluan untuk bidang

perhubungan bergerak berpunca daripada perambatan gelombang ke dalam bangunan

berbilang aras. Pengukuran kekuatan medan dari empat tapak pemancar dan penerima

gelombang (BTS) yang bertempat di kampus Universiti Putra Malaysia (UPM) serta

Taman Desa Serdang telah dilakukan di dua buah bangunan dengan menggunakan

penganalisis spektrum Advantest U3641 dan antena berkala log AHS519-4. Satu

pengaturcaraan komputer telah dibangunkan untuk memperolehi data pengukuran

kekuatan medan dari penganalisis spektrum dan menukar nilai-nilai yang diperolehi

kepada kehilangan laluan menggunakan perisian Agilent VEE. Perambatan garisan

pandangan (untuk kawasan terbuka) dan perambatan garisan ketakpandangan (untuk

penghalangan dinding bangunan) telah disiasat. Data kehilangan laluan yang diukur

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telah dibandingkan dengan keputusan yang diperolehi menggunakan pelbagai model

ramalan kehilangan laluan seperti garisan pandangan COS7231 (CLOS), garisan

ketakpandangan COS7231 (CNLOS), Gahleitner-Stochastic (GS), Paulsen-

Microcell (PMI) dan Paulsen-Macrocell (PMA). Keputusan-keputusan

menunjukkan persetujuan buruk di antara kehilangan laluan yang diukur dengan

ukuran sebenar. Untuk kes garisan pandangan; model CLOS, GS, PMI dan PMA

telah melebihi anggaran kehilangan laluan setinggi 16.1%, 78%, 8.61% dan 35.8%

secara berturut. Untuk kes ketakpandangan garisan; model CNLOS, GS, PMI dan

PMA telah melebihi anggaran kehilangan laluan setinggi 14%, 91%, 5.56% dan

56.17% secara berturut di dalam kesemua frekuensi-frekuensi pengukuran. Satu

versi model PMI yang dibaiki telah dibangunkan dan diuji yang mana nilai-nilai

ralat min didapati hampiran 2.5% untuk kesemua frekuensi-frekuensi pengukuran.

Sebagai tambahan, perisian bersepadu UPMIPL untuk ramalan kehilangan laluan

perambatan gelombang di dalam kedua-dua kes pandangan garisan dan

ketakpandangan garisan telah dibangunkan dan dilaksanakan menggunakan

Agilent VEE. Pengaturcaraan UPMIPL membekalkan kegunaan untuk pengiraan

ciri isyarat terhadap laluan perambatan radio dan dilaksanakan di dalam versi

masa larian.

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ACKNOWLEDGEMENTS

All the praise and admiration for Allah, the Almighty, Beneficial and the most

Merciful, who has enabled me to submit this thesis.

The authors gratefully would like to acknowledge all the peoples and organizations

for all their advice, help and support, assists, suggestions, motivations and

encouragement throughout graduate career:

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I certified that an Examination Committee met on DATE OF VIVA to conduct the final examination of Zainal Hafiz B Ramly on his Master of Science thesis entitled “Path Loss Study For Mobile Radio Wave Propagation Into A Multi Floored Building” in accordance with Universiti Pertanian Malaysia (Higher Degree) Act 1980 and Universiti Pertanian Malaysia (Higher Degree) Regulation 1981. The committee recommends that the candidate be awarded the relevant degree. Members of the Examination Committee are as follows:

ZAIDAN ABDUL WAHAB, PhD Associate Professor Faculty of Science Universiti Putra Malaysia (Chairman) IONEL VALERIU CROZESCU, PhD Lecturer Faculty of Science Universiti Putra Malaysia (Internal Examiner) KAIDA MOHD KHALID, PhD Professor Faculty of Science Universiti Putra Malaysia (Internal Examiner) ZAINOL ABIDIN ABDUL RASHID, PhD Associate Professor Faculty of Engineering Universiti Kebangsaan Malaysia (External Examiner)

___________________________________ HASANAH MOHD. GHAZALI, PhD Professor/Deputy Dean School of Graduate Studies, Universiti Putra Malaysia Date:

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This thesis was submitted to the Senate of Universiti Putra Malaysia and has been accepted as fulfilment of the requirement for the degree of Master of Science. The members of the Supervisory Committee were as follows: ZULKIFLI ABBAS, PhD Lecturer Faculty of Science Universiti Putra Malaysia (Chairman) ABDUL HALIM SHAARI, PhD Professor Faculty of Science Universiti Putra Malaysia (Member) MOHD YUSOF SULAIMAN, PhD Professor Faculty of Science Universiti Putra Malaysia (Member)

________________________ AINI IDERIS, PhD Professor and Dean School of Graduate Studies Universiti Putra Malaysia Date: 10 April 2008

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DECLARATION I hereby declare that the thesis is based on my original work except for quotations and citations which have been duly acknowledged. I also declare that it has not been previously or concurrently submitted for any other degree at UPM or other institutions.

__________________________ ZAINAL HAFIZ RAMLY Date:

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TABLE OF CONTENTS

Page DEDICATION ii ABSTRACT iii ABSTRAK v ACKNOWLEDGEMENTS vii APPROVAL viii DECLARATION x LIST OF TABLES xiii LIST OF FIGURES xiv LIST OF ABBREVIATIONS xvi LIST OF PLATES xix CHAPTER 1. INTRODUCTION 1.1

1.1 An Overview of Wireless Communication 1.1 1.2 Objective 1.4 1.3 Scope of Thesis 1.5

2. PROPAGATION PREDICTION MODELS 2.1

2.1 Introduction 2.1 2.2 Maxwell’s Equations 2.1 2.3 Path Loss Definition 2.2 2.4 Propagation in Free Space 2.6 2.5 Propagation over Earth Surface 2.8 2.6 COST 231 models 2.10

2.6.1. COST 231 LOS (CLOS) Model 2.13 2.6.2. COST 231 NLOS (CNLOS) Model 2.18 2.6.3. COST 231 Walfisch-Ikegami LOS (WI) Model 2.19

2.7 Paulsen Macrocell (PMA) model 2.20 2.8 Paulsen Microcell (PMI) Model 2.22 2.9 Stochastic Gahleitner (GS) Model 2.23 2.10 MTS-IMT 2000 Applications 2.25

2.10.1. Building Loss for outdoor to indoor 2.25 3. METHODOLOGY 3.1

3.1 Introduction 3.1 3.2 Measurement Site 3.1 3.3 The Base Station Transmitters 3.5 3.4 Measurement Setup 3.9 3.5 Calibration 3.11 3.6 Calculation the Path Loss from Field Strength Measurement 3.13 3.7 Software Development 3.14

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3.7.1. Data Acquisition Program 3.14 3.7.2. Spectrum Analyzer object 3.14 3.7.3. Path Loss calculation 3.16

4. RESULTS AND DISCUSSIONS 4.1

4.1 Introductions 4.1 4.2 Variation in path loss with floors 4.1

4.21. Reliability of LOS empirical model 4.2 4.22. Comparison between measured and predicted path loss 4.4

4.3 Optimisation to develop a new path loss prediction model 4.38 4.4 Measurement at different site using improve PMI model 4.63 4.5 Uncertainties Analysis 4.93

4.5.1. Distance d uncertainties 4.93 4.5.2. Angle of Incidence Vi Uncertainties 4.94

5. CONCLUSIONS 5.1

5.1. Main Contributions 5.1 5.2. Suggestions for future work 5.2

BIBLIOGRAPHY R.1 BIODATA OF THE AUTHOR B.1

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LIST OF TABLES Table Page

2.1 Indoor coverage from outdoor base station

2.21

2.2 Wall attenuation from different materials

2.22

3.1 Setting of BTS transmitters

3.8

4.1 Standard deviation between measured and predicted path loss

4.3

4.2 a) relative mean error % in line of sight measurement b) relative mean error % in non-line of sight measurement

4.5

4.3 List values and standard deviation

4.36

4.4 Mean error percentage for all distance and transmitters

4.61

4.5 Distance from BTS to K10 building at x=0

4.65

4.6 a) Mean error percentage for all distance and transmitters b) RME result for floor level at x=0

4.90

4.7 Uncertainties in path loss for various distances

4.93

4.8 The uncertainties in path loss for various angles of incidence Vi∆

4.94

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LIST OF FIGURES Figure Page

2.1 Elements of wireless communication system

2.3

2.2 Physical situation for plane earth loss

2.11

2.3 Definition of grazing angle θ and distance D, S and d.

2.14

2.4 Non line of sight scenario when external antenna is located above the building wall.

2.18

3.1 Floor plan of engineering building

3.3

3.2 a) Engineering building b) Measurement location

3.4

3.3 a) K10 building b) Measurement location

3.5

3.4 Floor plan of K10 building

3.6

3.5 UPM campus building and base station location

3.7

3.6 BTS A, B, C and D.

3.9 & 3.10

3.7 Magellan Meridian Global Positioning system.

3.12

3.8 Flow diagram of procedure to implement the calibration.

3.14

3.9 Flow diagram of procedure to determine the path loss

3.15

3.10 DAQ.vee program

3.20

3.11 CPL.vee program

3.21 & 3.22

4.1 Comparison between measured and various LOS empirical path loss model

4.2

4.2 Engineering building

4.4

4.3 Line of sight measurement

4.7 & 4.8

4.4 x=47m away from the end of building (NLOS)

4.10 & 4.11

4.5 x=38m away from the end of building (NLOS)

4.13 & 4.14

4.6 x=29m away from the end of building (NLOS) 4.19

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4.7 x=18m away from the end of building

4.22 & 4.23

4.8 x=9m away from the end of the building

4.26 & 4.29

4.9 x=0 away from the end of the building

4.32 & 4.33

4.10 second floor of engineering building

4,35

4.11 Mean path loss v distance from the end of the building for all floors of engineering building.

4.37

4.12 Comparison between measured, original and improved PMI model at x=45m.

4.45 & 4.44


4.47 & 4.48


4.50 & 4.51


4,53 & 4.54


4.57 & 4.58


4.60 & 4.61

4.18 a) K10 college building b) Schematic view of K-10 building with base stations site located

4.63 & 4.64

4.19 Comparison between measured, original and improved PMI model at x=0.

4.68 & 4.69

4.20 Comparison between measured, original and improved PMI model at x=0.

4.72 & 4.73


4.76 & 4.77


4.80 & 4.81


4.84 & 4.85


4.88 & 4.89

4.25 Variation in path loss uncertainties with distance uncertainties at distance x=47m

4.94

4.26 Variation in path loss uncertainties with angle of incidence uncertainties at distance x=47m

4.95

xvi

LIST OF ABBREVIATIONS jwte Implicit time dependence

Er

Electric field strength vector

Hr

Magnetic field strength vector

Dr

Electric flux induced

Br

Magnetic flux

qρ Charge density

Pr Receive input signal

G Power ratios

L Path loss

PT Effective isotropic transmit power

tP Power delivered to the transmitter antenna

tG Transmitter antenna gain

cR Reflection coefficient due to the ground surface

D Distance between transmitter and receiver

FSL Represent free-space loss

F Represents frequency in Megahertz

rh Receiving antenna with height

S Physical distance between the external antenna and the external wall

Wge Additional loss in dB in the external wall

Wi Loss in the internal walls

θ Angles

Gh Floor height gain in dB/floor

xvii

Ltotal Total path loss from base to mobile

L(d) Empirical path loss model

Lwe External wall attenuation

Lwi Internal wall attenuation

Nw Number of internal walls separating transmitter and receiver

Nf Floor number, ground floor is zero

N Number of external walls relevant for a certain floor

AnP Outdoor transmitter power (in mW)

ew ‘Linear’ wall attenuation factor of external wall

M Number of internal wall categories

mw ‘Linear’ wall attenuation factor of wall category m

mnk Number of walls of category m, traversed by a line drawn from the receiver

sh Height or receiver above ground level

Vi Angle of incidence

Vh Deviation from horizontal plane

MSC Mobile switching centre

HLR Home location register

GTD Geometrical theory of diffraction

BSS Base station subsystem

BSC Base station controller

BTS Base transceiver station

VEE Visual environment engineering

LOS Line-of-sight

xviii

NLOS Non-line-of-sight

PMA Paulsen Macrocell model

PMI Paulsen Microcell model

GS Gahleitner stochastic model

CLOS COST231 line-of-sight model

CNLOS COST231 non-line-of-sight model

GPS Global positioning system

DAQ Data acquisition

PDF Probability density function

EOL End of line

NMTs Nordic mobile telephones

TACS Total access communication system

UPMIPL UPM indoor path loss model

WI Walfisch Ikegami model

RME Relative mean error

PEL Represent earth surface loss

Loutside External path loss

xix

LIST OF PLATES

Plate Page 3.1 Field strength measurement setup 3.12

1.1

CHAPTER 1

INTRODUCTION

1.1 An Overview of Wireless Communication

The first generation mobile system introduced in 1980s was based on analogue

transmission techniques. During that time, there was no worldwide (or even Europe-

wide) coordination for the development of technical standards for mobile

communication. Nordic countries deployed Nordic Mobile Telephones or NMTs,

while UK and Ireland went for Total Access Communication System or TACS, and

so on. In the early stage of wireless communication, roaming was not possible.

The goal of every operator company is to give a good prediction of radio wave

propagation. Since most cellular users spend most of the time inside buildings, the

level of service which they perceives will depend heavily upon the signal strengths

provided inside the building. With the introduction of high-speed multimedia

services, the demand for indoor coverage will become more important. A prerequisite

for improving indoor coverage in a cost-efficient way is the detailed knowledge of the

actual and the planned indoor coverage. This information can be obtained from pre-

dictions or measurements. A widely used approach to forecast indoor coverage in

radio network planning is to use a low-resolution macro-cell model and to apply an

additional indoor penetration margin (Saunders, 1999). With such a procedure,

however, only a rough estimation of indoor coverage is possible. Furthermore, the

only possibility to determine the large-area indoor coverage by measurements is to

1.2

measure each floor in each building individually. This is a very time consuming and

expensive process. In the case of access restrictions to buildings, it is even not

possible to make such measurements. Therefore, a so-called outdoor-to-indoor

coverage prediction method is required, which predicts indoor coverage by outdoors,

BTS. The method has to consider both the complex propagation process occurring

between the BTS and the building as well as the building penetration process itself.

Since the rapid growth of mobile communication technology and increasing number

of users, the path loss prediction models have been developed in order to estimate the

systems capacity and futures needed. Signal penetration into a building is dependent

on the distance of the external base station from the building as well as the effective

radiated power of the base station transmitter. It may also be dependent on both the

frequency and the environments.

Since the transmission between base station and a mobile device is rarely line-of-

sight, the received signal consists of a number of waves reflected from, or a diffracted

around, objects in close proximity to the mobile. The received signal is thus no

deterministic and the resulting propagation models are statistical. Measurements of

the received signal have to be made in areas where radio communication is likely to

be generated or received to evaluate the parameters of these models.

Indoor radio propagation is dominated by the same mechanisms as outdoor such as

reflection, diffraction and scattering. Conditions also are much more variable.

1.3

Example signal levels vary greatly depending on whether interior doors are open or

closed inside a building.

1.2 Problem Statement

Several researchers have proposed path loss models for wave propagation due to base

station transceiver (BTS) into multi-storey building. Outdoor models that describe

wave propagation in open and urban areas are not sufficient, as propagation into

buildings involve more complex multipath structure. The path loss of wave

propagation into building depends on not only the distance between the BTS and the

receiver in building but also on the BTS antenna height and output power, mobile

antenna height and environment local to the mobile. Additionally, the path loss is also

affected by other empirically observed variables such as building structure and layout

of rooms. Theoretical models such as the geometrical diffraction model and uniform

diffraction model are not used in practice as they often display a large error standard-

deviation with respect to empirical models because of spatial offsets (COST231,

1999).

Most of the empirical models including the COST231 model are essentially based on

improvement of earlier models (Saunders, 1999) which are distance-dependency of

the path loss when the mobile is outside the building, plus building factors, which are

included in the model to account for the increase in attenuation of the received signal

observed when the mobile is moved from outside a building to inside. As different

competing empirical models emerge, there is a need to compare the different models

1.4

on the same data. This requires procedures for comparing model predictions with

measurements and with each other.

An up-to-date literature search has been carried out to investigate existence of other

previous works carried out in similar environment in Malaysia. It is found that only

full indoor wave propagation works are reported and their operating frequencies at

2.4 GHz and 60 GHz were meant for WLAN (or HIPERLAN) application not mobile

communication. Their signal sources were all located in the building and which

actually is not similar and thus not similar to the work carried out for this study.

None has been reported to-date in Malaysia about mobile communication “outdoor to

Indoor” propagation where the signal sources were from fully operational commercial

base station transmitters.

1.3 Objective

The objective of this study is to develop a program to convert measured field

strengths to path loss using Agilent VEE graphical programming technique. The

program is especially useful for telecommunication engineers as a cost-effective

solution to obtain path loss values directly from the measured electric field strengths

on any commercial spectrum analyzer without using additional instruments such as

TEMS Cell Planner. The accuracy of the various path loss prediction models for

mobile communication due to wave propagation into multifloored building will be

investigated. The models involve both line-of-sight (LOS) wave propagation from

BTS to building and the non-line-of-sight (NLOS) propagation into the building. The

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