Thesis-Portsmouth Uni

M582 MASTER THESIS
Study of Broadband Wireless
Communication in Urban Environment

Submitted By: Saif Al-Shoker
Supervised By: Manish Malik (M.Sc)

Study Broadband Wireless Communication in Urban Environment

University of Portsmouth

Portsmouth/United Kingdom

Master Thesis

Study of Broadband Wireless Communication in
Urban Environment

Submitted By

SAIF AL-SHOKER

Supervised by

MANISH MALIK (M.Sc)

June 2012

In partial fulfillment of the requirements
For the degree of

Master of Science

Page | 2


Page | 3


List of Contents
List of Contents 4
List of Figures and Tables 6
Acknowledgements 7
Chapter One - Introduction 9
1.1 Introduction 9
1.2 Project scope 10
1.3 Aim of mobile systems 10
1.4 Introduction to Cellular Communications 11
1.4.1 Cellular network architecture: 11
1.4.2 Cellular concept: 12
1.4.3 Time line of modern wireless cellular systems: 14
Background Research and Related Work 15
1.5 Free space propagation model: 15
1.6 Radio wave propagation mechanisms: 15
1.7 Reflection: 16
1.7.1 Reflection from dielectrics: 16
1.7.2 Reflection from perfect conductors: 18
1.8 Path Loss Model: 18
1.9 Fresnel zone and Huygen’s Principle: 19
1.10 Cellular Coverage area: 20
1.11 Outdoor Propagation Models: 22
1.11.1 Ray Tracing: 23
1.11.2 Two – Ray Model: 23
1.11.3 Okumura Model: 24
1.11.4 Hata Model: 26
1.11.5 Lee Model: 28
1.12 Multipath and fading in radio channels: 29
1.12.1 Doppler shift: 29
1.12.2 Influence of mobile unit velocity on data transfer and impulse response: 30
1.12.3 Power delay profile: 32

Page | 4


1.12.4 Evaluation of transmission performance of mobile communication systems
in urban environments: 33
1.12.5 Microwave propagation characteristics in the presence of vehicles and
pedestrians: 36
1.12.6 Ray tracing 37
Chapter Two - Methodology 41
2.1 Introduction 41
2.2 Simulation overview 42
2.3 Environmental classification and test route 42
2.4 Measurement Scenario 43
2.5 Structure Characteristics: 44
2.5.1 Dependency on distance 45
2.5.2 Dependency on the Variability of terrain elevation 45
2.5.3 Dependency on the closest surrounding buildings height with respect to
the mobile receiver. Error! Bookmark not defined.
Chapter Three - Simulation 49
3.1 Simulation of models 49
3.2 Path loss in low-rise environment 50
3.3 Comparison of simulation results with cost COST 231 Walfish-Ikegami Model 57
4.1 Analysis of simulation outcomes 61
4.2 conclusion 61
works cited Error! Bookmark not defined.
Appendices 65

Page | 5


List of Figures and Tables

Chapter One

1 Figure (1.1) Basic cellular network [4]. ............................................................................ 11
2 Figure (1.2) Illustration of common used cellular reuse clusters [6] ............................ 13
3 Figure (1.3) Illustration of cellular frequency reuse concept [5]. ............................... 13
4 Figure (1.4) Geometry for the calculation of the reflection coefficients between
two dielectrics [5]. ................................................................................................................. 17
5 Figure (1.5) shape of constant received power [4]...................................................... 21
6 Figure (1.6) Path loss, shadowing and multipath against distance [4]. .................... 22
7 Figure (1.7) two ray Model [4].......................................................................................... 24
8 Figure (1.8), shows motion of the car and the direction of arrival of the wave ........ 30
9 Figure (1.9) shows the total amount of data being transferred at velocity shown in
table (1), calculated without overhead packets [10]. .................................................... 31
10 Figure (1.10) ....................................................................................................................... 34
11 Figure (1.11) ...................................................................................................................... 35
12 Figure (1.12) shows the path-loss characteristics during daytime [12] ..................... 36
13 Figure (1.13) shows the path-loss characteristics during midnight [12] ................... 37
14 Figure (1.14) shows a distribution of buildings, vehicles and trees in an urban
environment [14] ................................................................................................................... 38
15 Figure (1.15) ...................................................................................................................... 39

Chapter Two

16 Figure (2.1) Staircase zigzag (transverse + lateral) and LOS test routes relative to
the street grid ......................................................................................................................... 43
17 Figure (2.2) Model considering homogeneous height and terrain variation ......... 46
18 Figure (2.3) Main rays considered by COS231 model ..Error! Bookmark not defined.

Page | 6


Acknowledgements

Throughout this thesis, I learned patience and dedication. Now I really know
myself, and I know my voice. First and foremost, I would like to express my
gratitude to the two most caring and loving parents in the world, my precious
father Faris Al-Shoker and my mother Aayad for their love, affection and
support. I thank you both for giving me strength and courage to chase my
dreams and to become the man I am today. My sister, my two brothers
deserve my wholehearted thanks as well.

I would like to sincerely thank my supervisor Mr. Manish Malik for sharing with
me his experience and patience. His comments and questions were very
invaluable for completing this thesis.

Finally, I would like to leave the remaining space to thank everyone around
me, my friends and work colleagues, who supported me all the way through
writing this thesis.

Page | 7


CHAPTER 1
Introduction

Page | 8


Chapter One - Introduction

1.1 Introduction

The cellular mobile communications system has grown rapidly as the usage of
mobile services and its applications is increasing, co-channel and adjacent
interference are becoming more significant, many efforts are underway and
become a challenge of many engineers and researchers to develop new
methods, undertake new experiments to find the best way possible to fit in
more users efficiently [1]. “The multipath fading experienced by the signal in
urban environments results in an irreducible error rate due to the interference
caused by the overlapping of time delayed replicas” [1], as well as different
antennas height and antennas with different down tilting and high gain
antennas play an important role for microcellular applications. [2] The
characterization of the urban microcellular channel has been the main
working area of many researchers, radio cellular systems need to be assessed
and evaluated according to the environment of working area, the selection
of multipath propagation parameters needed for the design and
implementation of such systems, is determined according to statistical model
or results of actual implementation [3].

Page | 9


1.2 Project scope

The main objectives of this project are as follows:

To undertake a literature review of research conducted illustrating
the impact of radio communication channels on different urban
environment areas and to find a mathematical formulation for
modeling these types of communication channels.
Propose a method to predict the effect of vehicular and pedestrian
traffic on the characteristics of path loss and delay spread.
To develop a simulation tool to predict those channels and
compare it with available data analysis.

1.3 Aim of mobile systems

To provide good outdoor coverage in different urban areas.
To provide indoor coverage area inside buildings, parks, tunnels and
etc...
Capacity is needed to accommodate more users.
Insure a high quality of service.
No dropped and blocking calls during high speed mobility (e.g., when
driving a car at high speed).

Need of higher data rates for customer satisfaction.

Page | 10


1.4 Introduction to Cellular Communications

1.4.1 Cellular network architecture:

Cellular systems are extremely important worldwide, two-way and data
communication are carried out by cellular phones; this concept was
initially designed to communicate with mobile terminals in vehicles. After
the evolution of these systems, they become more sophisticated to
support lightweight devices known as (cellular phones) which can
operate inside buildings and outside, in open areas and urban
environments, at different speeds [4], the figure (1.1) shows a basic cellular
network:

Base station

Internet
Mobile Telephone
Switching Office
Public Switched
Telephone
Network

Cellular phone

Figure (1.1) Basic cellular network [4]

Page | 11


1.4.2 Cellular concept:

In the past, the idea of telephone mobile system infrastructure was
designed like television broadcasting by providing a high antenna
transmitter covering a wide area surrounding the antenna, but this idea
had limitations in terms of user capacity and spectral congestion [4].

The cellular concept was introduced to overcome this major problem by
replacing the high power antenna transmitter with many low power
transmitters (cells), each cell is required to cover a small area and
assigned a small portion of the total channels, neighboring cells, will be
assigned different groups of channels to keep the interference as low as
possible between cells and mobile users and by systematically spacing
cells and their channel groups. This concept was a huge turn since it
enables the reuse of the same channels by different cells distributed by a
certain minimum distance to avoid co channel interference between
them as shown in figure 1.2, each letter which represents a cell is assigned
a different group of channels and in figure 1.3, cells with the same letter
use the same group of frequency and in this way, will cover more area
and increases capacity usage [5].

Page | 12


G
A F B
A D A
C B E C
B C D

3-Cell 4-Cell 7-Cell

Figure (1.2) Illustration of common used cellular reuse clusters [6]

Figure (1.3) Illustration of cellular frequency reuse concept [5]

Page | 13


1.4.3 Time line of modern wireless cellular systems:

First Generation Cellular Systems

In early 1980s The world witnessed the deployment of first mobile radio
systems, in fact many countries launched first generation cellular systems
after the world allocation Radio Conference (WARC) Signed the approval
of frequency allocations for cellular telephones operating in the 800/900
MHz, starting a new era of cellular systems, based on Frequency division
multiple access (FDMA) [6].

Second Generation Cellular Systems

After launching the first generation cellular systems, many efforts were
made by researchers and engineers to convert all speech into digital
code and in fact, it came into existence by launching the world’s first
digital cellular system (GSM) in late 1992, with higher signal quality.

Many versions of GSM were deployed later on to operate on higher
frequency bands and introducing new features like messaging, voice mail
and caller ID [6].

Third Generation Cellular Systems

Compared to first and second generation, third generation cellular
systems was a turning point in cellular systems history. Internet access, Calls
using VoIP over Internet protocol, unparalleled network capacity,
downloading data, starting web sessions are some of the new features
that 3G offers in a single cellular phone [5].

Page | 14


Background Research and Related Work

1.5 Free space propagation model:

It can be defined as radio signals propagate in the medium from a
transmitter antenna to the receiver antenna without the presence of
interfering terrain and atmospheric anomalies along their path of
propagation [7], a good example of this is the propagation occurred in
space.

The free space loss can be predicted from the well-known equation (1):

(1)

(Where is in km and f is in MHz) [7].

1.6 Radio wave propagation mechanisms:

Radio signals as they propagate in medium, through space usually don’t
experience any reflection, diffraction or scattering but when it comes to
radio signals propagating in urban environments, where there is no line of
sight [5], then they can be attributed to the basic propagation mechanisms
which effect the signal characteristics of the wave, generally speaking can
be defined as follows:
A. Absorption. Can be defined as the decrease in the power level of a radio
wave caused by partial conversion of the energy in radio wave to matter
in the propagation [8].

Page | 15


B. Scattering. Is the process in which a wave is diffused by collisions with
particles they exist in the medium as the wave goes through it [8].

C. Refraction. Is the process in which electromagnetic waves, are deflected when
the waves go through a substance. The wave generally changes direction due
to the variations in the refractive index of the medium [8].

1.7 Reflection:

It occurs when the radio wave travels from one medium to another medium
different in electrical properties and reflection causes changes in the
direction, magnitude, phase and polarization of the incident wave,
depending on the reflection coefficient [5]:

1.7.1 Reflection from dielectrics:

When an electromagnetic wave is incident to a perfect dielectric at an
angle it causes the energy to be partially reflected to the original media
and partially refracted into the second media at an angle and the value
of reflection coefficient varies depending on either the e plane or h plane
is parallel to the reflecting plane. The figure below (1.4), illustrates the
electromagnetic waves as it propagates between two dielectrics media
with subscripts i, r, t refer to the incident, reflected and transmitted fields,
respectively [5].

Page | 16


(a). E- field in the plane of incident [5] (b). E- Field normal to
the plane of incident [5]

Figure (1.4) Geometry for the calculation of the reflection coefficients
between two dielectrics [5]

The reflection coefficients for the previous two cases at the boundary of
two dielectrics are given by the equations (2) and (3) [5]:

(2)

E- Field in the plane of incident.

(3)

E- Field normal to the plane of incident.

Page | 17


Is the intrinsic impedance of the Th medium [5].

1.7.2 Reflection from perfect conductors:

When it comes to reflection by a perfect conductor the electromagnetic
waves cannot pass through it and the electromagnetic waves will
completely and the incident and reflected waves by a perfect conductor
must be equal in magnitude and it can be summarized as follows [5]:

(4)

(5)

(6)

1.8 Path Loss Model:

Most of the prediction models depend on the following path loss equations
(7) and (8) [2]:

P = (7)

= (8)

Where:
PL is the path loss.
is the path loss exponent.

Page | 18


is the wavelength.
are the receiver and transmitter gains, respectively [2].
Is the shortest distance at which free space propagation ceases to
dominate [2].
These models assume that the gain of base station antenna is uniform
throughout the coverage area, which is not the case with high gain antennas
[2].

1.9 Fresnel zone and Huygen’s Principle:

When it comes to conditions under free space propagation, Fresnel zones
can be applied to describe propagation path loss. The wavefront can be
divided into a series of concentric rings, known as Fresnel zones [2], and are
mostly used for suburban and open areas, as the first Fresnel zone indicates
the domination of a direct path [2], on the other hand, huygen’s principle
explains the phenomenon of diffraction, Huygens showed that propagation
occurs along a wave front, with Each point on the wavefront acting as a
source of a secondary wavefront known as a wavelet, with a new wavefront
being created from the combination of the contributions of all the wavelets
on the Preceding front. Importantly, secondary wavelets radiate in all
directions. However, they radiate strongest in the direction of the wave front
propagation and diffraction occurs when these secondary wavelets
propagate into shadowed region around the obstacle [5].
Some facts about using high and low antenna heights in microcellular
systems and can be summarized as follows:

Page | 19


Increasing antenna height will reduce diffraction path loss and this
will be less significant as the distance increases between the
transmitter (base station) and receiver [2].
Down tilting and high sites cannot be used effectively without each
other [2].
Reduction in system interference can be reached by using high
antennas and down tilting, as they can discriminate the boundaries
of an intended coverage area [2].
Path loss can be reduced by using high antennas, consequently
reduces attenuation [2].

1.10 Cellular Coverage area:

In urban environments, buildings and blockage of mobiles are the main
obstacles of radio propagation, shadowing caused by these blockages will
effect some locations within the boundaries of the cell (base station) as it is
designed to cover an area where the minimum received power by
the mobiles should be above SNR for acceptable performance,
consequently, some locations within the cell will have received power below
and other locations will have above , depending on the effect of
shadowing in these locations [4].

All users within the boundaries of a base station cannot receive the same
power level as obstacles by either buildings or being inside a tunnel will cause
the received signal to be below the minimum acceptable received power,
even though it is enough close to the base station [4].

Page | 20


Figure (1.5) shape of constant received power [4]

For a combined path loss and shadowing the ratio received to the
transmitted power in dB is given by the equation (9) [4]:

(9)

is Gauss-distributed random variable with a mean zero, the figure (1.6)
below shows that the decreasing in path loss is relatively linear to with
a slope of dB/ decade and is the path loss and when it comes to
shadowing, the change is more rapid [4].

Page | 21


Figure (1.6) Path loss, shadowing and multipath against distance [4]

For the combined path-loss and shadowing, the outage probability becomes
as in the equation (10) [4].

– (10)

And this is the probability of the received power at a given distance to go
under the minimum received power due to path loss and shadowing and it
plays a significant role in wireless system design [4].

1.11 Outdoor Propagation Models:

Estimating the path loss of radio propagation in urban environments varies in
accordance with the terrain profile, the presence of trees, buildings, movable
obstacles, cars and other objects have a great impact on radio
propagation, some models have been developed to estimate the path loss

Page | 22


and signal strength over different areas, some of them are illustrated below
[5]:

1.11.1 Ray Tracing:

Radio signals in urban or indoor environments will normally experience
reflection, diffraction or scattering and this known to be as multipath signal
and it affects the power, delay in time, shift in phase and/ or frequency,
this eventually causes distortion in the received signal relative to the
transmitted signal [4].

This type of propagation model is retained to be suitable in rural areas,
along city streets when the height of the transmitter and receiver is low
and close to the ground and in indoor environments, when compared to
other empirical models [4].

1.11.2 Two – Ray Model:

Consider a receiver (at a height of ) at a distance d1 from the
transmitting antenna (at a height of ) then it can be assumed that the
received signal is composed of a direct path (d1) and a reflected path
(d2) usually from the ground and this model is useful especially in radio
communications of a distance of few kilometers between tall towers and
received mobile stations, the figure (1.7) shows a basic two ray model and
the equation (11) [5]:

Page | 23


d
Figure (1.7) two ray Model [4]

= - (11)

And when d is large with respect to , then Taylor approximation can
be applied as in the equation (12) [4].

(12)

Finally, the estimated received signal in dB is given by the equation (13)
[4]:

(13)

1.11.3 Okumura Model:

It’s a widely used empirical model for signal prediction from 150 MHZ to
1920 MHZ in urban areas, this type of model is applicable for distances
ranging from (1 km to 100 km) [5].

Page | 24


This model was developed by Okumura who created a set of curves
giving median attenuation relative to free space over an irregular terrain,
between a base station and a mobile antenna, the formula of Okumura
at a distance d can be expressed as in the equation (14) [4]:

=( (14)

Where:

is free space path loss at distance d,

is the carrier frequency,

is the median attenuation plus the free space path loss in all
environments,

is the height gain factor of the base station,

is the hight gain factor of the mobile antenna,

is the gain due to the type of environment,

Some formulas were derived by Okumura for G( ) and G( ) as in the
following equation(15) [4]:

G ( ) = 20 , 30 m 1000 m;

Page | 25


G( )= (15)

1.11.4 Hata Model:

The Hata Model is an empirical formulation of the graphical path loss
provided by Okumura, it is applicable for the frequencies between 150
and 1500 MHZ [4], height of transmitting antenna between 30 m - 200 m,
of received antenna between 1 m – 10 m and distance between 1 km to
20 km [9], the formula developed by Hata for empirical path loss in urban
areas states that (16) [4]:

dB = 69.55 + 26.16 ( 44.9 –

6.55 (16)

Where:

dB is the median path loss for an urban environment expressed
in decibels.

is the carrier frequency in megahertz.

is the transmitting antenna height in meters.

is the receiving antenna height in meters.

D is the distance between transmitting and receiving antennas in
kilometers.

Page | 26


is a correction factor for mobile unit antenna height.

The correction factor of a received antenna height depends on the
coverage area [9] and for a large city it is given by the formula (17) [9] :

= (17)

For a medium sized city is given by the equation (18) [9]:

= (18)

This Model also adds some correction factors as for suburban areas is
given by the equation (19) [9]:

dB = dB - - 5.4, (19)

And in open rural areas which is given by the equation (20) [9]:

dB = dB - – 40.94, (20)

Hata model does not provide correction factors for any path, unlike
Okumura Model, but instead it estimates the Okumura model for distances
d for current cellular systems with smaller cell
sizes and higher frequencies [4], because it is not enough to include PCS
band at 1900 MHz, so an extension to the Hata model was proposed by
the European Cooperative for scientific and Technical Research that will
extend its applicability to 2 GHz [9].

Page | 27


1.11.5 Lee Model:

Lee model is similar to the Okumura and Hata model represented earlier
by providing a method to calculate path loss for standardized conditions,
supported by correction factors to be applicable for conditions different
from the standard. It was developed by members of the Bell Laboratories
technical staff, based upon extensive measurements made in the
Philadelphia, Pennsylvania– Camden, New Jersey, area, and in Denville,
Newark, and Whippany, New Jersey [9].

A standard group of reference conditions and a flat terrain are initially
assumed by Lee Model, followed by correction factors to be added to
calculate the differences from the standard conditions. Lee model can be
applied for frequencies up to 2 GHz [9].

The median received power for Lee model is given by the equation (21)
[9]:

= 10 (21)

is the median received power level in decibels above a mill watt.

is the median received power level at the one-mile reference
range in decibels above a milliwatt.

v is the path-loss exponent for the specific type of area.

d is the total range between the transmitter and receiver antennas.

is the reference range of one mile.

is the correction factor in decibels for system parameters different from
the standard.

Page | 28


1.12 Multipath and fading in radio channels:

Fading occurs due to multipath which effects and changes the amplitude,
phases, or multipath delays of a signal as it propagates over a short period of
time, the effect of fading can be seen more in urban areas where the height
of mobile antennas are well below the surrounding buildings. The signal
received by a mobile can experience reflections from the ground and
surrounding objects which will eventually cause the signal to have a large
number of plane waves with different amplitudes, phase shift and angles [5].

Many existing factors have a great impact on fading in radio propagation
channel, multipath propagation due to reflections and scattering, makes the
transmitted signal to have multiple versions at the receiving side, displaced in
time and spatial orientation, as well as the motion between the base station
and mobile, leads to random frequency modulation due to Doppler shift [5].

1.12.1 Doppler shift:

It can be defined as the change in frequency of a wave that the mobile
receives as it travels from point x to point y having a distance of d and is
given by (22) where [5]:

= = (22)

The previous equation relates “the Doppler shift to the mobile velocity and
the special angle between the direction of motion of the mobile and the
direction of arrival of the wave” as shown in figure (1.8) [5].

Page | 29


The received frequency increases as the mobile moves in the direction of
arrival of the wave and decreases as the mobile moves in the opposite
direction relative to the direction of arrival of the wave [5].

Figure (1.8), shows motion of the car and the direction of arrival of the wave

1.12.2 Influence of mobile unit velocity on data transfer and
impulse response:

In any urban environment is becoming an issue to predict propagation
paths of radio signals, many efforts have been made to come up with
new models and improve existent ones to make them more realistic and
to assist the design process, many factors must be considered such as the
mobility of the mobile unit, mobile speed and the effects of the
surroundings in urban environments [10].

One of the most important characteristics of a mobile unit is that it is not
stable and changes position continuously and this in turn will affect the
amount of data being transferred and received by the mobile unit see

Page | 30


figure (1.9), so it’s vital to consider the possible effects of the receiver unit
movement and its velocity on the amount of data throughput [10].

Figure (1.9) shows the total amount of data being transferred at velocity
shown in table (1.1), calculated without overhead packets [10]

Table (1.1) indicates index to rates of movement table [10]

To analyze the performance of such mobile communication systems, the
impulse response is considered to be a useful characterization of the
channel, and a mobile radio channel can be modeled as a linear filter
with time varying impulse response, as the receiver unit moves along the
ground at a fixed velocity v for a fixed distance d, the channel can be
modeled as a linear time invariant system [5].

Page | 31


Since the impulse response of the linear time invariant channel is a
function of the position of the receiver, then the received signal at a
position d can be defined as in the equation (22) [5] below:

= = , (22)

This is the convolution of the impulse response and the transmitted signal.

1.12.3 Power delay profile:

Seeking new frequency bands has become very important because of
the huge growth and growth of mobile communications in terms of voice,
image and high data rates which is advancing rapidly and understanding
propagation delay is considered to be essential as the one of the major
problems that can effect radio signals as they propagate in urban
environments is the existence of multipath propagation paths with
different and varying time delays.

Normally in any urban environment, a transmission is between a fixed base
station and a mobile and the path is usually blocked resulting in scatter or
reflection from buildings and surrounding objects along the path.

If the mobile unit is moving, it produces a time-varying link and different
Doppler shifts are associated with scatter paths from different angles to
the mobile unit.

Multipath characteristics can be obtained by measuring the complex
band pass impulse response of the radio link as a function of distance,
resulting in delay Doppler power profiles, average power delay profiles,

Page | 32


complex correlation of transfer function variations as a function of
frequency separation, distributions of signal amplitudes at various delays
and different other statistical descriptions of the link which result from the
multipath delays.

1.12.4 Evaluation of transmission performance of mobile
communication systems in urban environments:

The transmission performance of broadband mobile communication
systems operating at megabit-per-second rates is decreased when it
comes to multipath propagation environments due to radio waves
echoes arriving after different delays which interfere the primary radio
signal [11].

A way to mitigate such performance degradation (resulting from the
intersymbol interference (ISI) caused by radio waves having different
delay times longer than the symbol duration) is by transmitting at lower
rates, this is achieved by dividing the source information stream into
several lower-rate channels that will be transmitted at the same time,
using parallel techniques such as orthogonal frequency-division
multiplexing (OFDM) and multi-code code-division multiplexing (CDM)
[11].

To predict the parallel transmission performance in actual environments, it
requires not only the propagation models but also measured impulse
responses and one way to do so is by using equivalent baseband analysis,
nevertheless it is considered to be time-consuming to predict such
performance, since it employs convolution of impulse responses [11].

Page | 33


According to an experiment conducted by a research group (S.
Takahashi, K. Takahashi, H. Masui, K. Kage and T. Kobayashi), they
proposed a theoretical method to estimate the transmission performance
in multipath propagation environment in an efficient way. This method
calculates radio wave-interference probabilities under the assumption
that the impulse responses have uniform-distribution phases [11].

Figure (1.10)

Figure (1.10) [11] shows the dependence of a data rate on transmission
performance at 3.35 GHz and it gives an indication that bare transmission
performance decreases at higher data rate, it also shows that the BER
exceeds when the distance between the transmitter and receiver
exceeds 100 meters and this indicates that anti-multipath techniques are
required for low BER applications. A better transmission performance can
be obtained by increasing the number of parallel transmission channels as
in the previous figure, but the increase requires a wider dynamic range
that causes the performance to decrease due to marginal symbol
detection [11].

Page | 34


Figure (1.11)

Figure (1.11) [11] shows the BER with parallel transmission in 10 channels at
1Mb/s each and compared with BER obtained using bare transmission
and the result is a great reduction in BER with parallel transmission
especially in the close vicinity to the transmitter, but when the BER with
parallel transmission in figure (11) is compared with the bare 1-Mb/s
performance in figure (10), the both BERs are almost the same within a
range of 100 meters [11].

It can be concluded that the parallel transmission is capable of improving
the BER, especially at distances less than 100 meters with respect to the
transmitting antenna, which can be retained to be more suitable for
broadband multimedia systems operating at high data rates up to 10
Mb/s [11].

Page | 35


1.12.5 Microwave propagation characteristics in the presence
of vehicles and pedestrians:

Traffic condition on the streets has a great impact on the behavior of
radio wave signals. According to an experiment conducted by a research
group in an urban area in Tokyo, it shows the effect of vehicles and
people on the characteristics of path loss and delay spread.

The experiment was made in an urban area where the transmitter and
receiver antennas are at low heights, (4) and (2.7, 1.6 two different heights
were considered) m respectively, at two different frequencies of 3.35 GHz
and 15.75 GHz in two different scenarios (at daytime and midnight, where
the number of vehicles passing is less than 1/3 with respect to daytime,
and the average number of pedestrians is less than 1/100 with respect to
daytime) [12].

1 Figure (1.12) shows the path-loss characteristics during daytime [12]

Page | 36


Figure (1.13) shows the path-loss characteristics during midnight [12]

The figure (1.12) shows the path-loss characteristics at height of 1.6 m at
two different frequencies (3.35 and 15.75 GHz) during daytime and figure
(1.13) shows the path-loss during midnight under the same conditions
(without the effect of passing vehicles and pedestrians). After comparing
the results in the previous two figures, it can be noticed that the Break
point moves away from the transmitter at midnight due to less traffic
conditions in the road [12].

1.12.6 Ray tracing

Radio signals in urban or indoor environments will normally experience
reflection, diffraction or scattering and this known to be as multipath signal
and it affects the power, delay in time, shift in phase and/ or frequency,
this eventually causes distortion in the received signal relative to the
transmitted signal [4].

This type of propagation model is retained to be suitable in rural areas,
along city streets when the height of the transmitter and receiver is low

Page | 37


and close to the ground and in indoor environments, when compared to
other empirical models [4].

A typical urban environment consists of buildings, static and moving
vehicles and trees that affect the radio wave propagation. Many papers
have been published discussing the propagation loss, delay spread in
simple environments using ray tracing technique without taking into
account cars, trucks or trees and to obtain a more efficient result, 2D ray
tracing is combined with simple 3D geometric considerations as shown in
figure (1.14) in order to handle any distribution of buildings, vehicles and
trees in an urban environment and their effects [13].

Figure (1.14) shows a distribution of buildings, vehicles and trees in an urban
environment [14]

Page | 38


As shown from the previous figure, buildings, vehicles and group of trees
and the behavior of the ray traveling can take different paths, consider
the projection Txp of a transmitting antenna on ground, depending on
the height of the vehicles and trees ( as they maybe higher or lower than
that of the transmitter), the ray may travel over the top of the vehicles and
trees, may even bounce off the projections of vehicles, trees and buildings
or transmit through the projections of trees and vehicles as shown in figure
(1.15), resulting into different reflected scattered waves. Based on this
idea, a binary reflection/transmission tree for a ray tube shot from Txp is
constructed. For each ray tube, the projection Rxp of the receiver Rx is
checked to see if it falls within the ray tube and if it does, a 2D ray from Txp
to Rxp can be determined. Once it is established, a third dimension is then
taken to determine if an exact 3D ray from to Exists [14] [13].

Figure (1.15)

Page | 39


CHAPTER 2
Methodology

Page | 40


Chapter Two - Methodology

2.1 Introduction

As mentioned earlier in the preceding topics that the behavior of multipath
channels is becoming more unpredictable as many factors play a big role in
defining the nature of these multipath channels along their path, when it
comes to urban environments, signals are affected by buildings, trees, cars
passing, pedestrians, interference with other channels as well as the speed of
either the mobile unit receiver or the objects moving around it. The signal
may bounce of the walls, cars as they pass, penetrate through them and
may take different paths which will cause the signal with different time
delays.

As the demand for high speed transfer of data is increasing, the
characterization of multipath propagation is becoming more difficult and not
easy to measure as it depends mostly on the type of environment, in which a
link has been deployed.

It can be summarized as follows:

1. Conduct research on different urban environments (possibly through
background research) especially in dense areas, where they
necessitate higher data rates and find the most suitable multipath
propagation parameters to use it as a standard model.
2. Find the impact of multipath on the radio propagation channel in
these areas and compare it with available data.
3. Estimate the path loss and delay spread when using high and low
antenna heights for microcellular applications.

Page | 41


4. Develop a simulation tool using MATLAB to predict the behavior of the
channels.

2.2 Simulation overview

Several steps are considered in providing realistic simulation of radio
propagation channels. The first step is to define the area survey of the urban
region that is to be simulated, Based on existent data which is provided and
the purpose of this project is to process the same data collected and
simulate it using Matlab software, compare it with actual measurements
obtained during the experiment, the simulation must consider and satisfy all
parameters taken into account during the experiment, figure (16) illustrates
the different stages of simulation.

According to [15] , measurements were carried out in an urban environment,
has shown that it is not necessarily to have a blockage between the
transmitter and receiver path to cause fading, instead, it can introduce
frequency selective fading of up to 40 dB and this arises another problem
that the existence of objects in the vicinity of radio wave signal, can still have
an effect and cause burst errors in reception.

2.3 Environmental classification and test route

Existent models for prediction of radio propagation are commonly classified
to urban, suburban and rural areas. The latter is characterized with fewer
buildings whose heights range between two to three stories which are widely

Page | 42


separated in comparison to urban and suburban areas. On the other hand,
suburban areas can be classified to commercial/residential and suburban
residential which is a mixture of residential and commercial buildings with
heights above four stories normally.

2.4 Measurement Scenario

Three different measurement scenarios on site with existent data have been
used for simulation, and later to be compared with real measurements, figure
(2.1) depicts the test routs.

Figure (2.1) Staircase zigzag (transverse + lateral) and LOS test routes relative
to the street grid [16]

These measurements were conducted in the San Francisco bay area using
different base station antenna heights which are near or below the

Page | 43


surrounding buildings with operating frequency of 900 and 1900 MHz,
following line-of-sight, zigzag and staircase test routes, which are shown in
figure (2.1) for the site experiment,. Recalling the importance of
understanding the behavior of radio propagation in small cell environments
where the antenna height is expected to be a key factor in the design of PCS
system, three different antenna heights were chosen, the transmitting
antennas of 3.2, 8.7 and 13.4 m, while for the receiving antenna, was chosen
to be at 1.6 m.

2.5 Structure Characteristics:

The working area which is in this case the sunset District and the Mission
District are characterized of attached buildings of quasi-uniform height
structured on a rectangular street grid with a flat terrain profile, the first
location is composed of two-story houses forming a rectangular grid and the
second location is composed of a mixture of different buildings heights,
typically between four to six stories and they were chosen to represent a
typical low-rise environment. While to represent high-rise environments,
measurements were also conducted in San Francisco downtown,
characterized by hills with most buildings being significantly higher than the
highest antenna used. The proposed model was developed as the base
model for characterizing outdoor signal propagation in low-rise and high-rise
environments taking into account some urban parameters: distance, mobile
height, Terrain elevation, and propagation over rooftops, diffraction from the
last rooftop to the mobile and finally presence of corners as new
contributions. These factors are explained in details as follows [16]:

Page | 44


2.5.1 Dependency on distance

It has been theoretically verified how distance variation can influence the
radio propagation, which depends mainly on the topography of the
terrain where the model is applied. This parameter is so significant that a
wrong estimation would result in wrong deductions later [1].

2.5.2 Dependency on the Variability of terrain elevation

Many researchers have extensively analyzed the effect of mobile height
on the attenuation and considered it a well-known factor in radio
propagation. The proposed model has not considered in details to support
variation in terrain elevation especially in downtown San Francisco, as the
terrain in this area has also hills. In order to have a better understanding on
the effect of the terrain elevation, see figure (2.2), where mobile receivers
on low areas are far from the average building height, this in turn will
increase the diffraction angle which would cause the signal to become
lower or higher in case of high areas.

Page | 45


Figure (2.2) Model considering homogeneous height and terrain variation [18]

2.5.3 Dependency on the closest surrounding buildings
height with respect to the mobile receiver

For an ideal urban environment where most of its structure is composed of
buildings, houses, etc, the usage of the height of the closest building
relative to the mobile receiver is theoretically correct. But in some cases it
is not accurate due to the existence of other buildings between the last
building close to the mobile receiver and the base station which obstacles
the line of sight propagation path and causes diffraction.

Taking into account all these factors, a correction factor was generated
to account for the effect of the closest building height relative to the
mobile receiver, so the total path loss was approximated as the sum of ,
and [18], where:

Page | 46


is free space loss

is the path loss associated due to the diffraction from the last rooftop
relative to the mobile receiver.

is the path loss accounted due to the blockage of previous buildings
before the mobile receiver.

Page | 47


CHAPTER 3
Simulation

Page | 48


Chapter Three - Simulation

3.1 Simulation of models

A continuous literature review was carried out by the author throughout the
whole project to familiarize the reader with main subject being addressed. At
the beginning, information was gathered using different sources, mainly from
published journals and books to establish a solid background and to outline
the thesis goals at a later stage. Meanwhile and side by side, a focus search
was conducted mainly on previous published articles proposing the different
models that were developed for radio propagation in urban environments.
Related work was of great benefit as it was utilized to refine the project scope
and to choose suitable data destined for simulation.

As the purpose of this project is to come up with a simulation tool that can be
used to predict the performance of radio channel and compare the results
with experimental measurements, data was chosen from models proposed in
[16]. As discussed earlier, test measurements were conducted using three
different base station antenna heights with operating frequency of 900 and
1900 MHz in urban and suburban areas, the test routes selected were line-of-
sight, zigzag and staircase routes. As explained earlier, the Sunset District and
the Mission District were selected to represent low-rise environments while for
the high-rise environment, San Francisco downtown was chosen for test
measurements.

The simulation of the different formulas developed in [16]will be implemented
under the matlab environment as a set of m-files which contain the different
functions and procedures. Each will be evaluated and simulated separately.
Later in the implementation process, COST 231 W-I model will be computed

Page | 49


using the same set of parameters used during the experimental
measurements in [16]. The results are then compared for further analysis.

3.2 Path loss in low-rise environment

The simulation model is deducted using three path-loss formulas: Staircase,
Transverse and lateral route developed in [16]with operating frequency at
900 and 1900 MHz and these formulas are as follows:

For Staircase route (23):

(23)

For Transverse route (24):

For Lateral route (25):

Page | 50


Where

: Carrier frequency valid for 0.9 < < 2
GHz

: Distance between the transmitter and receiver valid for -8 < <
6m

: Average base station height valid for 0.05 < < 3
km

In the previous test analysis, the average height of the surrounding buildings
has been taken as a significant parameter in deriving the different formulas
for path-loss prediction through the relative relation as follows:

Base station antenna Height ∆h is defined as

∆h = - (26)

Taking into account the sunset district which is mainly composed of houses
with average height of two stories, corresponding to an average height of 8
m, the measurements undertaken were computed using three base station
antenna heights of the values of -4.8 m, 0.7 m and 5.4 m. while in the Mission
district which is mainly composed of three to five story buildings,
corresponding to an average height of 11 m, the values -7.8 m, -2.3 m and
2.4 m were chosen as base station antenna height for the measurements in
the Mission district. Figure (3.1) and (3.2) show the results obtained in the
simulation process at a distance of 1 km as a function of height as well as the
path loss for a distance up to 2000 meters at operating frequency of 0.9 and
1.9 GHz for the previous three formulas of lateral, transverse and staircase
routs. The figure also shows the close result in case of transverse and lateral
routes for the low-raise environment.

Page | 51


Figure (3.1) illustrates path loss as a function of height and distance at 0.9
GHz.

Page | 52


Figure (3.2) illustrates path loss as a function of height and distance at 1.9
GHz.

Page | 53


It can be noticed from the previous two figures obtained after simulation that
the path-loss introduced in the lateral route is considerably lower than the
path-loss introduced in the transverse and staircase routes, as in the figure
(3.3) below, it can be noticed that which denotes the distance from the
last rooftop to the mobile receiver is large in case of lateral route whereas in
transverse and staircase routes are small. In addition, the number of half
screens and the separation between these screens is different for the
different previous routes. It can be seen in [16]that base station antenna
heights which are close to rooftops are not sensitive to irregularities so this
leads that average building separation can be applied. Moreover, path-loss
varies according to the equation as:

(27)

M is equal to the number of screens, so path-loss is not very much dependant
on M especially when it is closed to the cell boundary where M is large. In
light of this, the large value of is considered then to be the main cause for
path loss relative to the lateral route.

Figure (3.3) shows the simplified footprint of townhouses [16]

Page | 54


To account for the effect introduced by , a theoretical correction factor is
used as described in [16]so the distance is taken as 20 m as between the
building edge and the center of the street in case of the Sunset and Mission
districts and using the transverse formula as the standard formula, so the
correction factor is given as follows:

20/ ) (28)

So applying the previous correction factor, so the formula for all non-LOS
routes is given by:

40.67−4.57sgn∆hlog1+∆hlogRk+10log⁡(20/rh ) +20log⁡(∆h m/7.8) (29)

Where, the average building height in Sunset and Mission districts is 7.8
relative to the mobile receiver height of 1.6 m. figure (3.4) and (3.5) illustrate
the path loss results obtained after simulation of the previous formula (29) with
correction factor which is valid for all non-LOS routes and the previous lateral
formula in (25) as a function of height at 1 km distance.

Page | 55


Figure (3.4) Comparison of simulation results at 0.9 GHz

Figure (3.5) Comparison of simulation results at 1.9 GHz

Page | 56


3.3 Comparison of simulation results with cost COST 231
Walfish-Ikegami Model
The results obtained from formula (29) with correction factors for the Sunset
district is now compared with cost 231 model. This model is a combination of
J. Walfish and F. Ikegami model which later was developed by The COST 231
project [17]. This model among all the other models is more suitable for flat
suburban and urban environments that have almost uniform building heights
as it provides additional parameters and correction factors that can be
utilized for different environments. See figure (3.6) below for a typical
environment where this model is valid for path loss calculation.

(3.6) illustrates a typical urban environment where this model is valid for path
loss calculation

Page | 57


In the simulation process, the following data have been use for comparison:

Parameters Used for the Simulation
Building to building distance is 50 m
Street width is 40 m
Orientation angle of the street is 40
Relative base station height with respect to building height is 5 m
Is 18
Is – in the case of urban environment which is valid for
Sunset district
Is 54 which valid for base station antenna height greater than building
rooftop height.
Operating frequency is 900 MHz
Mobile receiver height is 1.6 m
Distance between the transmitter and receiver is 2000 m

The data presented previously was used within the formula of cost 231 model
and taking into account the most suitable parameters that are in close
agreement with data used in the formula found in (29), some of these
parameters were assumed to make the simulation more realistic. As it can be
seen from figure (3.7), which illustrates the path loss in dB encountered using
two different models, cost 231 which is known to be the most suitable model
for path loss calculation in urban and suburban and the formula (29) with the
correction factors added to the latter. The simulation showed differences in
path-loss with discrepancy of around 15-20 dB which is considered to be high.

Page | 58


(3.7) illustrates the path loss model within the non-LOS formula (29) and cost
231 W-I at operating frequency of 0.9 GHz.

Page | 59


CHAPTER 4
Analysis and Conclusion

Page | 60


4.1 Analysis of simulation outcomes

The accumulated results obtained from simulation of the proposed formulas
in [16] which were derived based on the extensive measurements conducted
in field, showed great match as with the three formulas: lateral, transverse
and staircase test routes. Lateral formula output showed significant different
with respect to the transverse and staircase routes, a correction factor has
been added to the transverse formula and has been considered for all non-
LOS routes in low-rise environment. For comparison purposes, the cost 231
model has been simulated using the same set of parameters in accordance
with the formula developed and presented earlier (29). The results obtain
after simulation and comparison as shown in figure (3.7) didn’t show good
agreement, so even the cost 231 model which is considered most suitable for
path-loss prediction in urban and suburban areas, didn’t provide precision in
accordance with the non-LOS formula (29), so hata 231 model cannot be
considered.

4.2 Conclusion

In light of the background research and related work, it can be noticed that
the radio propagation takes a different behavior within each different
operating area and requires the knowledge of its propagation parameters to
successfully design a radio cellular system as many factors influence the
performance of such systems, such as multipath fading, path loss, reflections
from buildings, no direct visibility between transmitter and receiver because
of the low antenna heights compared to the surrounding structures , speed
of the mobile and surrounding objects have also a great impact on the radio
propagation behavior.

Page | 61


As the urban areas become more populated, capacity becomes more
significant to accommodate more users and less probability of errors in data
rate, this will eventually require more cells to be repositioned and causes co-
channel interference to increase and ultimately constrain system capacity
finally, it requires more sophisticated approaches and methods to overcome
such problems.

Page | 62


Works Cited

[1] L. D. K. G. B. K. a. P. C. Athansios G. Kanatas, "A UTD propagation Model in
Urban Microcellular Environments," IEEE TRANSACTIONS ON VEHICULAR
TECHNOLOGY, vol. 46, FEBRUARY 1997.

[2] E. B. a. A. B. sesay, "Effects of Antenna Height, Antenna Gain and Pattern
Downtilting for Cellular Mobile Radio," IEEE transactions on Vehicular
Technology, vol. 45, May 1996.

[3] M. S. a. S. Y. Tsutomu Takeuchi, "Multipath delay prediction on a workstation for
urban mobile radio environment," vol. 36, 1991.

[4] A. Goldsmith, Wireless Communications, Newyork: Cmbridge University Press
2005, 2005.

[5] t. s. rappaport, wireless communications principles and practice, second edition
ed., 2001.

[6] G. L. Stuber, Principles of Mobile Communication, 2nd Edition ed., Georgia:
Kluwer Academic Publishers.

[7] D. H. Morais, Fixed Broadband Wireless Communications: Principles and
Practical Applications.

[8] L. J. I. Jr., Satellite Communications Systems Engineering atmospheric Effects,
Sattelite Link Design and System Performance, 2008.

[9] Bruce A. Black; Philip S. DiPiazza; Bruce A. Ferguson; David R. Voltmer; Frederick
C. Berry, Introduction to Wireless Systems, Prentice Hall, 2008.

[10] D. D. a. G.-M. M. Tim Casey, "Influence of Mobile User Velocity on Data Transfer
in a Multi-Network Wireless Environment," in 9th International Conference on
Mobile and Wireless Communications Networks, Cork, Ireland, 2007.

[11] K. T. H. M. K. K. a. T. K. Satoshi Takahashi, "Performance of Parallel Transmission
Applied to Broadband Mobile Communication Systems in Urban Multipath
Environments," IEEE, pp. 1028-1032, 1999.

[12] M. I. S. T. H. S. a. T. K. Hironari Masui, "Microwave Propagation Characteristics in
an Urban LOS Environment in Different Traffic Conditions," IEEE, pp. 1150-1153,
2000.

Page | 63


[13] S.-C. J. a. S.-K. Jeng, "A Propagation Modeling for Microcellular Communications
in Urban Environments with Vehicles and Trees," IEEE, pp. 1214-1217, 1996.

[14] S.-C. J. a. S.-K. Jeng, "A Novel Propagation Modeling for Microcellular
Communications in Urban Environments," IEEE TRANSACTIONS ON VEHICULAR
TECHNOLOGY, Vols. 46, NO. 4, pp. 1021-1026, November 1997.

[15] K. S. S. T. B. V. a. D. S. D. L. Ndzi, "Wideband Sounder for Daynamic and Static
wireless channel characterisation: Urban Picocell channel Model," Progress in
Electromagnetics Rsearch, vol. 113, pp. 285-312, 2011.

[16] Dongsoo Har, Howard H. Xia and Henry Bertoni, "Path-Loss Prediction Model for
Microcells," IEEE Transactions on Vehicular Technology, pp. 1-10, 1999.

[17] C. A. 231, "cost231," [Online]. Available: http://www.lx.it.pt/cost231/. [Accessed
22 May 2012].

[18] Casaravilla J.,Dutra G., Pignataro N. and Acuna J., "Propagation Model for Small
Macrocells in Urban Areas".

Page | 64


Appendices

Appendix A
Matlab code for low-rise environment for Lateral, Transverse and staircase
test routes at 900 MHz and distance of 1 km as a function of Height.

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Lateral, Transverse and Staircase route Simulation %
% at 1 km distance Formula for Low-Rise Environment %
% as a function of Base Station Antenna Height %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

close all;

clear all;

clc

% Parameters Used in the Simulation

f1=0.9; % Frequency at 0.9 GHz

I=10;
Delta_H =-10.0:0.5:I; % Antenna Range from -10 to 10 meters with step
of 0.5 meter
x = sign(Delta_H); % The sign function

% Note "Simulation computed at distance of 1 kilometer"

%%%%%%%%%%%%%%%%%%%%%%%%%% Lateral Route Path Loss Formula with operating
frequency of 0.9 GHz %%%%%%%%%%%%%%%%%%%%%%%%%%%%

lpmodel=(127.39+31.63.*log10(f1))-
(13.05+4.35.*log10(f1))*x.*log10(1+abs(Delta_H))+(29.18-
6.70.*x.*log10(1+abs(Delta_H)))*log10(1);

%%%%%%%%%%%%%%%%%%%%%%%%%% Transverse Route Path Loss Formula with
operating frequency of 0.9 GHz %%%%%%%%%%%%%%%%%%%%%%%%%%%%

Tpmodel=(139.01+42.59.*log10(f1))-

Page | 65



Spmodel=(137.61+35.16.*log10(f1))-

%%%%%%%%%%%%%%%%%%%%%%%%%% Plot %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

plot(Delta_H,lpmodel,'b.-' ,Delta_H,Tpmodel,'r.-',Delta_H, Spmodel,'g.-');

%%%%%%%%%%%%%%%%%%%%%%%%%% X, Y Axis and Titles %%%%%%%%%%%%%
xlabel ('Relative Antenna Height Range in Meter');
ylabel ( 'Path Loss In dB');
title ( 'Lateral,Transverse and Staircase route Simulation at 1 km
distance');

h = legend('lateral','Transverse','Staircase','1');
set(h,'Interpreter','none')

text(-8,118,'Operating Frequency = 0.9 GHz');

Page | 66


Appendix B
test routes at 1900 MHz and distance of 1 km as a function of Height.

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% at 1 km distance Formula for Low-Rise Environment %
% as a function of Base Station Antenna Height %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

close all;

clear all;

clc


f1=1.9; % Frequency at 1.9 GHz

I=10;
of 0.5 meter

% Note "Simulation computed at distance of 1 kilometer"

frequency of 0.9 GHz %%%%%%%%%%%%%%%%%%%%%%%%%%%%

lpmodel=(127.39+31.63.*log10(f1))-


Tpmodel=(139.01+42.59.*log10(f1))-


Page | 67


Spmodel=(137.61+35.16.*log10(f1))-

%%%%%%%%%%%%%%%%%%%%%%%%%% Plot %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

plot(Delta_H,lpmodel,'b.-' ,Delta_H,Tpmodel,'r.-',Delta_H, Spmodel,'g.-');

title ( 'Lateral,Transverse and Staircase route Simulation at 1 km
distance');



Page | 68


Appendix C
test routes at 900 MHz for an average antenna height of 5 m as a function of
distance.

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Formula for Low-Rise Environment as a function of %
% distance %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

close all;
clear all;
clc


f1=0.9; % Frequency at 900 MHz

N=2;
d=0.0:0.01:N; % Distance Range from 0 to 2 kilometres
Delta_H= 5; % Average Base station Height at 5 meters


frequency of 0.9 GHz %%%%%%%%%%%%%%%%%%%%%%%%%%%%

lpmodel=(127.39+31.63.*log10(f1))-
6.70.*x.*log10(1+abs(Delta_H)))*log10(d);


Tpmodel=(139.01+42.59.*log10(f1))-


Spmodel=(137.61+35.16.*log10(f1))-

Page | 69


%%%%%%%%%%%%%%%%%%%%%%%%%% Plot %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

plot(d,lpmodel,'b.-' ,d,Tpmodel,'r.-',d, Spmodel,'g.-');


xlabel ('Distance between Tx and Rx in kilometers');
ylabel ( 'Path Loss In (dB)');
title ( 'Lateral,Transverse and Staircase route Simulation');

text(1.0,100,'Operating Frequency = 0.9 GHz');

Page | 70


Appendix D
test routes at 1900 MHz for an average antenna height of 5 m as a function of
distance.

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Formula for Low-Rise Environment as a function of %
% distance %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

close all;
clear all;
clc


f1=1.9; % Frequency at 1900 MHz

N=2;
d=0.0:0.01:N; % Distance Range from 0 to 2 kilometers
Delta_H= 5; % Average Base station Height at 5 meters


frequency of 0.9 GHz %%%%%%%%%%%%%%%%%%%%%%%%%%%%

lpmodel=(127.39+31.63.*log10(f1))-


Tpmodel=(139.01+42.59.*log10(f1))-


Spmodel=(137.61+35.16.*log10(f1))-

Page | 71


%%%%%%%%%%%%%%%%%%%%%%%%%% Plot %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

plot(d,lpmodel,'b.-' ,d,Tpmodel,'r.-',d, Spmodel,'g.-');


xlabel ('Distance between Tx and Rx in kilometers');
ylabel ( 'Path Loss In (dB)');
title ( 'Lateral,Transverse and Staircase route Simulation');

text(1.0,100,'Operating Frequency = 1.9 GHz');

Page | 72


Appendix E
Matlab code for comparison of lateral formula and non-LOS formula with
correction factors for the sunset district as a function of height for 1.9 and 0.9
GHz at 1 km distance

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% comparison of lateral formula and non-LOS formula with %
% correction factors for the sunset district as a function%
% of height for 1.9 and 0.9 GHz at 1 km distance %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

close all;
clear all;
clc


f1 = 0.9; % Frequency at 0.9 GHz
f2 = 1.9; % Frequency at 1.9 GHz
I=10;
of 0.5 meter

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 900 MHz %%%%%%%%%%%%%%%%%%%%%%%%%%%%
lpmodel1=(139.01+42.59.*log10(f1))-
4.57.*x.*log10(1+abs(Delta_H)))*log10(1)+ 20*log10( 10./
7.8)+10*log10(20./250);

lpmodel3=(127.39+31.63.*log10(f1))-

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 1900 MHz %%%%%%%%%%%%%%%%%%%%%%%%%%%%
lpmodel2=(139.01+42.59.*log10(f2))-
4.57.*x.*log10(1+abs(Delta_H)))*log10(1)+ 20*log10( 10./
7.8)+10*log10(20./250);

lpmodel4=(127.39+31.63.*log10(f2))-

figure(1);
plot(Delta_H,lpmodel1,'b.-' ,Delta_H,lpmodel3,'r.-');


Page | 73


title ( 'comparison of lateral formula and non-LOS formula with correction
factors');
h = legend('lateral','Non-Los','1');

figure(2);
plot(Delta_H,lpmodel2,'b.-',Delta_H,lpmodel4,'r.-');
title ( 'comparison of lateral formula and non-LOS formula with correction
factors');
h = legend('lateral','Non-Los','1');

Page | 74


Appendix F
Matlab code for comparison of simulation results with cost COST 231 Walfish-
Ikegami Model

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Comparison of simulation results with cost COST 231 %
% Walfish-Ikegami Model %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

close all;
clear all;
clc

%%%%%%%%%%%%%%% COST Walfish-Ikegami (WI) Model%%%%%%%%%%%%%%
%distance between buildings
B=50;
f = 0.9; % Frequency at 0.9 GHz
d =0:0.01:2000; % Distance
%street width B/2
w=40; % Width of the street
%Mobile_Height=h roof-h mobile(15-10/6/3)m we consider h roof is 5 m
Mobile_Height=1.6; % Antenna height in meter for mobile
receiver

%street orientation angel 40 degree
theta=40;
Lori_angle=2.5+0.075*(theta-35);
Lrts=-16.9-10.*log10(w)+10.*log10(f)+20.*log10(Mobile_Height)+Lori_angle;
Lfs=32.45+20.*log10(d)+20.*log10(f);
height_base=5;
%in urban kf is (-4+1.5((f/925)-1))
Lmsd=-18.*log10(1+height_base)+54+18.*log10(d)+(-4+1.5*((f/925)-
1)).*log10(f)-9.*log10(B);
Path_loss_wl=Lfs+Lrts+Lmsd;
Delta_H = 5;
lpmodel1=(139.01+42.59.*log10(f))-
(14.97+4.99.*log10(f))*x.*log10(1+abs(Delta_H))+(40.67-
4.57.*x.*log10(1+abs(Delta_H)))*log10(d/1000)+ 20*log10( 10./
7.8)+10*log10(20./250);

plot(d,lpmodel1,'b.-',d,Path_loss_wl,'r.-');
title ( 'Comparison of simulation results with cost COST 231 Walfish-
Ikegami Model');
h = legend('Low-Rise (Non-LOS)','Cost WI','1');
text(200,0,'Operating Frequency = 0.9 GHz');

Page | 75

Thesis-Portsmouth Uni

Recommended

Recommended

More Related Content

What's hot

What's hot (8)

Similar to Thesis-Portsmouth Uni

Similar to Thesis-Portsmouth Uni (20)

Thesis-Portsmouth Uni