idma with tree based interleaver_ph.d.thesis

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Performance Evaluation of IDMA

Scheme in Wireless Communication

A Thesis

Submitted in Partial Fulfillment of the Requirements

for the Degree of

Doctor of Philosophy

in

Electronics & Communication Engineering

by

Manoj Kumar Shukla

Department of Electronics & Communication Engineering

Motilal Nehru National Institute of Technology,

Allahabad (India)

November- 2010


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Undertaking

I declare that the work presented in this thesis titled Performance Evaluation of IDMA

Scheme in Wireless Communication, submitted to the Department of Electronics &

Communication Engineering, Motilal Nehru National Institute of Technology, Allahabad, for

award of theDoctor of PhilosophyinElectronics & Communication Engineering, is my original

work. I have not plagiarized or submitted the same work for the award of any other degree. In

case this undertaking is found incorrect, I accept that my degree may be unconditionally

withdrawn.

November, 2010

Allahabad (Manoj Kumar Shukla)


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Certificate

Certified that the work contained in this thesis titled Performance Evaluation of IDMA Scheme in

Wireless Communication submitted by Manoj Kumar Shukla, has been carried out under our

supervision and that this work has not been submitted elsewhere for a degree.

Dr. Sudarshan Tiwari Dr. V.K. Srivastava

Professor and Head Professor

Department of Electronics & Comm. Engg. Department of Electronics & Comm. Engg.

Motilal Nehru National Institute of Technology Motilal Nehru National Institute of Technology

Allahabad, INDIA Allahabad, INDIA


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Acknowledgements

I am highly indebted to my thesis supervisors, Professor Sudarshan Tiwari and Professor V.K.

Srivastava for their kind support and guidance without which this thesis would not been possible.

Their sound knowledge, enthusiasm to research, and guidance was invaluable to me since the day I started

as a research scholar. Their untiring encouragement has always been endless source of motivation for me.

I can never thank them enough. I feel to be lucky to work under their invaluable guidance during the

research work in MNNIT, Allahabad.

I am extremely grateful to Professor Rajiv Tripathi for his valuable encouragement during the entire

research work. He was really helpful especially during the stressed moments during all these years. I have

always found him a true reliever. Thank you sir!

I am also thankful to Professor T.N. Sharma, Professor H.N. Kar, and all the faculty members of the

department for maintaining a congenial research environment. I am also thankful to many colleagues

who have enhanced my understanding of the subject, in particular to Dr. P.C. Upadhyaya, Dr.

V.S. Tripathi and Dr. D.K. Kothari. These colleagues and valued friends, too numerous to be

mentioned, have influenced my views concerning various aspects of wireless communication. I

am also grateful to Rajesh Verma, V.K. Dwivedi, A. Raghuvanshi, Arun Prakash, Malaya Hota,

Prashant Shah, Subodh Waria, and many others with whom I enjoyed an association.

I also acknowledge my valuable associations with the faculty members of Department of

Electronics Engineering, Harcourt Butler Technological Institute, Kanpur, INDIA, in particular

with Prof. G.P. Bagaria, Dr. Rachna Asthana, Mrs. Rajani Bisht, Dr. Krishna Raj, Mr. Ashok

Shankhwar, Mr. Ashutosh Singh, Mr. Ram Chandra Singh Chauhan and many other valued

colleagues. My sincere thanks are also due to administration of Harcourt Butler Technological

Institute, Kanpur, INDIA, for supporting my research.

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I feel particularly indebted to my guides for her skilful assistance in correcting the final

manuscript in MS WORD. Finally, my sincere gratitude is due to the numerousauthors listed in

the Author Index as well as to those whose work was not cited owing to space limitations for

their contributions to the state of the art, without whom this thesiswould not have materialized.

Manoj Kumar Shukla

Department of Electronics & Communication Engineering

Motilal Nehru National Institute of Technology, Allahabad, INDIA

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Synopsis

The development of wireless cellular communication systems has evolved from the first-

generation (1G) of analogue stage to second-generation (2G) and third-generation (3G) of digital

stage. Now, due to market oriented demands, it is has stepped into fourth-generation (4G) of

broadband stage. As per recommendations of International Mobile Telecommunications-2000

(IMT-2000), the future wireless communication is bound to occupy the features including

high-speed data and broadband transmission, high capacity to support a huge number of

simultaneous users, global mobility, high security, and scalable quality of service (QoS) along

with low cost for both operators and subscribers. The above features are imposing technical

challenges on system design and stimulating various research topics on capacity, complexity and

performance. In order to increase the capacity of wireless networks, various multiple access

schemes have been reported in the literature. The credit of most competent multiple access

scheme in 2G systems goes to CDMA scheme which offers an even better bandwidth-efficiency

than TDMA and FDMA schemes, however, its implementation is quite difficult due to

involvement of rather complex technologies including complex power-control, and multiuser

detection techniques etc. The performance of CDMA scheme is mainly limited by multiple

access interference (MAI) and inter-symbol interference (ISI). In conventional CDMA

systems, the spreading sequences were employed for the purpose of user separation, however

due to poor aperiodic correlations amongst spreading codes including Gold, Walsh, Kasami

sequences, the direct-sequence (DS) spreading mechanism demonstrates low spreading

efficiency (SE) in case of high user count.

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The requirement of alternate mechanism for user separation has been solved by Interleave-

Division Multiple-Access (IDMA) scheme, in which, most of above stated problems do not exist

due to application of user-specific interleavers having low cross-correlation amongst them. The

interleaved data resulted from user-specific interleavers, demonstrates better orthogonality

amongst each other in the channel. The condition of orthogonality is maintained for reducing the

risk of collision amongst the interleavers during communication process.

In IDMA scheme, orthogonal interleavers are employed as the only means for user separation

and, hence, are referred as the heart of the scheme. The selection of interleaver along with

optimum design methodology for IDMA system leads to satisfactory spectral efficiency.

During initial run of IDMA scheme, random interleavers (RI) were employed for user

separation. Later, random interleavers were replaced by master random interleavers (MRI) in

order to reduce the memory requirement raised due to storage of random interleavers at

transmitter and receiver ends. Many more interleavers are reported in literature but most of

them are based on methodology of selection of user-specific interleavers amongst available

random interleavers. Still, the problem of computational complexity involved in

interleaving and de-interleaving mechanism is unresolved for user specific interleavers.

These problems in user-specific interleavers have provided the motivation for development of

an optimum interleaving mechanism for IDMA scheme.

In this thesis, an optimum interleaving mechanism has been proposed named as tree based

interleaving (TBI) mechanism, for the solutions related to computational complexity,

bandwidth requirement and optimization of memory size, at transmitter and receiver ends.

The orientation of the work has been maintained towards the analysis and design of

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proposed tree based interleaving (TBI) mechanism for IDMA scheme fulfilling the

requirement of orthogonality and easy implementation.

In the beginning of thesis, the mechanism of interleaving with necessary conditions is

presented. Later, the performance and analysis of proposed TBI mechanism with IDMA scheme

has been presented. Apart from the bit error rate (BER) performance analysis, the

interleavers have also been analyzed on the basis of memory requirement and

computational complexity at transmitter and receiver ends. The performance evaluation of

IDMA scheme with proposed tree based interleaving (TBI) mechanism, in uncoded and coded

environments, has been duly investigated. After investigation, it is noticed that the computational

complexity of tree based interleaver is extremely less in comparison to that for master random

interleaver while it is marginally higher to that occurring in case of random interleaver.

However, the bandwidth and memory requirement of proposed tree based interleaver is found to

be considerably less than that of random interleaver and slightly higher to that of master random

interleaver. It has been observed that BER performance of this interleaver is similar to that of

random interleaver and master random interleaver.

The second goal of the thesis is to evaluate BER performance of IDMA scheme with

maximal ratio combining (MRC) diversity, for proposed TBI mechanism along with RI and

MRI mechanisms with various architectures. After simulations, the BER performance of

proposed TBI mechanism is observed to be very near to that of random interleaver.

Further, the correlation analysis of all the concerned interleavers have been carried out in this

thesis which reveals the behavior of interleavers with increment in user count. It is observed

that the cross-correlation of TBI mechanism is almost similar to that of MRI and RI mechanisms.

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It again confirms that BER performance of TBI mechanism should be similar to that of other

mechanisms. The increment in multiple access interference (MAI) is also observed with

increment in user count for all the interleaving mechanisms.

Finally, the proposed tree based interleaving mechanism has been implemented on field-

programmable gate-array (FPGA) system for observing the performance related to hardware

requirements and timing constraints in comparison to that required with RI and MRI

mechanisms, for IDMA systems. During the implementations, it is observed that the hardware

requirement of tree based interleaving (TBI) mechanism is at the minimum level in comparison

to other considered mechanisms. The timing constraints of TBI mechanism are also found to be

at its minimum level. In addition to it, the tree based interleaving mechanism inherits comparably

lesser hardware complexity to that required for master random interleaving mechanism due to

requirement of lesser looping operations. After the analysis, it has been observed that proposed

tree based interleaver requires least hardware along with least timing constraints for its operation.

The proposed tree based interleaving (TBI) mechanism has demonstrated optimum overall BER

and other performances in comparison to RI, and MRI mechanisms. Thus, the proposed

interleaving mechanism along with IDMA scheme provides an alternative to conventional

CDMA scheme for future wireless communication systems.

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Table of Contents

Acknowledgements iSynopsis iii

Table of Contents vii

List of Figures x

List of Table xiii

Glossary xv

1.

Introduction 1

1.1.Development of Wireless Communication Systems 11.2.Multiple Access Schemes 5

1.2.1. FDMA Scheme 51.2.2. TDMA Scheme 61.2.3. CDMA Scheme 7

1.3.Motivation 81.4.Problem Statement 101.5.Research Contributions 121.6.Thesis Organization 13

2. Overview of Interleave-Division Multiple-Access (IDMA) Scheme 152.1.Introduction 152.2.Interleavers in Digital Communication 152.3.Interleavers in IDMA Scheme 162.4.Mechanism of Interleaving Process 172.5.Interleave-Division Multiple-Access (IDMA) Scheme 19

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2.5.1. Comparison of CDMA and IDMA Schemes 202.5.2. IDMA Transmitter and Receiver 21

2.5.2.1. Basic Primary Signal Estimator (PSE) Function 232.5.2.2. Algorithm for Chip-By-Chip Detection 242.5.2.3. Decoder (DEC) Function 25

2.5.3. IDMA over Multipath Channels 262.6.Literature Review 312.7.Simulation of IDMA Scheme 392.8.Conclusions 41

3. Performance Evaluation of Tree Based Interleaver (TBI) in IDMA Scheme 423.1.Introduction 423.2.Motivation 433.3.Mechanism of Tree Based Interleaver (TBI) 443.4.Performance Evaluation of Tree Based Interleaver 473.5.TBI with Unequal Power Allocation Algorithm 61

3.5.1. Unequal Power Allocation Mechanism 613.5.2. Numerical Results 63

3.6.Conclusions 664. Performance Evaluation of Tree Based Interleaver in IDMA Scheme with

Maximal Ratio Combining (MRC) Diversity 68

4.1.Introduction 684.2.Diversity Mechanisms 68

4.2.1. Frequency Diversity 694.2.2. Time Diversity 70

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4.2.3. Space Diversity 714.2.3.1. Transmit Diversity 724.2.3.2. Receive Diversity 73

4.3.Combining Mechanisms 744.3.1. Selection Combining 744.3.2. Maximal Ratio Combining (MRC) 764.3.3. Equal Gain Combining (EGC) 78

4.4.Performance Evaluation of IDMA Scheme with MRC Diversity 784.4.1. IDMA Scheme with Maximal Ratio Receiver Combining (MRRC)

Diversity 78

4.4.2. IDMA Scheme with Maximal Ratio Transmitter Combining (MRTC)Diversity 80

4.5.Simulation Results 824.5.1. Simulation Results of IDMA Scheme using MRRC Diversity 824.5.2. Simulation Results of IDMA Scheme using MRTC Diversity 90

4.6.Conclusions 945. Correlation Analysis and FPGA Implementation of Interleavers 96

5.1.Introduction 965.2.Motivation 965.3.Design Criteria for Interleavers in IDMA Scheme 985.4.Correlation in Interleavers 985.5.Correlation Analysis of Interleavers 995.6.Interleaving Mechanism in IDMA Scheme 105

5.6.1. Random Interleaving (RI) Mechanism 1075.6.2. Master Random Interleaving (MRI) Mechanism 109

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5.6.3. Tree Based Interleaving (TBI) Mechanism 1105.7.Performance Comparison of Interleavers on FPGA Implementation 112

5.7.1. Summary of Hardware 1125.7.2. Final Register Report 1135.7.3. Device Utilization Report 1135.7.4. Timing Summary Report 114

5.8.Conclusions 1156. Conclusions 118

6.1.Suggestions for Further Investigations 121

References 123

Appendix 142

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List of Figures

1.1 Progress in wireless communication from 1G to 4G 3

1.2 Frequency Division Multiple Access (FDMA) 5

1.3 Time Division Multiple Access (TDMA) 6

2.1 Mechanism of data interleaving 18

2.2 CDMA scheme vs. IDMA scheme 20

2.3 IDMA transmitter and receiver structure 22

2.4 IDMA transmission in single path 23

2.5 Flowchart of decoding mechanism in the receiver of IDMA scheme 26

2.6 IDMA in multipath transmission 27

2.7 Simulation of IDMA and CDMA schemes 40

2.8 Simulation of IDMA scheme with Random Interleaver 40

3.1 Interleaving strategy for Tree Based Interleaving scheme 45

3.2 Performance of Tree based Interleaver with Random Interleaver 50

3.3 Comparison of RI, MRI, and TBI for memory requirement 52

3.4 Comparison of RI, MRI, and TBI for computational complexity at

transmitter end 54

3.5 Comparison of RI, MRI, and TBI for computational complexity at

receiver end 55

3.6 Data formats of RI, MRI, and TBI mechanisms in IDMA scheme 56

3.7 Simulation of TBI in multi-user environment 57

3.8 Uncoded IDMA scheme in AWGN and Flat Rayleigh fading environment

57

3.9 Simulation of RI in coded and uncoded IDMA scheme 58

3.10 IDMA scheme in uncoded environment for variation in user count 59

3.11 Simulation of RI in coded and uncoded IDMA scheme 59

3.12 IDMA scheme in coded environment for variation in user count 60

3.13 Simulation results for 32 users without coding with RI with various data

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lengths 64

3.14 Simulation result for 32 users without coding with TBI with various

data lengths 65

3.15 IDMA scheme in uncoded environment for variation in user count

with RI and TBI with unequal power allocation algorithm 65

3.16 IDMA scheme in rate convolutionally coded environment for variation

in user count with RI and TBI with unequal power allocation algorithm 66

4.1 Frequency diversity Mechanism 70

4.2 Time Diversity Mechanism 70

4.3 Transmit diversity with multiple antennas at transmitter side 72

4.4 Receive Diversity having multiple antennas at receiver side 73

4.5 Mechanism of Selection combining 75

4.6 Maximal Ratio Combining (MRC) 76

4.7 IDMA with MRRC Receiver diversity 79

4.8 Transmit diversity having two transmitter and one receiver antenna 81

4.9 Performance of IDMA system with and without MRRC diversity 83

4.10 Performance of IDMA having Random Interlever with MRRC diversity

technque at various iterations count with datalength=1024,

spreadlength=16 844.11 Performance comparison at different data length with Random Interleaver

with MRRC Diversity 85

4.12 Performance of IDMA using tree based interleaver with MRRC Diversity 86

4.13 Simulation of Uncoded IDMA with variation in interleaver 86

4.14 Performance of Random Interlever with 1Transmitter and 2 Receive

Antenna, MRRC diversity Technique 87

4.15 Performane of master random interleaver with 1Transmitter and

2 Receive Antenna, MRRC diversity Technique 88

4.16 Performance of Tree based Interleaver With 1Transmitter and 2 Receive

Antenna, MRRC diversity Technique 88

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4.17 Perfromance of IDMA scheme with FEC coding with tree based

interleaver and datalength=1024 bits 89

4.18 IDMA scheme with variation in receiver count using MRRC diversity 89

4.19 Performance of IDMA system using MRTC diversity with random

interleaver 91

4.20 Performance of IDMA at different data lengths using random interleaver

with MRTC diversity Scheme 92

4.21 Uncoded IDMA scheme with variation in datalength for RI & TBI 93

4.22 Rate Conlutionaly coded IDMA scheme with variation in datalength

for RI & TBI 93

4.23 Rate Conlutionaly coded IDMA scheme with uncoded IDMA scheme 94

5.1 Mechanism for calculation of resultant user-specific cross-correlation

amongst users 101

5.2 Resultant user-specific cross-correlation for 25 users with RI, MRI,

and TBI 102

5.3 Resultant user-specific cross-correlation for 100 users with RI, MRI,

and TBI 103

5.4 Graphical view of resultant user-specific cross-correlation with RI, MRI,

and TBI 105

5.5 Block Diagram of Random Interleaving Mechanism 108

5.6 Block Diagram of Master Random Interleaver (MRI) 110

5.7 Block Diagram of Tree based Interleaving mechanism 111

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List of Tables

3.1 Comparison of Memory requirement of user-specific interleavers in

IDMA scheme 51

3.2 Comparison of Computational complexity of user-specific interleavers/

deinterleavers at transmitter end 52

3.3 Comparison of Computational complexity of user-specific interleavers/

deinterleavers at receiver end 54

5.1 Peak Resultant User-Specific Cross-Correlation of RI, MRI, and TBI 104

5.2 Summary of hardware 112

5.3 Final Register report 113

5.4 Device utilization report 114

5.5 Timing summary of interleavers 115

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Glossary

3GPP Third Generation Partnership Project

AMPS Advanced Mobile Phone Service

APP A Posteriori Probability

AWGN Additive White Gaussian Noise

BER Bit Error Rate

BPSK Binary Phase Shift Keying

BS Base Station

CBC Chip by Chip

CDMA Code Division Multiple Access

DEC Decoder

DL Downlink

DS Direct Sequence

EDGE Enhanced Data Rate for Global Evolution

ENC Encoder

ETACS Extended Total Access Communication System

EV-DO Evolution-Data Optimized or Evolution-Data only

FDD Frequency-Division Duplex

FDMA Frequency Division Multiple Access

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FEC Forward Error Correction

FPGA Field-Programmable Gate-Array

GPRS General Packet Radio Service

GSM Global System for Mobile Communications

HSDPA High-Speed Downlink Packet Access

HSPA High Speed Packet Access

IDMA Interleave Division Multiple Access

IS-136 Interim Standard-136

IS-95 Interim Standard-95

ISI Inter Symbol Interference

ITU International Telecommunication Union

LAN Local Area Network

LDPC Low Density Parity Check

LLR Log Likelihood Ratio

LTE Long Term Evolution

MAC Multiple Access Channel

MAI Multiple Access Interference

MC Multi Carrier

MC-CDMA Multi-Carrier CDMA

MIMO Multiple Input Multiple Output

MRC Maximal Ratio Combining

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MRI Master Random Interleaver

MRRC Maximal Ratio Receiver Combining

MRTC Maximal Ratio Transmitter Combining

MS Mobile Station

MUD Multi User Detection

NMT Nordic Mobile Telephony

OFDM Orthogonal Frequency Division Multiplexing

PDC Personal Digital Cellular

PEG Progressive Edge Growth

PI Power Interleaver

PN Sequences Pseudo Noise Sequences

PSE Primary Signal Estimator

QoS Quality of Service

QPSK Quadrature Phase Shift Keying

RI Random Interleaver

RTT Radio Transmission Technology

SAS Singe Antenna System

SE Spreading Efficiency

SNR Signal to Noise Ratio

TACS Total Access Communication System

TBI Tree Based Interleaver

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xviii

TDD Time Division Duplex

TDMA Time Division Multiple Access

TD-SCDMA Time-Division synchronous CDMA

UL Uplink

UMTS Universal Mobile Telecommunications System

UWB Ultra Wide Band

VHDL Very High Speed IC Hardware Description Language

WCDMA Wideband Code Division Multiple Access


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CHAPTER 1

Introduction

Since the beginning of the 20thcentury, technologies have placed its marks with stone

line for providing new techniques and products for wireless communication.

Especially in the past three decades, wireless communication services have penetrated

into our society with an explosive growth rate.

Cellular radio was originally developed for offering phone services to mobile

subscribers. Now-a-days, it is engaged in even providing a variety of services,

including video conferencing, music or movie appreciation, games, internet access.

The demands and applications from subscribers stimulate the market and drive the

technology for further growth. On the other hand, research and development of

communication engineering are undergoing a revolution due to rapid advances in

technology.

1.1. Development of Wireless Communication Systems

Wireless cellular communication systems have evolved with the first-generation

(1G) of analogue stage using frequency division multiple access (FDMA) scheme.

Later, due to rapid advances in technologies based on market demand, it has led to

the second-generation (2G) of digital stage with time division multiple access

(TDMA) and code division multiple access (CDMA) schemes, and now it has stepped

into the third-generation (3G) with eye on fourth-generation (4G) of broadband

stage [8, 9, 12].

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The most popular technology related to 1G is the Advanced Mobile Phone

Service (AMPS) developed in the United States (U.S.) by AT&T in the late 1970s,

and later, it was implemented by Ameritech at the end of 1983. The further

developed version of AMPS was known as Extended Total Access Communication

System (ETACS) developed in Europe in 1985. The both of these systems were

employing frequency-division duplex (FDD) and frequency-division multiple-access

(FDMA) scheme. Due to problem of slower data rate and lower user base, these

analogue systems, soon, were replaced by 2G digital systems based on time-division

multiple-access (TDMA) scheme. The representatives of 2G systems i.e. Interim

Standard-95 (IS-95) system and the Global System for Mobile Communication

(GSM), have been widely deployed throughout the world. The IS-95 system,

developed in United States of America, is mainly based on code-division multiple-

access (CDMA) scheme while GSM system, developed in Europe, is mainly based

on time-division multiple-access (TDMA) scheme.

Due to lots of technological changes and market oriented demands, mobile

communication technology has entered in 3G stage. The distinctive features of 3G

systems in comparison to 2G systems are inherited with technology of packet-

switched high-rate data transmission along with voice services. Specifically,

CDMA2000, a representative of 3G systems, builds on the packet-switched

technology along with increased data transmission rate, and backward compatibility

with original CDMA standards. It is employed primarily in North America and some

parts of Asia. Another qualified 3G candidate, wideband CDMA (WCDMA) is

referred as an evolution of the GSM technology, including aspects of TDMA and

CDMA2000 for global accessibility. The time-division synchronous CDMA (TD-

SCDMA) is mainly developed by the Datang Group, China, building on the original

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CDMA standard to deliver multimedia data, considering its largest user base in its

own country. Figure 1.1 demonstrates the development of progress of wireless

communication from 1G to 4G, in terms of data rates, with all the technological

development observed in meantime. The CDMA and its other extended versions

such as IDMA, lie between technological developments from 2G to 3G during the

span from 1993 to 2007.

Figure 1.1: Progress in wireless communication from 1G to 4G [148]

Although the standards for further generation systems are still in formative

stages, leading companies in the industry have started some groundwork with their

researchers. Now-a-days, the techniques related to future wireless communication

have become hot topics for research all over the world.

The 3G and beyond systems have been developed to serve people's daily work

and life, and to satisfy their demands. The ultimate user needs reliable, cheaper,

secure, and low-delay voice & data services anytime and anywhere. The additional

features of the future wireless communications include high-speed data and

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broadband transmission for huge user base, along with global mobility, & scalable

quality of service (QoS) for both operators and subscribers.

The above features are imposing technical challenges on system design and

stimulate various researches to work on topics related to capacity, complexity and

performance of the communication systems [23, 56, 20]. There are also other research

topics highly related to the physical layer in wireless systems including optimum

channel coding, detection, and diversity mechanisms. For immediate solutions of

above problems, near-capacity-achieving forward error correction (FEC) codes are

developed to enhance power efficiency while improved detection algorithms are

designed to enhance the reliability or bit-error rate (BER) performance. Diversity

techniques have been proposed to increase spectral efficiency and diversity for

accommodating more users and mitigating fading [20]. The new horizons on above

discussed topics have emerged as hot cake for researchers all over the world.

In India, cellular industry came into existence nearly in mid 1990s and since

then the average growth rate per annum has been about 85 percent [1]. By the end of

2002, the total number of cellular subscribers, in India, had increased to about 10

million subscribers. In addition to it, telecom customers have also been doubled

during last two years from 300 million to 600 million. According to Reuters India

[3], total mobile users in India, now, stand at 584.32 million, data from the sector

regulator showed, behind only China that had 777 million at the end of March 2010.

There is tremendous scope for researches in the area of wireless

communication for improving the back-bone of communication systems as per the

recommendations of International Telecommunication Union (ITU) [5]. One of the

hot-cake areas for research is improvement in technology related to multiple access

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techniques with communication channels. In the next, section, various multiple access

techniques including recently evolved IDMA scheme will be discussed, in brief.

1.2. Multiple Access Schemes

Generally, in wireless communication, large numbers of users are involved in the

conversation at a time with each other leading to share the same wireless channel.

For sharing of wireless channel, there exist three widely deployed multiple access

schemes [8] popularly known as, frequency-division multiple-access (FDMA), time-

division multiple-access (TDMA), and code-division multiple-access (CDMA). It

will also be worth mentioning that recently, a new variant of CDMA scheme i.e.

interleave-division multiple-access (IDMA) scheme has been proposed [76].

In the next subsection, the prime multiple access schemes are being

presented in brief so as highlight their merits and demerits.

1.2.1. FDMA Scheme:

Frequency Division Multiple Access (FDMA) scheme is reffered as the most common

technique employed in analog communication systems utilizing division of entire

frequency spectrum into multiple frequencies slots to be assigned to indivdual users,

as shown in figure 1.2. With FDMA scheme, each subscriber at any given time is

assigned with particular frequency channels for transmission and reception

independently. The channel, therefore, is closed to other conversations until the

initial call is completed, or handed-off to a different channel. FDMA scheme has

been used for first generation analog communication systems.

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Figure 1.2: Frequency Division Multiple Access (FDMA)

The scheme is referred to be inefficient due to underutilization of bandwidth.

In addition to it, FDMA systems are bound to employ a guard-band between adjacent

channels, for avoiding random Doppler shift, occurring due to the user's random

mobility. The guard-bands also reduce the probability of adjacent channels

interference, while decrease the spectral efficiency [9].

1.2.2. TDMA Scheme:

Time Division Multiple Access (TDMA) scheme improves spectrum capacity by

splitting each time period into multiple time slots. It allows each user to access the

entire radio frequency channel for the allotted time slot of during a call as presented in

figure 1.3. Other users are also allowed to share the same frequency channel at

different time slots. TDMA scheme is the dominant technology for the second

generation (2G) mobile cellular networks.

Figure 1.3: Time Division Multiple Access (TDMA)

However, the TDMA systems have to be carefully synchronized during

communication for all the users to ensure that they are received in the correct time-

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slots and do not cause the interference to other users [7]. Since it cannot be perfectly

controlled in a mobile environment, a guard-time is inserted between each time-slot,

which reduces the probability that users will interfere, but decreases the spectral

efficiency. Also in case of bursty traffic, user has to wait for his next allotted time-

slot which ultimately slows down the data rate during communication [9].

1.2.3. CDMA Scheme:

Code Division Multiple Access (CDMA) scheme is, basically, based on spread

spectrum technology. It increases spectrum capacity by allowing all users to occupy

all channels at the same time [10]. The data streames related to indivual users are

spreaded over the whole radio band, and each voice or data call is assigned a unique

code to differentiate from the other calls carried over the same spectrum [14]. The

asynchronous CDMA system offers a key advantage in the flexible allocation of

communication resources. It is ideally suited to a mobile network where large

numbers of transmitters generating a relatively small amount of traffic at irregular

intervals individually.

The performance of CDMA scheme is mainly limited by multiple access

interference (MAI) and intersymbol interference (ISI). Its processing gain is

reduced considerably with increment in users per sector. The processing gain is

referred as a figure of merit in spread spectrum communication. Also, in CDMA

scheme, the complexity of decoder increases with increment in user count [6].

From the viewpoint of sharing communication resources, TDMA scheme is

termed to be more efficient to FDMA scheme due to better spectral effinciency

while considering the matter of message delay, FDMA scheme outperforms the

TDMA scheme. In addition to it, as quoted in [5] regarding future requirements in

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wireless communication, it is recommended that a communication system must

possess the essential parameters for consumers including low receiver cost, de-

centralized control, diversity against fading, power efficiency, multi-media

services, high user number, and high throughput along with high spectral efficiency

[6].

For further way of efficient communication, employing spread spectrum

technology, the question regarding alternate way for user separation arises. Recently, a

new variant of CDMA scheme known as interleave-division multiple-access (IDMA)

scheme has evolved on the horizon of wireless communication [76, 77]. The IDMA

scheme employs the interleavers as the only means of user separation in order to

ensure privacy related to data of users.

1.3. Motivation

The most commonly employed multiple scheme in the world, i.e. CDMA scheme

offers an even better bandwidth-efficiency than TDMA and FDMA schemes, and has

been widely adopted in the 3G mobile cellular systems, including CDMA2000,

WCDMA, TD-SCDMA systems. It offers robust performance due to its unique

feature of processing gain. However, its successful operation is based on rather

complex technologies including complex power-control, and multiuser detection

techniques, and thus it is comparatively difficult to get implemented, when compared

with FDMA and TDMA schemes.

The CDMA mechanism is reported to be unsuitable to support QoS sensitive

multimedia traffic. It is extremely difficult to adjust data rate on-a-fly and even the

small change in data rate may result with change in processing gain [7], which further

compels to adjust transmitter power. Hence, ultimately rate change for ONE user

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affects whole cell-wise code-assignment plan [10]. Looking into implementation

complexity of CDMA systems, the requirement of very precise power control,

powerful multi-user detection, requirement of RAKE receiver, and costly sectorized

antennas, becomes highly desirable.

In addition to it, CDMA system needs long frames for signal detection.

Therefore, it is well suited for slow-speed continuous-time transmission specially.

Apart from it, it inherits poor orthogonality of user-specific spreading codes and

merely periodic correlation functions are considered in code design process resulting

in poor aperiodic correlations amongst spreading codes for higher user count.

Therefore, a big room is left for the researchers, leading to improvement in spreading

efficiency of CDMA systems. Apart from it, only unitary codes, i.e., Gold, Walsh,

Kasami, etc. have been used in CDMA scheme.

All of the above stated problems come from the same root i.e. inefficient

Unitary codes i.e. one-code-per-user basis, used for user separation in CDMA

systems. Though, the spreading PN-sequences used for user separation in CDMA

systems, are orthogonal to each other, but the spreaded data related to all the users

may loose its orthogonality, in the channel, in case of high user count. Therefore, the

requirement for alternate mechanism for user separation is needed urgently.

In interleaver-division multiple-access (IDMA) scheme, most of above stated

problems do not exist due to application of user-specific interleavers as alternate way

of user separation in place of unitary spreading PN-sequences used in CDMA scheme.

With IDMA scheme, user separation is achieved with the help of user-specific

interleavers, having low cross-correlation amongst them [76]. As the spreaded user

data is fed to the user-specific interleavers, it results in better orthogonality between

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resultant interleaved data in the channel. The condition of orthogonality is maintained

for removing the risk of collision between the interleavers [91] in the channel.

In IDMA scheme, orthogonal interleavers are referred as the heart of the

systems. If random interleavers are employed as the means of user separation

[76] in IDMA systems, it results in heavy memory requirement for storing the

user-specific interleavers at transmitter and receiver ends. In [104], power

interleavers were introduced which solves the problem of memory requirement

but increases computational complexity during estimation and turbo processing

[51, 62] of interleavers and deinterleavers, at the receiver end. This interleaver is

named as master random interleaver (MRI). Many more interleavers are reported

in literature but most of them are based on methodology of selection of user-

specific interleavers amongst available random interleavers. Still, the problem of

computational complexity is unresolved for the interleaving and de-interleaving

mechanism in IDMA scheme.

In this thesis, an optimum interleaver is proposed for not only solution of

the problem related to computational complexity and bandwidth requirement but

also for optimization for memory requirement at transmitter and receiver ends.

1.4. Problem Statement

Keeping in mind the problems related to implementation of random and master

random interleavers, it becomes mandatory to look for alternate interleaving

mechanism for the solution of the stated problems. In present work, an attempt has

been made to study various aspects of optimum interleaving mechanism for

interleave-division multiple-access scheme, a potential candidate for next-generation

wireless communication. The analysis has been carried out in terms of BER

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performance, memory requirement, bandwidth requirement, and computational

complexity along with hardware requirement needed for its field-programmable gate-

array (FPGA) implementation. Specifically, the problem undertaken in this thesis can

be stated as follows:

(i) To suggest a user-specific interleaver generation mechanism for IDMA

scheme and to evaluate its performance using analytical modeling and

simulation.

(ii) To examine the performance of the proposed interleaving scheme

under various conditions including its performance comparison with

other interleaving schemes for various parameters.

(iii) To evaluate the performance of IDMA scheme with proposed

interleaving scheme employing maximal ratio combining (MRC)

diversity technique. Also to compare its performance to that of other

interleaving schemes under similar conditions.

(iv) To investigate into the correlation analysis of proposed and other

interleaving schemes to justify the increment in multiple access

interference (MAI) with relative increment in user count.

(v) To study the performance analysis of proposed interleaving scheme

with its implementation on field-programmable gate-array (FPGA)

system for observing the comparative hardware requirements and

timing constraints with that of random and master random interleaving

schemes.

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1.5. Research Contributions

In this thesis, the emphasis has been given on analysis and design of optimum

interleaver for IDMA scheme which may fulfill all the requirement of

orthogonality as well must be easy to implement.

(a)The mechanism of interleaving with necessary conditions is presented.

Later, block diagram of IDMA scheme is explained including

transmitter and receiver section.

(b)Further, a tree based interleaver (TBI) mechanism [147], for generation of

user-specific interleavers is proposed for interleave-division multiple-

access (IDMA) scheme.The BER performance comparison of the TBI

with random interleaver (RI) and master random interleaver (MRI)

also known as power interleaver [104] is also presented. Apart from the

performance analysis, all the interleavers have also been analyzed

based on memory requirement and computational complexity. Later,

performance evaluation of IDMA scheme with TBI in uncoded and rate

convolutionally coded environment, is presented.

(c)The performance of IDMA is also demonstrated with maximal ratio

combining (MRC) diversity along with random and master random

interleavers with single transmitter two receiver and other

architectures.

(d)The impact of increment in data length on correlation of user-specific

interleavers has also been investigated. It has been revealed that with

increment in user count, the cross-correlation between user-specific

interleavers goes for hike.

(e)Finally, the FPGA implementation of all the interleavers is

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demonstrated for observing the timing constraints and hardware

requirement. From the analysis, it becomes apparent that tree based

interleaver is an optimum interleaver.

1.6. Thesis Organization

The remaining chapters of the thesis are organized as detailed ahead. Chapter 2

provides preliminaries on interleavers their mechanism and characteristics along with

conditions for orthogonality. In addition to it, the mechanism of interleave-division

multiple-access (IDMA) scheme is also explained for single path and multipath

environments along with literature review.

In chapter 3, proposed user-specific interleaver generation mechanism named

as Tree Based Interleaver (TBI) is presented for IDMA systems [147]. This

interleaver generation mechanism, optimally, removes the problems of extra

bandwidth consumption, excessive memory requirement, and high computational

complexity inherited with other interleaver generation mechanisms. In this chapter,

the performance comparison of IDMA scheme is presented with random interleavers

and master random interleavers in terms of BER performance, memory requirement,

and computational complexity. Also, the performance of IDMA scheme with unequal

power allocation algorithm has been demonstrated along with all the above stated

interleavers.

The chapter 4 demonstrates the analysis of IDMA scheme with maximal ratio

combining (MRC) diversity at transmitter and receiver end along with various

transmitter-receivers architectures. During the performance analysis of MRC diversity

technique, the enhancement in the BER performance of IDMA scheme has been

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observed and the performance of IDMA systems with tree based interleaver is found

to be similar to that with random interleavers.

In chapter 5, the correlation analysis of all the three interleavers i.e. random

interleaver, master random interleaver, and proposed tree based interleaver has been

performed to analyze the decrement in BER performance with increment in user

count. Further, all the interleavers have been duly implemented on field

programmable gate array (FPGA) for studying their hardware and timing

requirements.

In chapter 6, the conclusion the thesis is presented along with the possible

directions for further research related to interleavers in IDMA systems.

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CHAPTER 2

Overview of Interleave-Division Multiple Access

Scheme

2.1. Introduction

Historically, interleaving was employed in ordering block storage on disk-based

storage devices including floppy diskand the hard disksystems. The primary purpose

of interleaving was to adjust the timing differences between the adjacent bits during

transfer of data between computer and storage media. Interleaving was very common

prior to the 1990s, but, later, faded due to availability of high speed processors. Now-

a-days, all the modern disk storage systems are not at all being interleaved.

In communication systems, interleaving is referred to be technique commonly

used to overcome correlated channel noise such as burst error or fading [8, 9, 15]. In

interleaving mechanism, the input data rearranges itself such that consecutive data bits

are split among different blocks and is swapped in a known pattern amongst them. At

the receiver end, the interleaved data is arranged back into the original sequence with

the help of de-interleaver. As a result of interleaving, correlated noise introduced in

the transmission channel appears to be statistically independent at the receiver and

thus allows better error correction.

2.2. Interleavers in Digital Communication

Interleaving has been frequently used in digital communication and storage systems to

improve the performance of forward error correcting codes. Many communication

channelswhich are not memoryless in nature, errors typically occur in bursts rather

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than independently. If the number of errors within a code word exceeds the error-

correcting code's capability, it fails to recover the original code word. Interleaving

ameliorates this problem by shuffling source symbols across several code words,

thereby creating a more uniform distributionof errors.

Typically, in the analysis of modern iterated codes, including turbo and low-

density parity-check (LDPC) codes, independent distribution of errors is assumed

[140]. Systems using LDPC codes therefore typically employ additional interleaving

across the symbols within a code word.For turbo codes, an interleaver is an integral

component of the architecture, and its proper design is crucial for its good BER

performance. However, application of interleaving increases latencyaccordingly. This

happens due to requirement of entire interleaved block at the receiver side to recover

the critical data. In multi-carrier communication systems, additional interleaving

across carriers may be employed to mitigate the effects of prohibitive noise on a

single or few specific carriers.

In next section, the mechanism of interleaving process will be duly studied

along with condition of orthogonality.

2.3. Interleavers in IDMA Scheme

The user-specific interleavers play vital role in the efficiency of IDMA system. It not

only provides decorrelation between adjacent bit sequences as provided in the case of

orthodox turbo coding and decoding, but also facilitates a means for decorrelating

various users [91]. The correlation between interleavers should measure how strongly

signals from other users affect the decoding process of a specific user [102]. The

better the interleaver decorrelation, the lesser the iterations, required for detection in

multiuser detection (MUD) mechanism [105]. The decorrelation among the user-

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specific interleavers provides a mean to reduce the multiple access interference (MAI)

from other users thus helping in the convergence of detection process.

A set of interleavers is considered to be practical if it is easy to generate, and

no two interleavers in the set collide. The transmitter and receiver need not store or

communicate many bits in order to agree upon an interleaving sequence. It may be

demonstrated that a properly defined correlation between interleavers can be used to

formulate a collision criterion, where zero cross-correlation (i.e., orthogonality)

implies no collision [91].

In case of IDMA systems, the transmitter is required to transmit the interleaver

matrix consisting of interleaving pattern along with spreaded data related to users, to

the receiver. So, greater the size of the interleaver, the more bandwidth and resources

are consumed during transmission. Also, it is worth to be mentioned that greater the

size of interleaver, more the orthogonality is achieved amongst interleaver [104].

For better understanding of interleaving mechanism, in the next section, interleaving

process will be discussed.

2.4. Mechanism of Interleaving Process

The interleaver is termed as a mechanism which rearranges the ordering of a data

sequence by means of a deterministic bijective mapping. Let0 1 1

[ , ,...... ]N

C c c c be a

sequence of length N [109]. An interleaver maps C onto a

sequence such that X is a permutation of the elements of C.

Considering C and X as a pair of N-dimensional vectors, there is one-to-one

correspondence between each element of C and each element of X, as shown

in Figure 2.1.

0 1 1[ , ,...... ]

NX x x x

i jc x

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0 1 2c c c 3c 4c 5 6c c

0x 1x 2x 3x 4x 5

x6

x

Figure 2.1:Mechanism of Data Interleaving

An interleaver can then be defined by the one-to-one index mapping function.

( ) : [A A j i], where A={0,1N-1} for ,i j A, .(2.3.1)

The term i' and j are indices of an element of the original sequence c and the

interleaved sequence x, respectively. The mapping function can be expressed as an

ordered set called interleaving vector :

[ [0], [1],...., [ 1]].N

k

. (2.3.2)

The element of the permuted sequence X isthk

[ ]kX C ..... (2.3.3)

The inverse interleaver, i.e. the deinterleaver, restores the permuted sequence

to its original order. Throughout the thesis, the terms and 1 are used to

denote the interleaving and deinterleaving vectors, respectively. With the proper

deinterleaver, the permuted elements can be shifted back to their original positions:

1 1[ [ ]] [ [ ]]k k k

n

..(2.3.4)

Replacing k by in (2.3.3), then from (2.3.4),1[ ]n

1 1[ ] [ [ ]] .n nX C

C . (2.3.5)

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Since the separation of users is achieved by user-specific interleavers, an

obvious interleaver design criterion is that every two interleavers related to specific

users out of a set of interleavers collide up to minimum extent. With increment in

cross-correlation amongst the interleavers, number of collisions also increases,

resulting in increment in bit error rate (BER) of the system.

The property of minimum collision amongst user-specific interleavers depends

on property of orthogonality. It is referred as an important factor in generating the

interleavers. If the orthogonality is not maintained amongst the user-specific

interleavers, the correlation between the users increases proportionally, with

increment in user count resulting in lower BER performance. Therefore, interleavers

generated according to the orthogonality criteria having minimum number of

collisions are accepted as part of IDMA systems.

Two interleaversi and j (where i j ) are said to be orthogonal, if for

any two words, a and b, the correlation C is such that [91],(.)

( , , , ) ( ( )). ( ( )) 0i j i j

C a b f a f b .(2.3.6)

Above condition is for the orthogonality check of the user-specific interleavers.

2.5. Interleave Division Multiple Access (IDMA) Scheme

In [76], the interleaver based multiple-access scheme has been studied for high

spectral efficiency, improved performance and low receiver complexity. This scheme

relies on interleaving as the only means to distinguish the signals from different users

and hence it has been called interleave-division multiple-access (IDMA). As reported

in [76, 77], IDMA systems inherits many advantages from CDMA systems, in

particular diversity against fading and mitigation of the worst-case other cell user

interference problem. Furthermore, it allows a very simple chip by chip iterative

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multiuser detection (MUD) strategy. The normalized MUD cost (per user) is

independent of the number of users [76].

2.5.1. Comparison of CDMA & IDMA Schemes

Comparing CDMA and IDMA mechanisms [129, 67, 68], it is observed that IDMA

scheme may be considered as a special case of Code-Division Multiple Access

(CDMA) scheme. The differences and commonalities of conventional CDMA with

channel coding (top part) and IDMA (bottom part) is presented in figure 2.2.

Figure 2.2: CDMA scheme vs. IDMA scheme

Visualizing the apparent difference between CDMA and IDMA schemes, it is

observed that ordering of interleaving and spreading is reversed in IDMA scheme. In

conventional CDMA scheme, the spreader is user specific, whereas in IDMA scheme,

the interleaver is user-specific. In addition to it, in IDMA scheme, forward error

correction (FEC) and spreading is combined in a single encoder (ENC), which is same

or different for all users [76]. As a consequence, very low rate encoding is used for

forward error correction coding. The spreader has no fundamental relevance any more

in IDMA systems. The spreading of data may be used to simplify the overall encoder

[71]. The interleaver is interpreted as a keyword and only authorized receivers are

FEC

FEC Spreader

m

mSpreader mx

mx

CDMA Scheme

Data Input

IDMA Scheme

Data Input

ENCODER AND SPREADER SECTION

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able to decode the message [76]. However in [78], scheme exploiting the advantages

of CDMA and IDMA schemes has also been proposed. It is suggested in the approach

that for lower count of users, CDMA may be used while for higher user count, IDMA

scheme may be utilized.

In the next section, the block diagram of IDMA communication system

incorporating transmitter and receiver section is explained.

2.5.2. IDMA Transmitter & Receiver

The upper part of Figure 2.3 demonstrates the transmitter structure of the IDMA

scheme under consideration with K simultaneous users. The input data sequence

of user-k is encoded based on a low-rate code C, generating a coded sequence,

kd

(1), (2),....... ( )........ ( )T

k k k k k C c c c j c J (2.4.1)

where J is the frame length.

The elements in are referred to as coded bits. Then is permutated by an

interleaver

kc

kc

k , hence, producing (1), (2),....... ( ) ( )

T

k k k k k X x x x x J

k

........j . Following

the CDMA convention, the element in x will be denoted as chips. Users are solely

distinguished by their interleavers, hence the name interleave division multiple access

(IDMA) scheme [71].

The key principle of IDMA is that the interleavers k , opted for user

separation, should be orthogonal for all the users. It is assumed that the interleavers

are generated independently and randomly. The randomly generated interleavers

disperse the coded sequences so that the adjacent chips are approximately

uncorrelated, facilitating the simple chip-by-chip detection scheme as discussed

below.

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Figure 2.3: IDMA Transmitter and Receiver Structure

Adopting an iterative sub-optimal receiver structure, as demonstrated in figure

2.3, consisting of the primary signal estimator (PSE) and K single user a posteriori

probability (APP) decoders (DECs), the data is iterated for pre-decided number

iterations before finally taking hard decision on it.

Figure 2.4: IDMA transmission in single path

For single path propagation, as shown in figure 2.4, there is only one path for

the transmission. The multiple access and coding constraints are considered separately

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in the PSE and DECs. The outputs of the PSE and DECs are extrinsic log-likelihood

ratios (LLRs) about k j , assuming y as the output of PSE and DEC with x as

input for analysis purpose, is defined below as,;

( | ( )) 1

( ) log , ,( | ( )) 1

kk

k

p y x je x j K j

p y x j

.. (2.4.2)

Those LLRs are further distinguished by subscripts, i.e.,

and , depending on whether they are generated by the PSE or DECs.

( )PSE ke x j

( )DEC ke x j

For the PSE section,y in (2.4.2) denotes the received channel output while for

the DECs, y in (2.4.2) is formed by the deinterleaved version of the outputs of the

primary signal estimator (PSE) block. A global turbo type iterative process is then

applied to process the LLRs generated by the PSE and DECs blocks [76].

2.5.2.1. Basic Primary Signal Estimator (PSE)

Assuming that the channel with no memory and after chip matched filtering, the

received signal from K users, for single path as shown in figure 2.4, can be written as;

j = 1, 2 J ..... (2.4.3)1

( ) ( ) ( ),K

k k

k

r j h x j n j

where is the channel coefficient for user-k and {n (j)} are samples of an AWGN

process with zero mean and variance, . Assuming that the channel

coefficient { } are known a priori at the receiver. Due to the use of random

interleaver {

kh

20 / 2N

kh

k }, the PSE operation can be carried out in a chip-by-chip manner, with

only one sample used at a time. r j

( ) ( ) ( )k k kr j h x j j .. .. (2.4.4a)

where,

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' ''

( ) ( ) ( ) ( ) ( )k k k k k

k k

j r j h x j h x j n j

... (2.4.4b)

( )k j is the distortion (including interference-plus-noise) in r j with respect to

user-k. From the central limit theorem, ( )k

j can be approximated as a Gaussian

variable, and r j can be characterized by a conditional Gaussian probability density

function;

2

( ) ( ( ( )))1( ( ) / ( ) 1) exp

2 ( ( ))2 ( ( ))

k k

k

kk

r j h E jp r j x j

Var jVar j

..(2.4.5)

where E (.) and Var (.) are the mean and variance functions, respectively.

The following is a list of the PSE detection algorithm based on (2.4.4a) ~

(2.4.5), assuming that the a priori statistics kE x j and kVar x j are

available [76]. Based on [76], the algorithm for chip-by-chip detection will now be

presented in next sub-section.

2.5.2.2. Algorithm for chip by chip Detection

Step (i): Estimation of Interference Mean and Variance

( ) ,k kk

E r j h E x j . .. (2.4.6a)

2 2 ,k kk

Var r j h Var x j

..... (2.4.6b)

,k kE j E r j h E x j k .... (2.4.6c)

2

.k kVar j Var r j h Var x j k ... (2.4.6d)

Step (ii): LLR Generation

2 . .k

PSE k kk

r j E j

e x j h Var j

. ... (2.4.6f)

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2.5.2.3. DEC Function

The DECs in figure 2.3 carry out APP decoding using the output of the PSE as the

input. With binary phase shift keying (BPSK) signaling, their output is the extrinsic

log-likelihood ratios (LLRs) ( ( ))DEC ke x j of ( )k j defined in (2.4.2), which are used

to generate the following statistics,

,....(2.4.7a)

.. (2.4.7b) ( ) tanh( ( ( )) / 2),k DEC k E x j e x j

. .....(2.4.7c)2( ( )) 1 ( ( ( )))kVar x j E x j k

In the iterative process, PSE and DEC-k exchange the extrinsic information

about ( )k

j . The CBC detection for IDMA scheme can be concluded as follows;

(1) Primary signal estimator generates PSE ke x j by (2.4.6f) for decoder DEC-k.

(2) DEC-k generates ( ( ( )))DEC ke x j , which are used to update mean and variance

of ( )k

x j .

Under the assumption that { k j } are independent, (2.4.6a)-(2.4.6d) are a

straightforward consequence of (2.4.4a) and (2.4.4b). The Step (ii), shown in

algorithm, is obtained by evaluating (2.4.2) based on (2.4.5). Algorithm shown is an

extremely simplified form for all spreading sequences to be length-1. The operations

in (2.4.6a) and (2.4.6b), i.e., generating E(r(j))and Var(r(j)), are shared by all users,

costing only three multiplications and two additions per coded bit per user. Overall,

the PSE operations shown in step (i) and step (ii), cost only seven multiplications and

five additions per coded bit per user, which is very modest [76]. Interestingly, the cost

per information bit per user is independent of the number of users K. This is

considerably lower than that of other alternatives.

1

( ( ( ))) ( ( ( )))S

DEC k ESE k

j

e x j e x j

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Figure 2.5: Flowchart of decoding mechanism in the receiver of IDMA scheme

The flowchart used for detection mechanism is presented in figure 2.5. The

iterative procedure adopted in the receiver is based on turbo processing [62]. The data

is iterated in the receiver section for the pre-decided number of iterations. After final

iteration in the receiver, the data is decoded with respective mechanism.

2.5.3. IDMA over Multipath Channels

In this section, the basic mechanism of IDMA scheme over multipath channels is

explained. The focus has been kept on the detection algorithm for IDMA scheme in

complex multipath fading channels described in [76]. IDMA scheme, as already

discussed in sub-section 2.5.2, is a recently proposed multiple access scheme, in

which user-specific interleavers are adopted as the only mechanism for user

separation. It can be honored as a particular case of chip interleaved CDMA scheme

[103]. The figure 2.6 shows the multipath transmission for IDMA scheme.

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Figure 2.6: IDMA in multipath transmission

As so, IDMA scheme inherits many advantages of CDMA scheme including

easy treatment for multipath fading. With the help of random interleaving and chip by

chip (CBC) iterative multiuser detection algorithm, the IDMA scheme is applicable to

cancel MAI and ISI effectively and support systems with large numbers of users in

multipath fading channels.

The upper part of Fig. 2.3 presents the transmitter structure of the IDMA

scheme with K simultaneous users. Let be the data stream of user-k. This data

stream is encoded by a forward error correction (FEC) code, generating a chip

sequence . (Here, the spreaded data is denoted by chip instead of bit as the FEC

encoding may include spreading or repetition coding.) Then is permutated by a

user-specific interleaver-k to produce chip sequence . After quadrature phase shift

keying (QPSK) symbol mapping, the symbol sequence

kd

kc

kc

kv

kX =T[ ..........; ( );..........; ( )]k k k(1);x x j x J is produced, where J is the frame length.

Either superscripts Re and Im or function notations Re(.) and Im(.) are used to

indicate real and imaginary parts, respectively. After symbol mapping, it is observed

that,

Re Im( ) ( ) . ( );k k k

h l h j i h j (2.4.8)

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where Re ( )k j and

Im ( )kx j are two coded bits from . The mapping rule for QPSK

usedin the simulations is given as follows:

kv

(0, 0) (1,1)

(0,1) (1, 1)

(1,1) ( 1, 1)

(1,0) ( 1,1)

(2.4.9)

A multipath propagation channel modeled by a tapped delay-line with several

non-zeros taps is used in the simulation. The fading factor of each tap is Rayleigh

distributed random variable. The power profile and time delay profile can be set. The

channel coefficient can be expressed for several scattered impulses received from L

different paths as .[ (0), (1),.........., ( 1)]k k k k

h h h h L

For1

( )0

l

l

if

otherwise

(2.4.10)

And is the impulse response of path-l with the amplitudel

h lh the phase l , the

propagation time delayl and the Doppler frequency shift ,D lf . As the Doppler Effect

is not taken into account in the simulation, the channel model is simplified for channel

impulse response composed of several scattered impulses received from L different

paths as,

1( )

0

( ) ( ),lL

l

l

h h e

l

....(2.4.11)

As it is assumed that the fading coefficients do not change within one

simulation frame, this channel model is referred as quasi-static Rayleigh fading

multipath channel.

Assuming an L-path channel model with fading coefficients

for user-k, . The received

signal for multipath channel as shown in figure 2.6, can be represented by,

[ (0), (1),.........., ( 1)]k k k k

h h h h L Re Im( ) ( ) . ( )k k k

h l h j i h j

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.

( ) ( ). ( ) ( )k k

k l

r j h l x j l n j ,(2.4.12)

where are the samples of a complex AWGN process with variance( )n j 2 in each

dimension.

As illustrated in lower part of figure 2.3, an iterative sub-optimal receiver

structure is adopted, which consists of a primary signal estimator (PSE) and K single-

user APP decoders (DECs). The multiple access and coding constraints are considered

separately in the PSE and DECs. In the iterative detection process, the PSE and DECs

exchange extrinsic information in a turbo-type manner [76].

The outputs of the ESE and DECs are LLRs about Re Im{ ( ), ( )k k

}x j x j k (j)as

defined below:

Re

Re

Re

( ( ) 1)( ( )) log

( ( ) 1)

k

k

k

p y x je x j

p y x j

)

)

,..(2.4.13)

These LLRs are further distinguished by subscripts, i.e.,

and , depending on whether they are generated by the PSE or DECs. For

the PSE,y in (2.4.13) denotes the received channel output. For the DECs,y in (2.4.13)

is the deinterleaved version of the outputs of the PSE. A global turbo-type iterative

process is applied to exchange the LLRs generated by the PSE and DECs, as detailed

below. Here, the focus has been maintained on detecting

Re( ( )PSE k

e x j

Re( ( )DEC ke x j

Re ( )k

x j after receiving r.

( Im ( )kx j can be handled in a similar same way.) The CBC detectionalgorithm includes

PSE and DEC part as discussed below.

Now, concentrating on the detection of Re ( )kx j for user-k from path-l and

rewrite (2.4.12) as,

,( ) ( ). ( ) (k kr j l h l x j j)l ;.. (2.4.14)

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where,( )

k lj consists of the MAI from other users, ISI of the multipath propagation

and the noise. Denote the conjugate of ( )k

h l by . The received signal is*kh

2*

,( ) ( ). ( ) ( ) . ( ) ( ),k k kr j l h l r j l h l x j j k l . (2.4.15)

where *, ,( ) ( ). ( ),

k l k k l j h l j

By the central limit theorem,, ( )k l j

can be approximated as a Gaussian

variable. This approximation is used by PSE to generate LLR for ( )k j

Im (r j

.The phase

shift due to be cancelled out in (2.4.15), which means that is not a

function of

( )k

h l

Re (k

)l

)x j ). Denoting Rer j j l ( ) (l r ) , for simplicity, from 2.4.13,

2 ( ) (

( ( ))

k

k

E

j

( )),

j( ( ) ( ) | .

PSE k

r j le x j l

Var

) 2 |

kh ...(2.4.16)

And1

0

( ( )) ( ( ))L

PSE k PSE k l

l

e x j e x j

..(2.4.17)

where it is assumed that the distortion components in the received samples from

different paths are uncorrelated, so that the LLR values based on individual chips can

be directly summed.

The basic mechanism of rest of the receiver section is similar to that of single

path transmission as explained in sub-section 2.5.2. However, the algorithm is given

below.

Denoting received signal as, ,

( ) ( ) ( )k l k k l

r j l h x j j for ,1,... 1j J L

Then,

',

,

( ( )) ( ( ))k l k

k l

E r j h E x j l .(2.4.18)

2 2

,

,

( ( )) ( ( ))k l k

k l

Var r j h Var x j l (2.4.19)

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Also,

,( ( )) ( ( )) ( ( ))

k l k l k E j E r j l h E x j

, ..(2.4.20)

2

, ,( ( )) ( ( )) ( ( ))k l k l k Var j Var r j l h Var x j .(2.4.21)

The output of PSE section is obtained as,

,

,

,

( ) ( ( )( ( )) 2

( ( ))

k l

PSE k l k l

k l

r j l E je x j h

Var j

)

....(2.4.22)

And1

0

( ( )) ( ( ))L

PSE k PSE k l

l

e x j e x j

,...(2.4.23)

The decoder part performs the APP decoding action using the output of PSE

section as its input.

( ) tanh( ( ( )) / 2),k DEC k E x j e x j

( ( )) 1 ( ( ( )) / 2)k k

Var x j E x j

Since, during the detection process, ESE combines the LLR values related to

all the paths, in RAKE manner, the detection algorithm is referred to as IDMA with

LLR combining (LLRC) in [76].

In the next section, the literature survey related to IDMA systems is presented.

Though, during the survey, overall view of various mechanisms related to researches

and applications have been duly presented, however, more attention have been paid

towards user-specific interleavers, referred as heart of IDMA systems.

2.6. Literature Survey

A conventional CDMA system includes separate coding and spreading operations

during the transmission mechanism of data. Theoretical analysis demonstrates the

optimal multiple access channel (MAC) capacity subject to reservation of entire

bandwidth devoted for coding, suggesting the combination of coding and spreading

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operations using low-rate codes for maximizing the coding gain. But separation of

users without spreading operation is not feasible in CDMA or in its variant such as

multi carrier CDMA (MC-CDMA) systems [11, 76].

In CDMA scheme, user-specific PN sequences are employed as the only

means of user separation by performing spreading operation on user-specific data [27,

17]. As already stated, CDMA system suffers with lot many problems including MAI,

unsuitability for high-speed burst-traffic, and poor orthogonality of PN codes. So,

keeping in mind the future requirement of wireless communication [5], it becomes

mandatory to look for alternate solution for user separation.

Now, the question arises regarding alternate strategy for user separation. The

possible solutions include narrow band coded-modulation scheme using trellis code

structures [61] and employment of chip-level interleavers [98, 99, 61, 62].

By assigning different interleavers to various users, the improvement in

CDMA scheme has already been reported in [62, 71]. Therefore, the possible solution

to the problem of user separation could be to employ chip-level interleavers [97]. This

principle has been considered previously and its potential advantages have been well

demonstrated [103] showing the possibility of employing interleaving for user

separation in coded systems. For wideband systems, the performance improvement by

assigning user-specific interleavers to various users in conventional CDMA has been

demonstrated in [98]. In [63], study of chip-interleaved CDMA scheme and its

application with maximal-ratio-combining (MRC) technique has been carried out for

combating the problem of inter-symbol interference (ISI) in multiple access channels

(MACs). An interleaver-based user separation scheme, known as interleave-division

multiple-access (IDMA) scheme, has also been reported, in [76, 77] for high spectral

efficiency, improved error performance, and low receiver complexity.

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The interleave-division multiple-access (IDMA) scheme is a technique that

relies on interleaving as only means for user separation [76]. IDMA not only inherits

lot many advantages from conventional CDMA, including robustness against fading

and mitigation of cross-cell interference, but also accommodates very simple chip-by-

chip (CBC) iterative multiuser detection (MUD) strategy [63] while achieving

impressive bit error rate (BER) performance. The IDMA system with random

interleavers performs similar or even better than its comparable counterpart i.e.

CDMA system. An IDMA system along with randomly and independently generated

interleavers has been presented in [76].

In IDMA systems, there exist several areas which are still open for the

researchers. Few of them includes optimal design of integral component of IDMA

communication system and further application of IDMA mechanism in other areas

including satellite communication, LAN networking, optical communications, power

line communications, MIMO systems, and UWB technologies. In addition to it,

horizons are still open for investigation about optimum modulation, channel coding,

spreading, interleaving, and detection mechanisms.

In [15, 17-19], an overview of CDMA scheme is presented with all the

inherent fruits inside it. In [88], authors have compared orthogonal and non-

orthogonal multiple access schemes and have concluded that multiple access schemes

such as schemes using spread spectrum communication are superior to their counter-

parts.

If multiple transmitters or receivers are employed for data communication, it

results in improvement in performance of system [8]. However, implementation of

multiple-input multiple-output (MIMO) system imposes lot of complexities along

with its optimal performance in [23, 20]. The application of IDMA scheme with

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MIMO systems has been discussed in [123]. Another evolving technology for IDMA

systems, the cooperative communication technique is also in its developmental stage

and is difficult for its implementation due to its inherent problems including

synchronism amongst users and complexity involved with its transmitters and

receivers. The cooperative relay diversity [138] has also been demonstrated in [125,

126, 124] for IDMA systems.

For orthogonal frequency-division multiple-access (OFDM) systems,

importance of interleaving has been duly identified in [116]. However, its application

with IDMA scheme is explored in [119, 143, 142]. In [119], OFDM-IDMA system

has been analyzed for peak power limitations. In [144], the factor graph based design

of OFDM-IDMA receiver is presented claiming its superior performance in

comparison to conventional receiver. The OFDM-IDMA system shares superior

performance in comparison of OFDM-CDMA systems [143]. Also in [121], the

performance comparison of chip interleaved MC-CDMA with that of MC-IDMA has

been discussed. The simulation results have demonstrated the better BER

performance of MC-IDMA systems to their counterpart for higher user count. As a

candidate of fourth generation mobile communication, the application of IDMA

mechanism has been discussed in [24, 132, 133, 135]. The security issue in IDMA

systems has also been taken up in [129].

The application of space time codes [33, 34, 35] have been duly demonstrated

in IDMA scheme in [71] with its superior performance to other codes. LDPC codes

have also been tested on IDMA scheme in [43, 41, 42], however, the IDMA performs

better with conventional convolutional codes and turbo codes for higher user count

including multipath environment [76, 43]. In [21, 22], chip interleaved based scheme

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has been demonstrated in ultra wide band (UWB) systems with superior performance.

However, UWB systems are under still developmental stage.

Various detection schemes [57, 51, 137] has also been reported for CDMA

systems in [45, 54, 63, 77]. For IDMA systems, the detection scheme employing turbo

processing based detection algorithm [62] has been demonstrated in [39, 71, 72] for

IDMA systems. In [52], various other low cost multi-user detectors, for IDMA

systems, have been discussed. In [49], blind detection based algorithm has been

presented. In [60], exit chart based detection algorithm has been demonstrated.

Various other detection algorithms have been presented in [58, 59]. In [120, 68],

detection mechanism based comparison between IDMA and CDMA schemes has

been demonstrated. In addition to it, various power allocation algorithms have also

been studied in [80-85, 87-90] for IDMA systems.

Employment of interleavers has also been explored with turbo codes in [95,

96, 29] and convolutional codes in [99]. Various interleaving schemes have also been

studied in the literature for CDMA systems [97-99, 112]. However, in [103],

researchers have reported the interleavers for the purpose of user separation and

demonstrated its superior performance over other similar schemes.

The implementation and performance comparison of various orthogonal and

non-orthogonal interleavers on field-programmable gate-array (FPGA) is also another

area of research. The designing of convolutional interleaver is duly explained in

[146], however, in [145], the FPGA implementation of convolutional interleaver has

been demonstrated. The convolutional interleaver is not termed as orthogonal

interleaver and hence cannot be used in IDMA scheme.

Criteria for a good interleaver design for IDMA include low memory

requirement, easy generation, low correlation among interleavers, and low overhead

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for synchronization between user and base station [109]. The interleavers used in

IDMA system, are bound to be orthogonal in nature [91]. The orthogonality of

interleavers avoids the risk of collision of interleavers in the system [99]. Various

other conditions for orthogonal user-specific interleavers have been discussed in [91,

105]. Initially, user-specific randomly selected interleavers were employed in IDMA

systems [76]. Various other mechanisms for generation of orthogonal interleavers

have been reported in the literature. However, most of them are based on strategy

related to selection of user-specific interleavers from already calculated interleavers.

If random interleavers are employed for the purpose of user separation, then

lot of memory space will be required at the transmitter and receiver ends for the

purpose of their storage. Also, consideration amount of bandwidth will be consumed

while transmission of all these interleavers. There are also other parameters of interest

with the interleavers including computational complexity at the receiver end. For

solution of problems related to high memory requirement and bandwidth

consumption, researches have taken lot of interest.

Many researchers have proposed the selection of user-specific interleavers

based of shifting mechanism of one randomly selected master interleaver. According

to [92], series of interleavers can be generated by circular shifting a specific pseudo

noise (PN) interleaver, which is generated by a PN sequence generator. In [94, 108],

multiple interleavers are generated by cyclically shifting and self-interleaving a

common mother interleaver in a few steps.

The 2-dimensional interleaver has been proposed in [93] by scrambling the

row indices and column indices of a traditional block interleaving matrix, and

obtaining a master interleaver. Various other user-specific interleavers, in the scheme,

are generated by circular shifting master interleaver. Besides, it is claimed that the

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minimum distance between two adjacent bits resulted from 2-dimension interleavers

is much larger than random interleaver [93].

Helical interleaver, in [107], has been reported, based on employing helically

shifting pattern on master interleaver for generation of other user-specific interleavers.

Also, in [101], a user-specific interleaver design method based on matrix cyclic

shifting is proposed for lower user count. The interleaver proposed in [100] displays

as advantages of approach as low bandwidth and memory requirements induced from

an algebraic solution and the parallel processing with negligible performance

degradations against random interleavers. It is reported to be specially suitable for

parallel implementation of multiple user detections and decoding of IDMA signals,

resulting in efficient improvements of system throughput.

The progressive edge growth (PEG) algorithm proposed for low-density

parity-check (LDPC) codes is adapted to multi-user interleave

idma with tree based interleaver_ph.d.thesis

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