UNIVERSITI PUTRA MALAYSIA

ALI KAMIL MARZOOK

FK 2013 126

REDUCED RANK TECHNIQUE FOR JOINT CHANNEL ESTIMATION AND JOINT DATA DETECTION IN TD-SCDMA SYSTEMS

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REDUCED RANK TECHNIQUE FOR JOINT CHANNEL ESTIMATION

AND JOINT DATA DETECTION IN TD-SCDMA SYSTEMS

By

ALI KAMIL MARZOOK

1

Thesis Submitted to the School Graduate Studies, Universiti Putra Malaysia, in

Fulfilment of the Requirements for the Degree of Doctor of Philosophy

May 2013

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2 COPYRIGHT

All material contained within the thesis, including without limitation text, logos,

icons, photographs and all other artwork, is copyright material of Universiti Putra

Malaysia unless otherwise stated. Use may be made of any material contained within

the thesis for non-commercial purposes from the copyright holder. Commercial use

of material may only be made with the express, prior, written permission of

Universiti Putra Malaysia.

Copyright © Universiti Putra Malaysia

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3 DEDICATION

To my ever-encouraging parents…

To my altruistic and beloved wife (Alya)…

To my lovely brother (Jassim) and lovely sisters…

To my lovely sons ( Zahraa, Mohammad, Zainab and Mahdi)…

To my understanding parent in laws ( Uncle Ghazi Darweesh)…

To my supportive siblings…

To my friends…

To every striving muhsin person who is constantly improving aspects of life…

To those who are compassionate towards achieving perfection…

To the consistent pursuers of knowledge aiming for positive change…

A special contribution to my home country Iraq and to Malaysia;

with lots of gratitude…

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Abstract of thesis presented to the Senate of Universiti Putra Malaysia in fulfilment

of the requirement for the degree of Doctor of Philosophy

REDUCED RANK TECHNIQUE FOR JOINT CHANNEL ESTIMATION

AND DATA DETECTION IN TD-SCDMA SYSTEMS

By

ALI K. MARZOOK

4 May 2013

Chairman: Assoc. Prof. Alyani Binti Ismail, PhD

Faculty: Engineering

Time Division–Synchronous Code Division Multiple Access (TD-SCDMA) has been

classified as one of 3G wireless communication systems in the last years. The

physical layers of this system have adopted several advanced technologies, such as:

joint detections, uplink synchronization, and smart antennas, making it capable of

meeting the requirements of 4G systems directly.

One of the essential parameters that affects the performance and reliability of TD-

SCDMA systems in current wireless applications is channel estimation. A novel

channel estimation method is presented in this thesis relying on the reduction of the

rank order of the total channel matrix H. We have exploited the rank deficient of H

to reduce the number of parameters characterizing the channel matrix and model it

with the lower number of parameters that actually require a description of H.

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The adopted reduced rank technique is based on Singular Value Decomposition

(SVD). The proposed method has declared the superiority over the conventional

methods that are being used in the current applications of TD-SCDMA systems. The

Mean Square Error (MSE) and Bit Error Rate (BER) metrics analyzing the channel

matrix precision among the methods is also suggested in this thesis for comparison;

Least square (LS), post-processing, and the proposed reduced rank methods.

In addition, the technique is proposed as a new algorithm for joint channel estimation

of the multi-cell model based on reduced rank technique handling the active users in

serving cell and the strong interferers from the neighboring cells. The new technique

can improve the TD-SCDMA systems with low rank order processing and low

computation complexity. Unlike the conventional models of multi-cell channel

parameters, the channel matrix of reduced rank multi-cell model has been estimated

in parsimony to involve the detected users from the serving and neighboring cells.

This proposed method can acquire and claim a remarkable improvement in the

performance especially under the worst interference situations.

Finally, a smart antenna system has been merged with reduced rank technique to

introduce a robust performance of TD-SCDMA system. A low effective rank order

of ST channel can be adopted to construct the low rank based receiver with low

complexity and remarkable performance.

The simulation results prove that the reduced rank technique of TD-SCDMA systems

can lead to considerable system performance enhancements and can efficiently

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mitigate interference. In single cell networks, rank two based detector has the

pioneered order along SNR and it introduces improvement about 4 dB gained over

the traditional LS full rank based detectors. In multi-cell networks, rank one

estimator is suitable for case one of multi-cell and provide 9 dB enhancement over

the multi-cell LS estimator while; rank two is more suitable for case two of the multi-

cell and provide at least 5 dB enhancement along the SNR axis over the multi-cell

LS estimator. Finally in the ST TD-SCDMA system, rank three based detector

outperforms traditional LS detector by having 4 dB gains at BER of 10-3

with 8

arrays model at 3Km/h. The reduced rank technique is used to control the complexity

of channel estimation. The performance of all the schemes are simulated and

analyzed by using MatLab 7.9 simulator.

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Abstrak tesis yang dikemukakan kepada Senat Universiti Putra Malaysia sebagai

memenuhi keperluan untuk ijazah Doktor Falsafah

PANGKAT DIKURANGKAN TEKNIK UNTUK ANGGARAN SALURAN

BERSAMA DAN BERSAMA PENGESANAN DATA DALAM SISTEM TD-

SCDMA

Oleh

ALI K. MARZOOK

5 Mei 2013

Pengerusi: Prof. Madya Alyani Binti Ismail, PhD

Fakulti: Kejuruteraan

Time Division-Synchronous Code Division Multiple Access (TD-SCDMA) telah

diklasifikasikan sebagai salah satu sistem komunikasi 3G tanpa wayar pada tahun-

tahun yang lalu. Lapisan fizikal system ini telah menerima pakai beberapa teknologi

canggih, seperti pengesanan bersama, penyegerakan pautan atas dan antenna pintar

menjadikan ia mampu memenuhi keperluan sistem 4G secara langsung.

Salah satu parameter terpenting yang memberi kesan kepada prestasi dan

kebolehpercayaan sistem dalam aplikasi semasa tanpa wayar TD-SCDMA adalah

penganggaran saluran. Satu kaedah novel untuk penganggaran saluran bergantung

kepada pengurangan peringkat berpangkat terhadap jumlah saluran matrik H telah

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dibentangkan di dalam tesis ini. Kekurangan peringkat H telah dieksploitasi untuk

mengurangkan bilangan parameter yang mencirikan matriks saluran dan

memodelkannya dengan bilangan parameter yang lebih rendah yang benar-benar

memerlukan penerangan H.

Teknik pengurangan pangkat yang digunakan adalah berdasarkan Singular Value

Decomposition (SVD). Kaedah yang dicadangkan ini telah menyatakan kelebihan

berlebihan kaedah konvensional yang sedang digunakan dalam aplikasi semasa

sistem TD-SCDMA. The Mean Square Error (MSE) dan Bit Error Rate (BER)

metrik menganalisis matriks ketepatan saluran antara kaedah yang juga dicadangkan

di dalam tesis ini untuk perbandingan; Least Square (LS), post processing, dan

cadangan reduced rank kaedah.

Di samping itu, sebuah algoritma baru telah dicadangkan untuk anggaran saluran

bersama untuk model multi-sel yang berdasarkan teknik pangkat dikurangkan

pengendalian pengguna aktif dalam melayani sel dan interferers kuat daripada sel-sel

jiran. Teknik baru ini dapat meningkatkan sistem TD-SCDMA dengan pemprosesan

pangkat rendah dan kerumitan pengiraan yang rendah. Tidak seperti model

konvensional parameter saluran multi-sel yang lain, saluran matriks oleh model

pengurangan peringkat multi-sel telah dianggarkan untuk melibatkan pengguna yang

dikesan dari sel-sel pelayan dan kejiranan. Kaedah yang dicadangkan ini mampu

memperoleh dan menuntut peningkatan prestasi yang luar biasa dalam prestasi

terutama di bawah situasi gangguan yang terburuk.

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Akhirnya, sistem antena pintar telah digabungkan dengan teknik pengurangan

peringkat untuk memperkenalkan prestasi yang teguh dalam sistem TD-SCDMA.

Saluran ST yang mempunyai keberkesanan kedudukan pangkat yang rendah boleh

diguna pakai untuk membina penerima pangkat rendah dengan kerumitan yang

rendah dan prestasi yang luar biasa.

Keputusan simulasi membuktikan bahawa teknik pangkat dikurangkan sistem TD-

SCDMA boleh membawa kepada peningkatan prestasi sistem yang besar dan cekap

boleh mengurangkan gangguan. Dalam rangkaian sel tunggal, pangkat dua pengesan

mempunyai perintah itu bersama-sama mempelopori SNR dan ia memperkenalkan

peningkatan kira-kira 4 dB mendapat lebih LS pengesan pangkat penuh tradisional

berasaskan. Dalam rangkaian multi-sel, pangkat satu penganggar sesuai untuk mana-

mana salah satu daripada pelbagai sel dan menyediakan peningkatan 9 dB lebih

penganggar LS pelbagai bimbit semasa; pangkat dua adalah lebih sesuai untuk kes

dua multi-sel dan menyediakan sekurang-kurangnya peningkatan 5 dB sepanjang

paksi SNR lebih penganggar LS multi-sel. Akhirnya pada ST TD-SCDMA sistem,

pangkat tiga pengesan pengesan melebihi performa LS tradisional dengan

mempunyai keuntungan 4 dB pada BER daripada 10-3

dengan 8 barisan model di

3km/h. Teknik pangkat dikurangkan digunakan untuk mengawal kerumitan anggaran

saluran. Prestasi semua skim adalah simulasi dan dianalisis dengan menggunakan

Matlab 7.9 simulator.

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ACKNOWLEDGEMENTS

Of all that exists in the entire universe, my sheer gratitude is dedicated to no other

than the Most Compassionate Allah S.W.T. Who had Generously Bestowed me a

golden chance to further my doctorate degree in Universiti Putra Malaysia.

I am too touched being fated an ardently obliging beloved wife who is incessantly

empowering my drive towards completing the painstaking processes throughout the

tribulations of the study. In addition to the dynamic spur of enthusiasm, which is

inexplicably bursting from the fierce love I deeply feel for my lovely daughters –

towards the betterment of our future life. So goes to other inspiring family members.

Anyhow, all the way through, I am truly indebted to my flexible but efficient

supervisor: Associate Professor Dr. Alyani binti Ismail for her clear-cut style of

supervision yet promoting students’ freedom of ideas expression to stand upright

with her securing offer of unwavering support – really, I am among the lucky few. In

addition, I wish to express my appreciation to the members of my committee,

Professor Dr. Borhanuddin Mohd Ali, Professor Dr. Sabira Khatun, and Dr. Aduwati

binti Sali for offering their valuable time and comments.

Besides, I definitely will be missing the campus life especially where my best friends

and engineering lab-mates regards, as their existence around is always an experience-

enriching one to the meaning and maturation of my colourful life.

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I certify that a Thesis Examination Committee has met on 17th May 2013 to conduct the final

examination of Ali Kamil Marzook on his thesis entitled "Reduced Rank Technique for

Joint Channel Estimation and Joint Data Detection in TD-SCDMA Systems" in

accordance with the Universities and University Colleges Act 1971 and the Constitution of the Universiti Putra Malaysia [P.U.(A) 106] 15 March 1998. The Committee recommends

that the student be awarded the Doctor of Philosophy.

Members of the Thesis Examination Committee were as follows:

Mohd Nizar Bin Hamidon, PhD Associate Professor

Faculty of Engineering

Universiti Putra Malaysia

(Chairman)

Nor Kamariah Noordin, PhD

Professor Faculty of Engineering

Universiti Putra Malaysia

(Internal Examiner)

Mohd Fadlee Bin A. Rasid, PhD

Associate Professor

Faculty of Engineering Universiti Putra Malaysia

(Internal Examiner)

Nelson Luis Saidanha da Fonseca, PhD

Professor

Instituto de Computacao

Universidade Estadual de Campinas (UNICAMP) Brazil

(External Examiner)

NORITAH OMAR, PhD

Assoc. Professor and 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 Doctor of Philosophy.

The members of the Supervisory Committee were as follows:

Alyani Binti Ismail, PhD

Associate Professor

Faculty of Engineering

Universiti Putra Malaysia

(Chairman)

Borhanuddin Mohd Ali, PhD

Professor

Faculty of Engineering

Universiti Putra Malaysia

(Member)

Aduwati Binti Sali, PhD

Senior Lecturer

Faculty of Engineering

Universiti Putra Malaysia

(Member)

Sabira Khatun, PhD

Professor

School of Computer and Communication System Engineering

Universiti Malasia Perlis

(Member)

BUJANG BIN KIM HUAT, PhD

Professor and Dean

School of Graduate Studies

Universiti Putra Malaysia

Date:

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6 DECLARATION

I declare that the thesis is my original work except for quotations and citations which

have been duly acknowledged. I also declare that it has not been previously, and is

not concurrently, submitted for any other degree at Universiti Putra Malaysia or at

any other institution.

ALI K. MARZOOK

Date: 17 May 2013

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TABLE OF CONTENTS

Page

ABSTRACT iii

ABSTRAK vi

ACKNOWLEDGEMENTS ix

APPROVAL xi

DECLARATION xiii

LIST OF TABLES xvi

LIST OF FIGURES xvii

LIST OF ABBREVIATIONS xxii

CHAPTER

1 INTRODUCTION 1

1.1 Background 1

1.2 Statement of Problem and Motivation 3

1.2.1 Accurate Channel Estimation with Low

Parameters Estimation

1.2.2 High Interference Environments

1.2.3 High Complexity of Smart Antenna Receivers

4

5

6

1.3 Research Aims and Objectives 7

1.4 Brief Methodology 8

1.5 Thesis Scope 10

1.6 Organization of the Thesis 11

2 LITERATURE REVIEW 14

2.1 Background

2.2 3G Wireless Commnication systems

15

18

2.2.1 WCDMA

2.2.2 CDMA 2000

2.2.3 TD-SCDMA

21

22

22

2.3 TD-SCDMA Systems

2.3.1 Time Frame Structure

2.3.2 Wireless Channel and Interference

2.3.2.1 Fading

2.3.2.2 Interferenc

2.3.2.3 Noise

2.3.2.4 Examples: TD-SCDMA Propagation

Enviroments

2.3.3 Features of TD-SCDMA Systems

2.3.3.1 Joint Detection

2.3.3.2 Time Division Duplex (TDD)

2.3.3.3 Uplink Synchronization

2.3.3.4 Smart Antenna

2.3.3.5 Dynamic Chnnel Allocation

2.3.4 Applicatins of TD-SCDMA Systems

2.3.5 TD-SCDMA Transceiver Structure

2.3.5.1 QPSK Modulation

25

25

26

29

31

32

33

35

36

38

39

40

42

43

44

44

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2.3.5.2 Specific Multiplier

2.3.5.3 The Spreading

2.3.5.4 The Scrambling

2.3.5.4 The Pulse Shaping

45

47

49

49

2.4 Singular Value Decomposition (SVD)

2.4.1 The principle of SVD

2.4.2 Low Rank Approximation by SVD

2.4.3 Hardware Implementation of SVD

2.4.4 The Applications of SVD

50

50

51

55

56

2.5 Smart Antenna System 58

2.5.1 Smart Antenna Structure

2.5.1.1 Antenna Arrays

2.5.1.2 Beamforming Network

2.5.1.3 Signal Processing Unit

2.5.1.4 Advantage of Smart Antenna

2.5.1.5 Examples on Smart Antenna

59

61

61

66

68

70

3 REDUCED RANK TECHNIQUE FOR SINGLE CELL

TD-SCDMA SYSTEMS 74

3.1 Introduction 74

3.2 Single Cell Model of TD-SCDMA Systems 76

3.2.1 Backgroung 76

3.2.2 Midamble Model

3.2.3 Data Model

78

81

3.3 Joint Channel Estimation

3.3.1 LS and MMSE Estimators

3.3.2 Post Processing Estimators

84

84

86

3.4 Reduced Rank Channel Estimation

3.4.1 Problem Formulation

3.4.2 Reduced Rank Model

3.4.3 Analysis and Performance

3.5 Multi User Joint Detection

3.6 Simulation Results

3.6.1 Simulation 1

3.6.1 Simulation 2

3.7 Summary

88

88

89

92

93

95

96

106

116

4 REDUCED RANK TECHNIQUE FOR MULTI-CELL

TD-SCDMA SYSTEMS 117

4.1 Introduction 117

4.2 Problem of Single-Cell Joint Channel estimation in

Multi-Cell Uplink 119

4.3 Multi-Cell Model of TD-SCDMA Systems 120

4.3.1 Midamble Model

4.3.2 Data Model

120

124

4.4 Multi-Cell Joint Channel Estimation 126

4.5 Multi-Cell Reduced Rank Channel Estimation 129

4.6 Multi-User Joint Detection of Multi-Cell Model 132

4.7 Simulation Results

4.7.1 Simulation 1

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4.7.2 Simulation 2

4.8 Summary

146

154

5 REDUCED RANK TECHNIQUE FOR SPACE-TIME

CHANNEL ESTIMATION AND DATA DETECTION OF

SMART ANTENA TD-SCDMA SYSTEMS 155

5.1 Introduction 155

5.2 ST Channel Model 156

5.3 System Model

5.3.1 Midamble Model

5.3.2 Data Model

160

160

162

5.4 Reduced Rank ST Channel Estimation 166

5.5 Selection of TD-SCDMA System Rank Order 172

5.6 Smart Antenna Beamforming and Data Detection

5.6.1 LS Block Linear Equalizer

5.6.2 Minimum Variance Distortionless Response

(MVDR) Block Linear Equalizer

174

175

176

5.7 Multiple Rank Based Receiver for ST TD-SCDMA

System

177

5.8 Simulation Results

3.6.1 Simulation 1

3.6.1 Simulation 2

3.6.1 Simulation 3

179

179

184

187

5.9 Summary 191

6 CONCLUSIONS, CONTRIBUTIONS AND FUTURE

RESEARCH DIRECTIONS 192

6.1 Conclusions 192

6.2 Contributions

6.2.1 Improved the accuracy of channel Estimation

and Data Detection of TD-SCDMA Systems

6.2.2 Reduce the Complexity of Multi-Cell Joint

Channel Estimation and Enhance the System

Performance

6.2.3 Introduce a Robust Smart Antenna Receivers for

ST TD-SCDMA Systems

194

194

195

195

6.3 Future Research Directions 196

REFERENCES 198

APPENDICES 209

BIODATA OF STUDENT 225

LIST OF PUBLICATIONS 226

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LIST OF TABLES

Table Page

2.1

Specifications of 3G standards

24

2.2 Characteristics of the TD-SCDMA Channels for ITU Standard 33

2.3 The MPSK modulation that proposed for TD-SCDMA systems 1.28

Mcps option.

45

2.4 The values of the multiplier corresponding for each channelization

code

46

3.1 Simulation parameters of TD-SCDMA system

96

3.2 Scenarios of user’s movements

97

3.3 The channel taps value for different estimators 98

3.4 ITU Indoor and Vehicular channels parameters

107

AC.1 BER Values for Conventional and re-Simulated LS Estimators for

Single Cell Networks

214

AC.2 BER Values for Conventional and re-Simulated LS Estimators for

Multi-Cell Networks

215

AC.3 BER Values for Conventional and re-Simulated LS Estimators for

Smart Antenna System

216

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LIST OF FIGURES

Figure Page

1.1 Brief Methodology

9

1.2 Study Module

10

2.1 IMT-2000 Radio Interference Standards

20

2.2 IMT-2000 Spectrum Allocation in Different Countries 21

2.3 Radio Frame, Subframe, and Time Slot Physical Structure for 1.28

Mcps Option of TD-SCDMA Systems

26

2.4 The Umbrella Coverage of TD-SCDMA Systems. 35

2.5 Elaborated the Joint Detection Process Among K Users.

37

2.6 (a) The Transmission Frame Allocation and Frequency Band of

FDD (Employed by WCDMA and CDMA2000 Systems) and (b)

TDD Operation (Employed by TD-SCDMA Systems).

39

2.7 The Uplink/Downlink Synchronization Problem

40

2.8 The Smart Antenna Strategy

41

2.9 Dynamic Chanel Allocation 42

2.10 The TD-SCDMA Transceiver Structure

44

2.11 OVSF Spreading Code

47

2.12 The Structure of Diagonal Matrix (Г) with Low Rank

Approximation

52

2.13 The Reduced Rank Approximation with Hypothetical Channel

Model; Colour Scale Denotes to the CIR as a Function of the

Number of Users (K) and Channel Length

54

2.14 The Block Diagram of SVD Algorithm with M Effective Singular

Values

55

2.15 The Hardware Implementation Architecture of SVD

56

2.16 The Principle Parts of Smart Antenna System 59

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2.17 Typical Structure of Adaptive Smart Antenna System 60

2.18 Beamforming Network with Adaptive ULA Structure 63

2.19 The Geometry of UCA Antenna

64

2.20 Pattern Using MVDR Method for Example 1

72

2.21 Beam Pattern Using LMS and RLS Methods for Example 2

72

2.22 Convergence Performance of LMS and RLS Algorithms for

Example 2.

73

2.23 The Main Lob and Side Lobes in Polar Diagram for Example 2 73

3.1 Generation of Midambles for Different K Users 78

3.2 Structure of System Matrix A 84

3.3 The Flow Chart of Post Processing Method 87

3.4 CIR of 1st User vs. Channel Length, W=16 chips, for Scenario 1(3

km/h)

99

3.5 CIR of 1st User vs. Channel Length, W=16 Chips, for Scenario

2(120 km/h)

99

3.6 The MSE vs. Eb/No in dB for Scenario 1 (3km/h) 101

3.7 The MSE vs. Eb/No in dB for Scenario 2 (120km/h) 101

3.8 The Correlation Coefficient vs. Eb/No in dB for Scenario 1 (3km/h) 103

3.9 Correlation Coefficient vs. Eb/No in dB for scenario 2 (120km/h)

103

3.10 The BER vs. Eb/No in dB for Scenario 1 (3km/h).

105

3.11 The BER vs. Eb/No in dB for Scenario 2 (120km/h) 105

3.12 CIR Using Multiple Ranks (r = 1 and r = 2), Steiner and Post

Processing Estimators vs. Channel Length, W = 8 Chips, According

to Scenario 1 (3 km/h) for All Users (K = 16)

108

3.13 CIR Using Multiple Ranks (r = 1, r = 2, r = 3 and r = 4), Steiner and

Post Processing Estimators vs. Channel Length, W = 8 Chips,

According to Scenario 2 (120 km/h) for All Users (K = 16)

108

3.14 The MSE vs. Eb/No in dB for Scenario 1 (3 km/h)

110

3.15 The MSE vs. Eb/No in dB for Scenario 2 (120 km/h) 110

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3.16 The MSE vs. Eb/No in dB under ITU standard for Indoor B channel

(3 km/h) Results

112

3.17 The MSE vs. Eb/No in dB under ITU Standard for Indoor B

Channel (3 km/h)

112

3.18 Correlation Coefficient vs. Eb/No in dB Under ITU Standard for

Indoor B Channel (3 km/h) 113

3.19 Correlation Coefficient vs. Eb/No in dB under ITU Standard for

Vehicular channel (120 km/h).

113

3.20 The BER vs. Eb/No in dB under ITU standard for Indoor B channel

(3 km/h)

115

3.21 BER vs. Eb/No in dB Under ITU Standard for Indoor B Channel (3

km/h)

115

4.1 Multi-Cell Model 118

4.2 Block Diagram of Transmitter / Receiver Multi-Cell TD-SCDMA

System with Reduced Rank Channel Estimator in the Receiver Side 123

4.3 The Flow Chart of Reduced Rank Channel Estimation for Multi-

Cell Model

131

4.4 The Normalized MSE vs. Eb/No in dB at (SIR= -15 dB) for

Scenario 1 (3 km/h)

136

4.5 The Normalized MSE vs. Eb/No in dB at (SIR= - 10 dB) for

Scenario 1 (3 km/h)

137

4.6 The Normalized MSE vs. Eb/No in dB at (SIR= -5 dB) for

Scenario 1 (3 km/h)

137

4.7 The Normalized MSE vs. Eb/No in dB at (SIR= -15 dB) for

Scenario 2 (120 km/h)

140

4.8 The Normalized MSE vs. Eb/No in dB at (SIR= - 10 dB) for

Scenario 2 (120 km/h)

140

4.9 The Normalized MSE vs. Eb/No in dB at (SIR= -5 dB) for

Scenario 2 (120 km/h)

141

4.10 The BER vs. Eb/No in dB at (SIR= -15 dB) for Scenario 1 (3 km/h) 142

4.11 The BER vs. Eb/No in dB at (SIR= - 10 dB) for Scenario 1 (3 km/h) 143

4.12 The BER vs. Eb/No in dB at (SIR= -5 dB) for Scenario 1 (3 km/h)

143

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4.13 The BER vs. Eb/No in dB at (SIR= -15 dB) for Scenario 2 (120

km/h)

144

4.14 The BER vs. Eb/No in dB at (SIR= - 10 dB) for scenario 2 (120

km/h)

145

4.15 The BER vs. Eb/No in dB at (SIR= - 5 dB) for scenario 2 (120

km/h)

145

4.16 The Three Dimensional Plots of the Individual CIR of the

Transmitted Active Users for the First User Throughout Different

Types of Multi-Cell Estimators for scenario 1 Indoor Channel (3

km/h)

147

4.17 The Three Dimensional Plots of the Individual CIR of the

Transmitted Active Users for the First User Throughout Different

Types of Multi-Cell Estimators for scenario 2 Vehicular channel

(120 km/h)

148

4.18 The Normalized MSE vs. SNR in dB at (SIR= -12 dB) for Scenario

1 Indoor Channel (3 km/h) 150

4.19 The Normalized MSE vs. SNR in dB at (SIR= -12 dB) for Scenario

2 Vehicular Channel (120km/h) 150

4.20 Correlation Coefficient vs. SNR in dB at (SIR= -12 dB) for

Scenario 1 Indoor Channel (3km/h) 151

4.21 Correlation Coefficient vs. SNR in dB at (SIR= -12 dB) for

Scenario 2 Vehicular Channel (120km/h) 152

4.22 The BER vs. SNR in dB at (SIR= -12 dB) for Scenario 1 Indoor

Channel (3km/h) 153

4.23 The BER vs. SNR in dB at (SIR= -12 dB) for Scenario 2 Vehicular

Channel (120km/h) 153

5.1 Multiple Antenna Model for the Uplink of TD-SCDMA System

with K Users and M Antennas 161

5.2 ST Rank Three Based Multiuser Receiver for Indoor 3GPP

Channel. 178

5.3 The MSE vs. SNR for Scenario 1 Indoor Channel of 3GPP ST TD-

SCDMA System 181

5.4 The MSE vs. SNR for Scenario 2 Vehicular Channel of 3GPP ST

TD-SCDMA System 181

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5.5 The BER vs. SNR for Scenario 1 Indoor Channel of 3GPP ST TD-

SCDMA System 183

5.6 The BER vs. SNR for Scenario 2 Vehicular Channel of 3GPP ST

TD-SCDMA System. 183

5.7 The MSE vs. SNR for Indoor Channel of ITU ST TD-SCDMA

System 185

5.8 The MSE vs. SNR for Vehicular Channel of ITU ST TD-SCDMA

System 185

5.9 The BER vs. SNR for Indoor Channel of ITU ST TD-SCDMA

System. 186

5.10 The BER vs. SNR for Vehicular Channel of ITU ST TD-SCDMA

System 187

5.11 The Performance of MSE vs. SNR for Different Number of

Antenna Arrays for Scenario 1 (3 km/h) of 3GPP Standard ST TD-

SCDMA System 189

5.12 The Performance of MSE vs. SNR for Different Number of

Antenna Arrays for Scenario 2 (120 km/h) of 3GPP Standard ST

TD-SCDMA System 189

5.13 The Performance of BER vs. SNR for Different Number of Antenna

Arrays for Scenario 1 (3 km/h) of 3GPP Standard ST TD-SCDMA

System 190

5.14 The Performance of BER vs. SNR for Different Number of Antenna

Arrays for Scenario 2 (120 km/h) of 3GPP Standard ST TD-

SCDMA System 190

AC.1 Conventional Single Cell LS Validation. 213

AC.2 Conventional Multi-Cell LS Validation. 214

AC.3 Conventional Smart Antenna LS Validation. 215

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LIST OF ABBREVIATIONS

1G First Generation

2G Second Generation

3G Third Generation

3GPP Third Generation Partnership Project

4G Forth Generation

AWGN Additive White Gaussian Noise

BER

BS

BSC

Bit Error Rate

Base Station

Base Station Controller

CDMA 2000 Code Division Multiple Access 2000

CIR

DCA

DFT

Channel Impulse Response

Dynamic Channel Allocation

Discrete Fourier Transform

DL

DSP

DS-UWB

FDD

DownLink

Digital Signal Processor

Direct Sequence-Ultra Wide Band

Frequency Division Duplex

FFT

FPGA

GSM

Fast Fourier Transform

Field Programmable Gate Array

Global System Mobile

ICI Inter-Cell Interfering

IFFT Inverse Fast Fourier Transform

IMT-Advanced International Mobile Telecommunications-Advanced

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ISI Inter symbol Interference

JD

IoT

Joint detection

Internet of Things

ITU

LOS

International Telecommunication Union

Line Of Sight

LS

LTE

Least square

Long Term Evolution

MAI

MIMO

Multiple Access Interference

Multi Input Multi Output

MMSE Minimum Mean Square Error

MMSE-BLE

MS

Minimum Mean Square Error Block Linear Equalizer

Mobile Subscriber

MSE Mean Square Error

MVDR

PoC

Minimum Variance Distortionless Response

Push to Talk over Cellular

SIR Signal to Interference Ratio

SNR

RRC

SAR

Signal to Noise Ratio

Root Raised Cosine

Synthetic Aperture Radar

ST Space Time

SVD Singular Value Decomposition

TD-SCDMA Time Division–Synchronous Code Division Multiple

Access

TD Time Division

TDD Time-Division Duplex

TSVD Truncated Singular Value Decomposition

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TDMA

Time Division Multiple Access

UL

VoIP

UpLink

Voice over IP

WCDMA

WSN

Wideband Code Division Multiple Access

Wireless Sensor Networks

ZF Zero Forcing

ZF-BLE Zero Forcing Block Linear Equalizer

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CHAPTER 1

1. INTRODUCTION

1.1 Background

From the beginning of the first generation (1G) lunch, there has been a tremendous

rapid development in mobile services and mobile systems become, with the dawn of

a new century, wireless communications has made it increasingly possible for people

to communicate anywhere and anytime owing to new services and more

sophisticated applications than there used to be [1]. It is predicated that future

services in wireless communications systems will increase the popularity of mobile

devices and motivating the development of various mobile applications. The rapid

growth in data communication has invited the need for high bit rates in the

communications systems to provide “wideband” contents such as video and audio

streaming [2].

After the 3G systems have been standardized, the interest of the research bodies has

gone beyond 3G and 4G systems aiming to operate at a much higher data rate

(100Mbps or even 1Gbps) [3]. In order to provide high-data-rate services that

deploys the new 4G system applications, communication designers and suppliers

have adopted two ways. The first group which has suggested and tried to create new

radio access technology, is currently engaged to several research programs such as

China’s FuTURE and the European MATRICE [4]. One of the principle challenges

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they are facing is the monetary issue as billions of dollars are required to build a new

cellular system. In addition to that, smooth migration from the old generation to the

next generation and matching with the current devices that have the ability to support

the new generation is another challenge [5].

Besides that, the second group has proposed the possibility of depending on the

current 3G systems infrastructure. They are attempting to improve the system

performance by solving the challenges and the open issues and focusing on

vigorously push of the boundaries on the maximum rate at which information can be

transmitted over the wireless communication systems.

There are many reasons are behind this motivation; the issue of cost involved in the

first rank, avoiding the migration and the coexisting problems between the two

generation systems. One of the major reasons that has motivated the second group is

advanced characteristics found in 3G systems (TD-SCDMA is our system that we

will try to develop some of the features) that can be directly applied to 4G systems.

TD-SCDMA system is considered as one of the promising multiple access

techniques which can be combined with Time Division (TD). The motivated features

of this system such as Time-Division Duplex (TDD) allows the flexible allocation of

the ratio between DownLink (DL) and UpLink (UL), which gives it a flexibility of

usage to handle both symmetric traffics (such as voice) and asymmetrical services

(such as mobile Internet access) [6-8]. Adding to that, the suitability for different

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deployment scenarios: from indoor to outdoor and from rural area to dense urban

area with user mobility from pedestrian to vehicular. The air interface of 4G will be a

mixture of mature technologies used in 3G and newly developed ones targeting

higher data rates.

Our vision of a 4G system is to have a set of improved the features of TD-SCDMA

systems and exploiting the advanced characteristics such as joint detection and smart

antenna, and flexible DL and UL capacity allocation. Besides, solving the problems

that are encountered to eliminate their performances with low complexity system and

high accuracy outage will make the TD-SCDMA a strong candidate for the evolution

of 4G system.

This chapter is organized as follows. Initially, the problem statement of the thesis is

discussed. It is followed by the thesis objectives and the scope covered in this thesis.

Finally, the organization of the thesis is presented.

1.2 Problem Statement and Motivation

Addressing various challenges and open issues such as, increasing the system

capacity, estimating accurate channel with reliable system, managing interference

mitigations, achieving higher data rate, etc, guarantees fixable and seamless

migration from the present 3G systems to the next 4G systems with applications

relying on the infrastructure of the present 3G systems, in order to present efficient

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TD-SCDMA systems to deploy the requirement of the future wireless

communications, as well as the limitation of the current research for the TD-SCDMA

systems performance describe in the next subsections:

1.2.1 Accurate channel estimation with low parameters estimation

One of the essential parameters affecting the performance and reliability of TD-

SCDMA systems in current wireless applications is channel estimation.

Theoretically, the main concerns in the channel estimators design are the accuracy of

the estimation and the simplicity of the hardware. A poor estimation degrades the

quality of the existing mobile communication systems, and increases their mean

square error measure of the system; in addition to that, increase the BER of multi-

user joint detector that based on a provision of precise joint channel estimation.

It is known that the channel estimation in TD-SCDMA systems requires the

knowledge of the entire number of channels between the transmitter (mobile station)

and the receiver (base station) and vice versa. Usually, this channel is estimated by

using an embedded training sequence or midambles (for example, 144 bit in the 1.28

Mbps option of TD-SCDMA systems) in each transmitted slot of data. However, this

estimation may be inaccurate on account of the large number of parameters that

requires estimation along short training sequence. Moreover, the estimation must be

made adaptive to coping with the rapid variations in the physical channel, especially

at high users' mobility.

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In addition, the estimation of full rank channel matrix parameters requires more

processing time; especially with densely populated areas where the planning

networks optimizers try to increase the system capacity by sharing the one time slot

with large number of users (a maximum of 16 users per time slot), which ultimately

increases the number of parameters that are needed to estimate the channel of each

user. In contrast, the total channels of entire system will become more complicated

and the processing time will be increased.

1.2.2 High interference environments

On the move, as the demand for high data rate mobile applications continues to rise,

cellular networks and mobile hardware designers seek to push vigorously the

boundaries at the maximum rate where data can be transmitted over wireless

communication channels.

The accuracy of channel estimation in TD-SCDMA systems is related to the

interference level (inter- and intra- interference). The current channel estimators

consider the Inter-Cell Interfering (ICI) signal as white noise added to the intra-

interference (Multiple Access Interference (MAI) and Inter symbol Interference (ISI)

and fading channel, which together degrades the precision performance of channel

estimators. The multi-cell channel estimation is an effective solution to obtain the

better knowledge of the Channel Impulse Response (CIR), by including the signals

of the strongest interfering users from neighbouring cells into the channel estimation.

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In this thesis, the proposed channel estimation method is based on the Singular Value

Decomposition (SVD) for multi-cell networks of the TD-SCDMA system tested

under 3GPP and ITU standards that describe the channel environments of the TD-

SCDMA system at indoor and vehicular channels. The channel matrix of each

scenario has correlated coefficients that cause a reduction in the effective number of

degree of freedom and the number of estimated parameters that really need it to

describe the channel matrix being low. According to the encountered results, the

multi-user reduced rank channel estimators have the superiority over the

conventional estimators that are currently used in single-cell and multi-cell networks.

1.2.3 High Complexity of Smart Antenna Receiver

The essence of cellular system design is spatial reuse, which allows geographically

separated transmitters to make the use of the same time and frequency resources

[21]. The need to find solutions that would support the growing number of users of

3G wireless systems including TD-SCDMA systems has stimulated many research

groups to explore new techniques to increase the system capacity of the mobile

communication systems.

Adding a new dimension in processing (spatial) will increase the parameters of the

Space-Time (ST) channel matrix and based on two ranking orders (temporal and

spatial) that will be proportional to the complexity of the system and the time

channel estimation.

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1.3 Research Aims and Objectives

This thesis aims to enhance the performances of the joint channel estimators and the

associated multi-user joint detectors in TD-SCDMA systems by proposing a new

technique based on singular value decomposition reduced rank algorithm for

different types of network scenarios ( single and multi-cell networks) and is extended

to smart antenna applications under two global standardizations (3GPP and ITU). As

such, the main objectives of this thesis are:

1. To develop a mathematical model of the TD-SCDMA signal aiming to

increasing TD-SCDMA systems throughout by a new channel estimation

process.

2. To optimise the reduced rank technique for the TD-SCDMA system for

signal cell network deployments.

3. To maximize the system capacity by inserting 16 users in one time slot.

4. To improve the accuracy of the multi-cell joint channel estimation by taking

the signals of users of the neighbouring cells that having a strong interference

into channel estimation matrix.

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5. To introduce an efficient ST joint channel estimation and data detection and

smart antenna system for TD-SCDMA systems.

To meet these aims and objectives, a new technique for joint channel estimation that

is based on SVD reduced rank is proposed in this thesis. In the single-cell TD-

SCDMA cellular communication systems, the proposed schemes outperforms

traditional channel estimation schemes by having 2-4 dB BER gain (depending on

the type of channel and the standardization model) and exploiting rank one or two

estimation only from the whole channel matrix system. For Multi-cell TD-SCDMA

system, the proposed scheme shows significant improvement in terms of user

capacity as compared to the conventional scheme with only 5-9 dB BER gain.

Finally the proposed method for ST TD-SCDMA system can provide remarkable

structure of receiver with low complexity. Rank three based receiver can be adopted

for the Indoor channel of 3GPP recommendations with five rank exploited advantage

under the conventional full rank; while rank four based receiver can be rely it for

vehicular channel.

1.4 Brief Methodology

To achieve the high data rate, user capacity, transmission reliability and bandwidth

efficiency in wireless transmission systems, several schemes are proposed in this

thesis. The methodology of this thesis is proposed for both real-time visual data

transmission and overloaded CDMA systems as illustrated in Figure 1.1.

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Figure 1.1. Brief Methodology.

The proposed techniques are designed and developed using MATLAB 7.9 (R2009b)

and simulated under frequency selective channel and Additive White Gaussian Noise

(AWGN) environments for Indoor and Vehicular user’s movement channels.

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1.5 Thesis Scope

A summary of the scope of this thesis is illustrated in Figure 1.2.

Figure 1.2. Study Module

Wireless Communication

Systems

1G 4G 3G 2G

TD-SCDMA CDMA2000 WCDMA

ST JD

Smart Antenna JCE

RR B. Steiner Post Processing Segmentation

MUJD

MMSE ZF MF Beamforming

LS MVDRD

R

BER MSE CIR Correlation Coeff. SNR SIR Capacity

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The direction of flow of the proposed schemes is indicated by the bold lines, whereas

the dotted lines indicate related research areas which are out of the scope of this

thesis.

1.6 Organization of the Thesis

This thesis addresses the problems and practical issues of joint channel estimation in

TD-SCDMA system with intra and inter-cell interference. Comprehensive study for

single and multi-cell network deployments will introduce and apply the reduced rank

technique for these scenarios and associating the multiuser joint detection systems.

The rest of the thesis is organized as follows.

Chapter One provides an introduction and a brief review on the latest joint channel

estimation in TD-SCDMA. It also includes the objectives of the study, the scope of

the work, and the problem statement.

Chapter Two, the related technical background and literature review are presented in

this chapter. The basic concepts of wireless mobile cellular communication systems

and their generations with short description to the TD-SCDMA air interface part. The

chapter reviews the principles of the important techniques employed in joint channel

estimation algorithms. In comparison to the other issues, practical problems

associated with these algorithms are also briefly discussed. The structure of TD-

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SCDMA receiver with the proposed channel estimation technique is extracted in this

chapter. It also presents the motivation of embedded smart antenna technology

solution in the future of wireless systems.

In chapter Three the underlying idea of the reduced rank approaches for single cell

TD-SCDMA system is introduced. The training and data model of the proposed

single-cell joint channel estimation and multi-user joint detection over Additive

White Gaussian Noise (AWGN) channels are presented. The effective low rank

property of the wireless channel is analyzed. A rank analysis of indoor and outdoor

typical propagation environments shows that single cell channel matrix describing

the channel in fact low rank. The reduced rank channel model is suggested as a

solution to overcome the complexity that resulted from increasing the system

capacity by inserting the maximum number of users in one time slots. To make the

test more comprehensive, we have involved the two standard systems 3GPP and

ITU.

Chapter 4 focuses on the reduced rank estimation which is extended to multi-cell

systems. The proposed method can effectively cope with inter-cell interference (ICI)

from neighboring cells and multiple access interference occurring because the non

orthogonality of training sequence. Furthermore, with respect to the conventional full

rank receiver, it has shown that the lower number of rank order that represents the

extended multi-cell channel matrix results not only in performing well estimation but

also in reduced complexity of the structure of multi-cell based detector.

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Chapter 5 presents a new method to reduce the complexity of the ST TD-SCDMA

receiver. Reduced rank channel modeling, estimation, and proper rank choice are all

detailed. By adopting rank three and rank four, we get simple ST TD-SCDMA

receivers architectures for 3GPP standard where their ST parameters are

simultaneously determined by a joint optimization criterion. In contrast, rank two and

three are optimized for ITU standard recommendations.

Chapter 6 includes conclusions and summarized the thesis, followed by the

discussion of the key contribution of the proposed work. There are several directions

for future research that have also been suggested for further investigation.

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