ABSTRACT
This thesis presents the uniform Linear Array model of a simple
adaptive antenna array based on signal-to-interference plus noise
ratio (SINR) maximization.
The SINR was investigated for a conventional narrow band beam
former by varying the number of antenna array elements and
number of interfering signals or users. The results were compared
with that of omni-directional antenna. The graph obtained showed
significant improvement in SINR as the number of antenna elements
increases in the presence of large interferers for odd numbered
array.
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TABLE OF CONTENTS
Title page – – – – – – – – i
Certification – – – – – – – – ii
Approval page – – – – – – – – iii
Dedication – – – – – – – – – vi
Acknowledgement – – – – – – – v
Abstract – – – – – – – – – vii
Table of Contents – – – – – – – viii
List of Tables – – – – – – – – xii
List of Figures – – – – – – – – xiii
CHAPTER ONE: INTRODUCTION
1.1 Background – – – – – – – 1
1.2 Problem statement- – – – – – – 2
1.3 Objective of the work – – – – – – – 3
1.4 Justification – – – – – – – 4
1.5 Scope of the work – – – – – – 5
1.6 Thesis organization – – – – – – 6
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CHAPTER TWO: LITERATURE REVIEW
2.1 Review of past related work – – – – – 8
2.2 Evolution smart antennas – – – – – 10
2.2.1 Omni directional antennas – – – – – 10
2.2.2 Directional antennas and sectorized systems – – 12
2.2.3 Adaptive array antenna development overview of smart
antenna technology – – – – – – 14
2.3 Overview of smart antenna technology – – – 18
2.4 Classification of smart antenna – – – – 20
2.4.1 Switched beam antennas – – – – – 21
2.4.2 Dynamically phased array – – – – – 22
2.4.3 Adaptive array antennas – – – – – 22
2.5 System elements of a smart antenna – – – 24
2.5.1 Smart antenna receiver – – – – – – 24
2.5.2 Smart antenna transmitter – – – – – 28
2.6 Antenna array and array geometry – – – – 31
2.7 Channel model – – – – – – 33
2.7.1 Mean path loss – – – – – – – 34
2.7.2 Fading – – – – – – – – 37
2.7.3 Slow fading – – – – – – – 38
2.7.4 Fast fading – – – – – – – 39
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2.7.5 Flat fading – – – – – – – – 41
2.7.6 Doppler spread – – – – – – – 41
2.7.7 Delay spread – – – – – – – 43
2.7.8 Angle spread – – – – – – – 44
2.8 CDMA system model for uplink – – – – 45
2.10 Benefits of adaptive antenna array – – – – 51
2.12 Adaptive filters – – – – – – – 53
CHAPTER THREE: METHODOLOGY AND SYSTEM ANALYSIS
3.1 Introduction – – – – – – – 56
3.2 Cell model – – – – – – – 57
3.3 Uniform linear array – – – – – – 59
3.4 Fixed weight beamformer – – – – – 61
3.4.1 Signal modeling – – – – – – – 62
3.4.2 Beamformer output – – – – – – – 65
3.5 Signal strength and DOA measurement – – – 68
CHAPTER FOUR
4.1 Maximizing signal-to-interference and noise ratio
Environment – – – – – – – 71
4.2 Summary of results – – – – – – 89
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CHAPTER FIVE
5.1 Summary of achievement- – – – – – 90
5.2 problems encountered and solution. – – – – 91
5.3 Recommendation and suggestion for further research 92
5.4 Conclusion- – – – – – – – 92
References – – – – – – – – – 94
Appendix – – – – – – – – – 101
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LIST OF TABLES
Table 3.1: Signal strength (dBm) and DOA (0
) measurements 69
Table 4.1: SINR when the number of interferers is two – 72
Table 4.2: SINR in the presence of three interferers – – 74
Table 4.3: SINR in the presence of four interferers – – 76
Table 4.4: SINR in the presence of six interferers – – 78
Table 4.5: SINR in the presence of eight interferers – – 80
Table 4.6: SINR in the presence of ten interferers – – 81
Table 4.7: SINR in the presence of 12 interferers – – 82
Table 4.8: SINR of Omni-directional antenna and 2-element
array- – – – – – – – 84
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LIST OF FIGURES
Figure 2.1: Omni directional antenna coverage pattern – 12
Figure 2.2: Sectorized antenna system and coverage pattern 13
Figure 2.3: Block diagram of adaptive array antenna – 20
Figure 2.4: Different smart antenna concepts – – – 23
Figure 2.5: Smart antenna configuration – – – – 25
Figure 2.6: Reception part of smart antenna at BS for uplink 28
Figure 2.7: Transmission part of smart antenna at BS for
downlink – – – – – – – 31
Figure 2.8: Different array geometries for smart antennas – 32
Figure 2.9: Path loss vs. distance for a typical sub-urban area 36
Figure 2.10: Block diagram of base station transmitter. – 46
Figure 2.11: Block diagram of base station receiver – – 47
Figure 2.12: Block diagram of Base station front end – – 48
Figure 2.13: Block diagram of base station dispreading unit
for each user – – – – – – 49
Figure 2.14: Block diagram of sample adaptive filter – – 54
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Figure 3.1: Typical WCDMA mobile environment with sector
antenna at BS – – – – – – 58
Figure 3.2: Proposed WCDMA mobile environment deploying
adaptive beam forming array antenna at BS – 58
Figure 3.3: Geometry of a uniform linear array – – 59
Figure 3.4 Conventional narrowband beamforming array – 63
Figure 3.5: Test bed: B-Division Police Station Awka – – 70
Figure 4.1: SINR vs. No. of antenna elements in the presence of
two interferers. – – – – – – 73
Figure 4.2: SINR vs. No. of antenna elements in the presence of
three interferers. – – – – – – 75
Figure 4.3: SINR vs. No. of antenna elements in the presence of
four interferers. – – – – – – 77
Figure 4.4: SINR vs. No. of antenna elements in the presence of
six interferers – – – – – – 79
Figure 4.5: SINR for the 7 scenarios when d=0.5 – – 83
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Figure 4.6: SINR vs, No. of interferers for omni-directional
antenna and 2-element adaptive antenna array- 85
Figure 4.7: SINR vs. No. of interferers for higher-element array
(M=9 to 12) when d=0.5λ. – – – 86
Figure 4.8: SINR vs. No. of interferers for medium-element arrays
(M= 6 to 8) when d= 0.5λ. – – – 87
Figure 4.9: SINR compared for lower-element array (M=3 to 6)
when d=0.5λ. – – – – – 88
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CHAPTER ONE
INTRODUCTION
1.1 Background
Smart antennas have emerged as one of the leading innovations for
achieving highly efficient networks that maximize capacity and
improve quality and coverage. Smart antennas provide greater
capacity and performance benefits than conventional antennas
because they can be used to customize and fine-tune antenna
coverage pattern to the changing traffic or radio frequency (RF)
conditions in a wireless communication system like the WCDMA
network.
Beam forming (BF) which is a key technology in smart
antenna system is a process in which each user’s signals is
multiplied by complex weight vectors that adjust the magnitude
and phase of the signal from each antenna element [1]. A beam
forming appropriately combines the signals received by different
elements of an antenna array to form a single output. Many
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adaptive algorithms have been developed to determine the optimal
weight vectors of array antenna elements dynamically, based on
different performance criteria. The weight vectors produce the
desired radiation pattern that can be changed dynamically, by
considering the position of users and interferers to optimize the
signal-to-interference and noise ratio (SINR).
1.2 Problem statement
The mobile radio propagation environment places fundamental
limitations on the performance of wireless communication systems.
Signals arrive at a receiver (usually the base station, BS) via a
scattering mechanism and the existence of multipath with different
time delays; attenuations and phases give rise to a highly complex,
time-varying transmission channel. The radio channel in a wireless
communication system is often characterized by multipath
propagation [3]. A fading signal results from interference between
multipath components at the receiver.
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The conventional antenna systems; the omni-directional
antenna and the sectorized systems cannot overcome these
limitations. Omni-directional antenna radiates and receives equally
in all directions. This will result in wastage of power as antenna
patterns are radiated in the direction of undesired users. While
sectorized antenna systems multiply the use of channels which
results in many handoffs between sectors [4], they do not overcome
the major limitations of omni-directional antennas such as filtering
of unwanted signals from adjacent cells. Therefore, the need for an
antenna system that will minimize or overcome these limitations
arises.
1.7 Objective of the work
The specific objectives of this thesis are:
1. Modeling and evaluation of a simple adaptive antenna
array that can form part of a WCDMA BS structure for
improving link capacity.
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2. To investigate the interference and noise reduction
capabilities of an adaptive antenna array.
3. Comparative analysis of omni-directional antenna and
adaptive antenna array based on SINR maximization.
1.8 Justification
There is an ever – increasing demand on mobile wireless operators
to provide voice and high speed data services. At the same time,
these operators want to support more users per BS to reduce overall
network cost and make services available to subscribers.
Unfortunately, because the available broadcast spectrum is limited,
attempts to increase traffic within a fixed bandwidth create more
interference in the system and degrade the signal quality. To
overcome this problem, adaptive antenna array is proposed for BS
transceivers. This work will encourage mobile wireless operators in
Nigeria to consider the option of adopting adaptive antennas at BSs
due to its numerous benefits.
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It will also be useful to scholars who have interest in this area of
study.
1.9 Scope of the work
This work will look at adaptive filtering technique which is the
principle of an adaptive antenna array. A cell model deploying
adaptive antenna array at BS was proposed and a mathematical
model for received signal at the antenna array derived based on
uniform linear array model. The SINR of an adaptive antenna array
was investigated for different antenna arrays for a conventional
narrow band beam former using fixed angles of arrival considering
different scenarios. Real time measurement was carried out at a test
bed to obtain the signal strength and distance of mobile users from
BS used in the evaluation of pathloss model described in chapter
two for a typical WCDMA carrier deploying sectorized antenna at
base station. The angles of arrivals (AOA) obtained from same
measurement are also useful in the evaluation of SINR for adaptive
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antenna. Channel model was considered as Rayleigh flat fading and
antenna noise as additive white Gaussian (AWGN). The simulations
are done in Matlab environment.
1.5 Thesis organization
This thesis is organized into five chapters. Chapter one deals with
the introduction to the research work which includes research
background, research objectives, justification and scope of the work.
In chapter two, past related works were reviewed; evolution,
principles and technologies of smart antenna were explained.
Channel model and the CDMA system model were illustrated.
Adaptive filtering was discussed also as the basis of beam forming.
Chapter three contains methods adopted in the research. Cell
model and signal model for an adaptive antenna array deployed at
BS were provided. The array factor and array response vector at
each element of the array were derived.
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Chapter four deals with system analysis. Here, the SINR was
investigated for different antenna arrays at d=0.5 and 0.75 by
varying the number of array elements and the number of interfering
signals for a fixed weight beam former. The comparative analysis of
omni-direction antenna and adaptive antenna was done in this
chapter.
Chapter 5 is Summary and conclusion. It contains summary of
achievements, problems encountered and solutions,
recommendations and suggestion for future research and
conclusion.
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