DEVELOPMENT AND IMPLEMENTATION OF IMPROVED CODED OFDM SYSTEM USING SDR PLATFORM
BY
HAMOOD SHEHAB HAMID
THESIS SUBMITTED TO UNIVERSITI SAINS MALAYSIA IN FULFILLMENT OF THE REQUIREMENTS
FOR THE DEGREE OF DOCTOR OF PHILOSOPHY
SCHOOL OF ELECTRICAL AND ELECTRONIC
ENGINEERING
ACKNOWLEDGEMENTS
First of all, I express my gratitude to the almighty Allah who is the ultimate source of guidance in all our endeavors. Second our Prophet Muhammad (Peace be upon him) who commanded us to seek knowledge from the cradle to the grave. Next, I am deeply obliged and thankful to my supervisor Dr. Widad Ismail whose cordial support, motivation and timely advises made me highly comfortable throughout this research work. To Dr. Widad, your great efforts will never be forgotten. I express my gratitude to Dr. Mahmood F. Mosleh, from College of Electrical and Electronics, Baghdad, Iraq, and to Dr. Hamad Khalifa, from Alanbar Technical Institute, Falloga, Iraq, for their valuable guidances. I would also like to thank all members of staffs in the School of Electrical and Electronic Engineering. I would like to express my thanks to the technical staff who were very friendly and cooperative; thanks go to Mr. Abdul Latip and Wan Nur Hafsha. Words cannot express my gratefulness to my dear family in Iraq, especially my late father, my mother, and my late brothers Hamdan, Rabah, Alaa and Muafek. I also thank my dear brothers, Eng. Mahmud, Mukhlef, Salah, Falah, Hamad, Mushrif, Bashir, Mohamad, Samir, Munir and Ali.
Thanks are also due to all my friends in the School of Electrical and Electronic Engineering and to all my friends in the USM for their cooperation with me. My special thanks are due to my friends Ku Abdul Rahman Bin Ku Ismail and Mr. M.
Abdul Mujeebu. Last but not the least I express my gratitude to my wife Zeena and my children Hamdan, Mustafa, Mohamed and Zaenb, who have been the source of mental peace and support throughout my work. I express my gratitude to the wonderful Malaysian people who gave their kindly help to me during my stay in Malaysia.
TABLE OF CONTENTS
Acknowledgements……… ii
Table of Contents……….. iii
List of Tables………. viii
List of Figures……… ix
List of Abbreviations………. xiv
List of Symbols……… xix
Abstrak……….. xxiii
Abstract………. xxvi
CHAPTER 1 INTRODUCTION 1 1.1 Motivation……… 1
1.2 Problem Statements……….. 3
1.3 Research Objectives……… 5
1.4 Research Scope……… 6
1.5 Summary of Contributions….. ……… 6
1.6 Thesis Outline……….. 9
CHAPTER 2 LITERATURE REVIEW 11 2.0 Introduction 11 2.1 Motivation Toward Error Detection and Correction Techniques… 12 2.2 Types of Error Correction and Detection Code……… 14
2.3 Performance of Parallel Concatenated Codes………. 15
2.4 RS Codes in the Communication Systems………. 19
2.5 Viterbi Decoding Complexity……… 26
2.7 OFDM In Wimax……….. 32
2.8 Conventional OFDM Performance over the Size of FFT………… 36
2.9 Adaptive Coding and Modulation (ACM) System Design ………. 37
2.10 Implementation of Communications Systems on SFF SDR DP….. 41
2.11 Summary……… 43
CHAPTER 3 METHODOLOGY OF PROPOSED OFDM AND CHANNEL CODING SCHEME 44 3.1 Introduction……….. 44
3.2 Orthogonal Frequency Division Multiplexing (OFDM) ……… 44
3.3 OFDM System Implementations……… 47
3.4 Block Diagram of an OFDM Transceiver……….. 49
3.5 Characteristics of Mobile Radio Channels……….. 53
3.6 Generic Model of Mobile Channel……….. 56
3.7 Additive White Gaussian Noise (AWGN) Channel……… 58
3.8 Main Characteristic of Fading Channels………. 60
3.9 Doppler Shift……… 61
3.10 Rayleigh Fading Distribution……….. 63
3.11 Channel Coding……….. 3.11.1 Reed-Solomon Code Algorithm………. 3.11.2 CC Introduction………. 64 65 76 3.12 Block Interleaving with Concatenated Codes………. 3.12.1 Interleaving Process Algorithm……… 88 90 3.13 Adaptive Transmission Technique……….. 92 3.14 The ACM Technique………
3.14.1 Performance of the ACM………..
94 96
3.15 Summary……… 98
CHAPTER 4 DEVELOPMENT OF THE PROPOSED SYSTEM 100 4.1 Introduction……… 100
4.2 Evaluated OFDM System Model……… 100
4.3 The Proposed Single Carrier Transceiver……… 4.3.1 The Proposed Single Carrier Transceiver (RS Code ) …… 4.3.2 The Proposed Single Carrier Transceiver (CC)………. 103 104 104 The Proposed Coded OFDM System (COFDM) Model……….. 4.4.1 The Proposed Reed-Solomon Coded OFDM (RSCOFDM)….. 4.4.2 The Proposed CC OFDM System Model (CCOFDM)……… 106 106 108 4.5 The Proposed RS-CCOFDM with Block Interleaver………. 109
4.6 New Scheme of (RS-CCOFDM)……….. 111
4.7 The Proposed ACM System Design………. 114
4.8 The Proposed ACM Algorithm ……… 118
4.9 Summary……….. 121
CHAPTER 5 RESULTS AND DISCUSSION FOR PROPOSED SYSTEM SCHEME 123 5.1 Introduction………... 123
5.2 Performance of Conventional OFDM System………
5.2.1 Performance under Various Types of Channels………..
5.2.2 Performance as a Function of FFT Size ……….
5.2.3 Performance at Various Level of Constellation Mapping………
123 123 124 126 5.3 Performances of RS Code……….
5.3.1 RS Performances as a Function of Code Rate………..
5.3.2 RS Performances as a Function of Block Size……….
126 127 128
5.4 CC Performances ………
5.4.1 CC Performance as a Function of Constrain Length………
5.4.2 CC Performance as a Function of Code Rate………
5.4.3 Performance of Variable Code Rate Using Puncturing …………
129 129 131 132 5.5 Coded OFDM (COFDM) Performances………
5.5.1 Reed-Solomon Coded OFDM (RSCOFDM) Simulations……..
5.5.1.1 BER Performance over Rayleigh Selective Fading………
Channel
5.5.1.2 Performance over Flat Fading and AWGN Channels…….
5.5.1.3 IEEE802.16e; Performance for Different Mapping and….
Coding Profile
5.5.2 Convolutional Coded OFDM (CCOFDM) Simulations…..
133 133 134 135 136 143 5.6 Symbol and Bit Interleaver COFDM Simulations and Performances… 147 5.7 The Performance of Proposed RS-CCOFDM Schemes ………….
5.7.1 RS-CCOFD Performance over RS (127, 89, 7) with CC (2, 1, 3)..
5.7.2 Evaluation of New RS-CCOFDM Scheme over RS (60, 54, 6) with CC (3, 1, 3)………..
5.7.3 Performance of Proposed Concatenated RS-CCOFDM Scheme for WiMAX………..
149 149 151 153 5.8 Evaluation of proposed ACM system………
5.8.1 Data Rate Gain from ACM over Non ACM………..
156 159 CHAPTER 6
REAL-TIME HARDWARE IMPLEMENTATION: CODED-OFDM
16
6.1 Introduction………. 162
6.2 SDR Development Platform Overview and Advantages……… 164 6.3 SDR Environment Setting……… 166 6.4 Experimental Setup Introduction………..
6.4.1 Steps of the Experimental Setup………..
6.4.2 The Full System integration and implementation processes…
171 171 174
6.5 Memory Allocation……… 176
6.5.1 CMD File………
6.5.2 The DSP Compiler Options Block………..
176 177 6.6 Implementation Results ………... 178 CHAPTER 7
CONCLUSIONS AND SUGGESTIONS FOR FUTURE WORK
7.1 Conclusions……….. 184 7.2 Suggestions for Future Research………. 186 REFERENCES………. 187 APPENDIX A ………..…..
RS DECDING PROCEDUR
196 APPENDIX B ………..
CC DECDING PROCEDURE
207 APPENDIX C ………..
SFF SDR DEVELOPMENT PLATFORM
211 APPENDIX D ………..
Reed-Solomon Codes Fundamentals and Describe of Paramount Features
223 APPENDIX E ……….
Performance Analysis of Convolutional Code
230 APPENDIX F ………..
Designing Digital Communication System
236 APPENDIX G………
Matlab M-Files Simulation Programs
249 PUBLICATIONS……… 261
LIST OF TABLES
Page Table 2.1 WiMAX Standard Parameters (WiMAX Forum, 2009) 35 Table 3.1 The Field Elements for GF(8) with p(x)=x3+x+1 69
Table 3.2 Addition Table 71
Table 3.3 Multiplication Table 71
Table 3.4 The States of Encoder Figure. 3.18 80 Table 3.5 The Modulation Scheme and the Coding Rates 96
Table 4.1 OFDM Proposed Parameters 102
Table 4.2 The Proposed Mandatory Concatenated Channel Coding 111 Table 4.3 The New Parameters of RS-CCOFDM scheme 112 Table 4.4 Summary of Showing Different Features between Conventional
Parameters of RS-CCOFDM and Proposed New Parameters
113 Table 4.5 Proposed Coding and Modulation Scheme for WiMAX
Protocol
115 Table 4.6 ACM Scheme to SNR Range for the 10-2 BER Target 117 Table 4.7 Coding and Modulation Scheme Implemented by Roca (2007) 117 Table 5.1 The proposed Generators Employed in Section 5.4.1 130 Table 5.2 Proposed Generator Polynomial for Each Code Rate in Section
5.4.2
132 Table 5.3 IEEE802.16e; Modulation and Coding Proposed Profile 137 Table 5.4 SNR Code Gain at BER Level 10-4 for Different Modulation
and Coding Profile
141 Table 5.5 The Proposed Parameters of CC in Section 5.5.2 143 Table 5.6 Code Gain for Various CCR over Three Type of Channel 145
LIST OF FIGURES
Page Figure 1.1 Wireless propagation environment 2 Figure 2.1 Current and Future Mobile Systems. (Tjelta et al., 2001and
DoCoMo, 2000
12 Figure 2.2 Turbo Encoder Implemented by Yuan etal. (2002) 17 Figure 2.3 Serial Concatenated Encoder Implemented by Yuan et al.
(2002).
17 Figure 2.4 BER Performance Parallel Concatenated Codes over Serial
Codes on Rayleigh Fading Channel (Yuan et al., 2002).
18 Figure 2.5 Schematic Diagram of Basic Structure of Communication
System
20 Figure 2.6 FEC Using RS Code in the Communication System (Shih,
2000).
22 Figure 2.7 FEC Coded OFDM Communication Systems Used by Julien
(2007).
23 Figure 2.8 Structure of the Transmitter (Lee et al., 1998). 28 Figure 2.9 BER Performance at High SNR of Concatenated RS-
CCOFDM (Nyirongo et al., 2006).
31 Figure 2.10 MB-OFDM System Block Diagram Used by Nyirongo et al.
(2006).
32 Figure 2.11 Convolutional Encoder Implemented by Wimax: Roca (2007)
and Hasan (2007).
34 Figure 2.12 The BER Target Achieved By Roca (2007) 40 Figure 2.13 The Achievable Capacity of ACM Scheme over a non ACM
Scheme (Bosanska,2008)
41 Figure 3.1 OFDM Signal (a) Conventional Multi-carrier Technique (b)
Orthogonal Multi-Carrier Modulation Technique (Mondin, 2008).
45
Figure 3.2 Spectra of (a) an OFDM Subchannel and (b) and OFDM Signal (Mondin, 2008)
46 Figure 3.3 The Block Diagram of Basic OFDM Transceiver 50 Figure 3.4 Gray Coded PSK, QPSK, and 16-QAM signal constellations 51 Figure 3.5 Cyclic Prefix of OFDM Transmitted Symbol (Hasan, 2007) 52 Figure 3.6 The Multi Path Receiving Signals. 54
Figure 3.8 The Signal Bandwidth and the Channel Frequency Response (Langton, 2004)
56 Figure 3.9 The Block Diagram of Generic Model for a Point-to-Point
Communication System.
57 Figure 3.10 Model for Received Signal Passed through an AWGN
Channel
57 Figure 3.11 Equivalent of (a) Wideband and (b) Complex baseband
AWGN
59 Figure 3.12 Probability Density Function of AWGN 59 Figure 3.13 Illustration of Doppler Effect 62
Figure 3.14 Pdf of Rayleigh Distribution 64
Figure 3.15 Reed Solomon Code (Clarke, 2002) 66
Figure 3.16 Reed-Solomon Code Algorithms 67
Figure 3.17 LFSR Proposed Encoder Architecture for RS Code 74 Figure 3.18 A Code (CR=1/2 ) Convolutional Encoder 77 Figure 3.19 State Diagram of (2, 1, 3) C Encoder 79
Figure 3.20 Three Stages of Trellis 81
Figure 3.21 The Sequence of States through Encoder Trellis 82 Figure 3.22 Schematic Diagram of Transmission System, U L- Input
Sequence, vL-Output sequence.
83 Figure 3.23 A Binary Symmetric Channel (BSC) (Proakis et al., 2004) 84 Figure 3.24 Trellis Initial Punctured Code 87
Figure 3.25 CC Algorithm 87
Figure 3.26 A Concatenated Code 88
Figure 3.27 Interleaving during Channel Coding 89
Figure 3.28 The Block Interleaver. 89
Figure 3.29 The Principle of Interleaver Process Algorithm 91
Figure 3.30 ACM utilization 95
Figure 3.31 BER vs. SNR Relationship and Corresponding SNR Threshold for H Coding and Modulation Schemes Employed by ACM
97
Figure 3.32 The Flowchart of Overall System Methodology 99 Figure 4.1 Block Diagram of OFDM Proposed System Model ` 101 Figure 4.2 Proposed Single Carrier Transceiver RS, or CC. 103 Figure 4.3 Proposed Single Carrier Transceiver RS Code 104 Figure 4.4 Proposed Single Carrier Transceiver CC. 105 Figure 4.5 Proposed RS Coded OFDM (RSCOFDM) 106
Figure 4.6 Proposed CCOFDM System 108
Figure 4.7 Proposed RS-CCOFDM With Block Interleaver 110
Figure 4.8 New Scheme of RS-CCOFDM 112
Figure 4.9 Block Diagram of a New ACM System Design 114 Figure 4.10 Seven Curves for Different ACM Schemes over the Flat
Fading Channel
116
Figure 4.11 Algorithm of New ACM System 120
Figure 4.12 Flowchart of Overall Development System 122 Figure 5.1 BER Performance Conventional OFDM over Three Channels
Scenarios
124 Figure 5.2 OFDM Performances with Various FFT Size 125 Figure 5.3 OFDM Performances at Various Modulation Levels 126 Figure 5.4 Reed-Solomon (63, k) Decoder Performance as a Function of
Redundancy
127 Figure 5.5 Reed-Solomon Performances as a Function of Symbol Size 129 Figure 5.6 Performance of CC With Various Constrain Length 130 Figure 5.7 CC Performance as a Function of Code Rate 131 Figure 5.8 Performance of CC with Variable Rate using Puncturing 133 Figure 5.9 RSCOFDM Performances over Rayleigh Selective Fading
Channel
134 Figure 5.10 RSCOFDM Performances over Rayleigh Flat Fading Channel 135 Figure 5.11 RSCOFDM Performances over AWGN Channel 136
Figure 5.13 RS Codes Effect on OFDM over 16 QAM Selective Fading 138 Figure 5.14 RS Code Effect on OFDM over 64 QAM Selective Fading 139 Figure 5.15 RS Code Effect on OFDM over QAM Flat Fading 139 Figure 5.16 RS Code Effect on OFDM over 16 QAM Flat Fading 140 Figure 5.17 RS Code Effect on OFDM over 64 QAM Flat Fading 140 Figure 5.18 RS Code Effect on OFDM over QAM AWGN 141 Figure 5.19 RS Code Effect on OFDM over 16 QAM AWGN 142 Figure 5.20 RS Code Effect on OFDM over QAM AWGN 142 Figure 5.21 Performance of CCOFDM at Variable Code Rate over
AWGN Channel.
144 Figure 5.22 CCOFDM Performance at Various Code Rate for Flat Fading
Channel
144 Figure 5.23 Performance of CCOFDM over Selective Fading Channel at
Various Code Rates.
145 Figure 5.24 Performance of CCOFDM over Selective Fading Channel
with Various Constraint Length and Code Rate
146 Figure 5.25 RSCOFDM Performance with Different Interleaver Types 148 Figure 5.26 The Effect of Bit Interleaver on CCOFDM Performance 149 Figure 5.27 RS-CCOFD Performance over RS (127, 89, 7) with CC (2, 1,
3)
150 Figure 5.28 RS-CCOFD Performance over RS (60, 54, 6) with CC (3, 1,
3)
152 Figure 5.29 RSCCOFDM performance over Single Code 153 Figure 5.30 WiMAX Standard Parameters Performance over OFDM. 155 Figure 5.31 Proposed RS-CCOFDM Performance over WiMAX Standard 156 Figure 5.32 The Performance of Proposed Scheme Compared with ACM3 158 Figure 5.33 The Influences of Varying the Target BER in the ACM
Mechanism
158 Figure 5.34 Throughput of ACM3 Compared to non ACM 159 Figure 6.1 The SFFSDR DP board (Texas instrument, 2009). 164
Figure 6.2 The SFFSDR DP Module 165
Figure 6.3 Developed System Model for IEEE Std.802.16 WiMAX 167
Figure 6.4 Simulation Setup 168 Figure 6.5 Proposed RS-C COFDM System for IEEE802.16 WiMAX 169
Figure 6.6 Channel Encoding Setup 170
Figure 6.7 Channel Decoding Setup 170
Figure 6.8 The Setting of Data Format 172
Figure 6.9 Real –Time Workshop (RTW) Setting 172 Figure 6.10 Verification Setting of Data Format Target Selection 173
Figure 6.11 External Module 173
Figure 6.12 The Overall Schematic Flow Diagram System Designed 175
Figure 6.13 Memory allocation 176
Figure 6.14 The DSP Compiler Options Block Setting 177 Figure 6.15 RS-CCOFDM Performance Compared with Single Code 179 Figure 6.16 The Performance of RS code over (60, 54, 6) 179 Figure 6.17 The Performance of CC over (3,1,3) 180 Figure 6.18 Performance of RS-CCOFDM over RS Code 180 Figure 6.19 Performance of RS-CCOFDM over CC 181
Figure 6.20 The Performance of RS-CCOFDM 182
Figure 6.21 RS-CCOFDM Performance over no Code 182
LIST OF ABBREVIATIONS
2G 2nd Generation
ACM Adaptive Coding and Modulation
ADC Analog-to-Digital Converter
ADSL Asymmetric Digital Subscriber Line AGC Automatic Gain Control
ARQ Automatic Repeat Request ASK Amplitude Shift keying
AWGN Additive White Gaussian Noise
BCH Bose-Chaudhuri-Hocquenghem codes
BER Bite Error Rate
BSC Binary Symmetrical Channel
CC Convolutional Codes
CCOFDM Convolutional Coded OFDM CMD Command File Generator Block CCR Convolutional Codes Rate CDMA Code Division Multiple Access
COFDM Coded OFDM
CP Cyclic Prefix
CR Code Rate
CSI Channel State Information ECC Error Correcting Code dB Decibel DFT Discrete Fourier Transform DP Development Platforms DSP Digital Signal Processor FDD Frequency Division Duplex
FDM Frequency Division Multiplexing FEC Forward Error Correction
FFT Fast Fourier Transform
FSK Frequency Shift Keying
GF Galois Field
GMD Generalized Minimum Distance GPP General Purpose Processor
ICI Interchannel Interference
IDFT Inverse Discrete Fourier Transform
IEEE Institute of Electrical and Electronics Engineers
IF Intermediate Frequency
IFFT Inverse Fast Fourier Transform
ISI Inter-symbol Interference
LDPC low Density Parity Check LFSR Linear Feedback Shift Register
LSR Linear Shift Register
lsb Least Significant Bit
LOS Line Of Sight
MBS Mobile Broadband Services MB-OFDM Multiband-OFDM
ML Maximum-Likelihood MIMO Multiple Input Multiple Output msb Most Significant Bit
MMSE Minimum Mean-Squar-Error
MQAM Multiple Quadrature Amplitude Modulation NLOS Non-Line of Sight
OFDM Orthogonal Frequency Division Multiplexing PAR Peak to Average Ratio
PCE Probability of Codeword Error Pdf Probability Density Function
Psd Power Spectral Density
PSK Phase Shift Key
PHY Physical Layer
QAM Quadrature Amplitude Modulation QPSK Quadrature Phase Shift Keying R & D Research and Development
RF Radio Frequency
RS Reed-Solomon Code
RS-CC Reed-Solomon and Convolotional Code
RS-CCOFDM Reed-Solomon and Convolotional Coded OFDM RSCOFDM Reed-Solomon Coded OFDM
RTW Real-Time Workshop
SDR Software-Defined Radio
SFF Small Form Factor
SFH Slow Frequency Hoping
SISO Soft-Input, Soft-Output SNR Signal to Noise Ratio
UWB Ultra Wide Band
TLC Target Language Compiler
WSSUS Wide Sense Stationary Uncorrelated Scattering
Wi-Fi Wireless Fidelity
WiMAX Worldwide Interoperability for Microwave Access XOR Exclusive OR Gates
LIST OF SYMBOLS
a Coefficient of polynomial expression for Galois Field element Bc Coherence bandwidth
BNo The Noise Inside the Bandwidth c Output of CC
CR The Code Rate of any Code dmin Minimum Distance of Codeword
dri The Distance between L Dimensional Received Vector E(x) The Error Pattern of RS Codes
ei Locations of Error in RS Codeword f Frequency Index
fd Doppler Shift
h Column Index of Interleaver H Number of SNR Regions of ACM k Number of Information Symbols or Bits K Constraint Length of CC
L Dimensional Received Vector
Ĺ Tracking the Order of the Equations for Berlekamp's Algorithm
m Number of Bits per Symbol
M(x) The message to be Encoded in RS Codes n Number of Codeword symbols
N Number of Elements in Galois Field n(t) Sample Function of Noise
Nc Number of Subchannel of an OFDM No One-Sided psd
P Probability of Error p Puncturing Matrix P(.|.) Conditional Probability P(x) Primitive Polynomial
q(x) The Quotient of Division Process RS Codes Qi(x) The Quotient of Dividing Process for RS
) ( i
Rα The Symbol Received Codeword
r(t) The Received Signal
r(x) The Remainder of Division in RS Codes R(x) The Received Codeword
S Number of Memory in CC
s(t) The Transmitted Signal Si The Syndromes Polynomial T IFFT Input symbol Period
t The Symbol Error Correcting Capability of RS Codes t' Time Index of CC
T(x) The Transmitted Codeword in RS Codes Tc Coherence Bandwidth
Tg Length of CP
Ts Symbol Time Duration
Tx The Starting of Sampling Period v Number of Errors in RS Codeword vd Velocity of Mobile Unit
w Row Index of Interleaver
x Location in Polynomial Equation
xri Code Subvector of rth Message Sequence for ith Branch Level Yi Error Values at Each Location of RS Codeword
Ҝ The Step parameter of Berlekamp's Algorithm
τmax Maximum Multipath
σ2 The Variance of the Noise
τ
Delay spreadσ τ Root-Mean-Square Delay Spread (x)
σ Error Locator Polynomial of RS Codes
(t)
φi Complex- valued function for interval (t1), i is integer.
(t)
φj Complex- Valued Function for Interval (t2) , j is Integer α Primitive Element
β Received Signal Length
(x)
Λ Alternative Form of Error Locator Polynomial
(x)
Ω Error Value Polynomial for RS Codeword
)
( 1
' −
Λ Xj
Derivative of Λ(x) γ Time Index
Ψ Standard Deviation
PEMBANGUNAN DAN IMPLEMENTASI PENAMBAHBAIK KOD SISTEM OFDM DENGAN MENGGUNAKAN PLATFORM
SDR
ABSTRAK
Peningkatan permintaan untuk sambungan tanpa wayar berkelajuan tinggi dengan kos rendah merupakan cabaran baru bagi para pereka bentuk sistem komunikasi, untuk melaksanakan penyelesaian yang meningkatkan kadar data supaya lebih berkesan dengan memanfaatkan sumber radio yang terbatas pada tahap kerumitan yang rendah. Kod Mudahsuai dan Modulasi (ACM) memanfaatkan keanjalan kod saluran dan gugusan dalam Pemultipleksan Pembahagian Frekuensi Ortogonal (OFDM) untuk mendapatkan kelajuan data yang lebih tinggi. Teknik ini menggunakan beberapa modulasi dan skim pengekodan untuk segera menyesuaikan diri dengan kepelbagaian dalam saluran Isyarat untuk Nisbah Hingar (SNR), dengan demikian memaksimumkan daya pemprosesan sistem dan meningkatkan prestasi Kadar Kesilapan Bit. Di sisi lain, sistem OFDM terjejas akibat gangguan antara- simbol (ISI), terutamanya dalam persekitaran komunikasi bergerak. Masalah ini dapat diatasi dengan meningkatkan tempoh simbol individu untuk setiap subpembawa bersama-sama dengan penggunaan masa adang. Namun demikian, hal ini tidak dapat menyelesaikan masalah sepenuhnya dalam saluran ketidakjelasan multi-laluan, kerana semua subpembawa akan tiba di penerima dengan amplitud yang berbeza. Malangnya, beberapa subpembawa mungkin akan hilang sepenuhnya kerana jurang ketidakjelasan yang tinggi. Oleh kerana itu, meskipun sebahagian besar subpembawa boleh dikesan tanpa kesilapan, keseluruhan BER akan sangat
ini, sistem berasaskan OFDM biasanya menggunakan teknik khas seperti pembetulan kesalahan pengekodan. Pelbagai kaedah pengekodan diadopsi oleh banyak standard untuk mengurangkan kesan memilih saluran frekuensi yang menyebabkan kesalahan bit terjadi di dalam keadaan letupan. Reed-Solomon (RS) dan Kod Konvolusi (CC) sangat berguna untuk pembetulan kesilapan-letup, begitu juga berkesan untuk saluran jurang ketidakjelasan yang tinggi. Hal ini berguna untuk meningkatkan prestasi OFDM. Tesis ini pada permulaannya mempersembahkan RS dan CC sebagai kod fleksibel untuk meningkatkan prestasi OFDM sebagai kod tunggal dan juga kod rangkaian. Selanjutnya satu ACM berdasarkan rangkaian RS dan CC untuk sistem OFDM direka. Akhirnya, perkakasan dilaksanakan dengan menggunakan faktor bentuk kecil (SFF) perisian menyatakan radio (SDR) platform-platform pembangunan (DP), untuk membandingkan prestasi penghantar terima jalur asas sistem OFDM untuk RS, CC dan RS-CC dengan saluran AWGN berdasarkan IEEE 802.16 Worldwide Interoperability untuk Microwave Access (WiMAX). Dengan perkakasan yang dicadangkan, BER akan merosot sebagai mana SNR meningkatkan dari 0 untuk 50 dB, menjadikan reka bentuk mudah dan sempurna untuk mana-mana jenis aplikasi SDR. Semua kerja-kerja tersebut sebelumnya dipersembahkan menggunakan perisian Matlab. Keputusan simulasi menunjukkan yang bit perantara- lembar menambah-baikan CC-OFDM sebanyak 9dB dan menurunkan RS-OFDM sebanyak 1.4 dB pada 10-4 BER. Skim cadangan RS-CC dengan OFDM juga boleh mencapai penambahan kod sebanyak 19 dB dibandingkan dengan sistem yang tidak dikod OFDM pada 10-4 BER, dan mengatasi sistem yang serupa dengan kod tunggal sebanyak 8dB. Tambahan pula, peningkatan baru menunjukkan persembahan terbaik pada SNR rendah. Keputusan juga menunjukkan sistem OFDM itu dengan ACM memberi persembahan terbaik terhadap kadar bit; reka bentuk yang dicadangkan
boleh mencapai kadar penambahan bit 7 Mbps pada SNR yang tinggi dibandingkan dengan skim yang tidak adaptif untuk 10-2 mensasar BER.
DEVELOPMENT AND IMPLEMENTATION OF IMPROVED CODED OFDM SYSTEM USING SDR PLATFORM
ABSTRACT
The increasing demand for high speed wireless connectivity at low cost poses new challenges for communication system designers, to implement solutions that increase the data rate by utilizing the limited radio resources more efficiently at a low additional complexity. Adaptive Coding and Modulation (ACM) exploits the flexibility of channel coding and constellation in Orthogonal Frequency Division Multiplexing (OFDM) to obtain higher data rates. This technique employs multiple modulation and coding schemes to instantaneously adapt to the variations in the channel Signal to Noise Ratio (SNR), thus maximizing the system throughput and improving Bit Error Rate (BER) performance. On the other hand, OFDM system suffers from inter-symbol interference (ISI), especially in mobile communication environments. This problem may be tackled by increasing the individual symbol duration for each subcarrier together with the use of guard time. Nevertheless, this does not solve the problem completely in multipath fading channel, because all subcarriers will arrive at the receiver with different amplitudes. Unfortunately, some subcarriers may be completely lost because of deep fades. Hence even though most subcarriers may be detected without errors, the overall BER will be largely dominated by a few subcarriers with bad SNR. To eliminate this problem, OFDM based systems usually employ a special technique like error correction coding (ECC). Various coding methods are adopted by many standards to mitigate the effects of frequency selective channel which causes bit errors to occur in burst. Reed- Solomon (RS) and convolutional codes (CCs) are particularly useful for burst- error
correction that is, they are effective for deep fades channel. It is useful to improve the OFDM performance. This thesis first presents the RS and CC as flexible codes to improve OFDM performance as single codes, and as concatenation codes.
Subsequently an ACM based on concatenation of RS and CC for OFDM system is designed. Finally, the hardware is implemented using the small form factor (SFF) software-defined radio (SDR) development platforms (DP), to compare the performance of the OFDM system baseband transceiver for RS, CC and RS-CC with AWGN channel based on IEEE 802.16 Worldwide Interoperability for Microwave Access (WiMAX). By the proposed hardware, the BER decreases as the SNR increases from 0 to 50 dB, making the design simple and acceptable for any type of SDR application. All the aforementioned works are performed by using Matlab tools.
The simulation results show that the bit interleaver improves CCOFDM by 9 dB and degrades RS-OFDM by 1.4dB at 10-4 BER. Also the proposed scheme of RS-CC with OFDM could achieve a code gain of 19dB compared with uncoded OFDM system at 10-4 BER, and outperforms the same system with single code by 8dB.
Moreover the new improvement in the proposed research has best performance at low SNR. The results also show that OFDM system with ACM gives best performance with respect to bit rate; the proposed design could achieve about 7 Mbps bit rate gain at high SNR compared with non-adaptive scheme for 10-2 target BER.
CHAPTER 1 INTRODUCTION
1.1 Motivation
Several technologies are considered to be candidates for future applications, such as Orthogonal Frequency Division Multiplexing (OFDM), which is a special form of multi-carrier transmission where all the subcarriers are orthogonal to each other.
OFDM promises a higher user level of implementation complexity (Chen et al., 2009). On the other hand, OFDM is very sensitive to frequency errors. Its performance also suffers from distortions, and Inter-Symbol Interference (ISI) caused by multipath in band-limited (frequency selective) time dispersive channels, causes bit errors at the receiver. ISI has been recognized as the major obstacle to high speed data transmission over mobile radio channels. The transmitted signal that is launched into the wireless environment arrives at the receiver along a number of distinct paths, referred to as multi-paths (Lawrey, 2001a). (See Figure 1.1). In addition, it exhibits a high peak-to-average ratio. In other words, there is a problem of extreme amplitude of the transmitted signal.
The OFDM signal is basically a sum of Nc complex random variables, each of which can be considered as a complex modulated signal at different frequencies. In some cases, all the signal components can add up in phase and produce a large output and in some cases, they may cancel each other producing zero output. Thus the Peak-to- Average Ratio (PAR) of the OFDM system is very large (Muhammad, 2005).
Figure 1.1: Wireless propagation environment.
To reduce these effects, channel coding is required which provides for forward error correction (FEC). This enables the receiver to correct the errors that have occurred in the transmission path (Lu et al., 2006). Channel coding selectively adds redundancy to the source encoded data to permit error detection/ correction at the receiver.
The channel encoding process may be considered as reverse process of source encoding in the sense that source encoding compresses the input information by reducing redundancy in it while the channel coding introduces the source encoded information. However, this redundancy is added as a result of channel coding is more logical and controlled in the nature than the inherent redundancy in the original information, and hence can be effectively utilized by the receiver to detect as well as
Mobile Obstacle
Scatterers BTS
The growing demand for all types of services aims for the design of increasingly more intelligent communication systems, capable of providing spectrally efficient and flexible data rate access. These systems are able to adapt and adjust the transmission parameters based on the link quality, improving the spectrum efficiency of the system, and reaching, in this way, the capacity limits of the underlying wireless channel (Goldsmith, 2005). The motivation of this thesis is to offer convenient remedies to overcome the drawback of OFDM system.
1.2 Problem Statements
Reliable data communication on wireless channels and high speed data transmission over mobile radio channels is a very challenging task that involves various different problems. Orthogonal Frequency Division Multiplexing (OFDM) as a candidates for future applications which promises a higher user level of implementation complexity, However OFDM performance suffers from distortions, and Inter- Symbol Interference (ISI) caused by multipath in band-limited (frequency selective) time dispersive channels, causes bit errors at the receiver.
It is necessary to choose a coding technique which provides Forward Error Correction (FEC) to mitigate OFDM influences which stems from multipath fading channel, high speed data rate, and frequency Doppler Shift emanated due to user movements that increases performance with minimal trade-offs in power and bandwidth.
The increasing demand for high speed wireless connectivity at low cost poses new challenges for communication systems designers to implement solutions that is to reduce the weight and cost. New coding schemes for low BER with lower decoding complexity is required for data communication services in order to meet higher capacity and quality demands with acceptable performance criteria over a hostile mobile radio channel.
Therefore real-time decoding without noticeable information losses typically require.
When high coding gain is required concatenated coding is approach to improve the error performance of code for a large constraint length with lower decoding complexity for this reason channel coding has become widespread in the design of digital transmission systems.
Reed-Solomon (RS) and convolutional codes (CCs) are particularly useful for burst- error correction that is, they are effective for deep fades channel. It is useful to improve the OFDM performance, but the range of SNR that achieves suitable BER is relatively high. In addition the performance is still worse with lower SNR, therefore there is need for further improvement especially when deals with mobile communication which is highly corrupted due to multipath and admissibility of the line of sight (LOS) and offer convenient remedies to overcome the drawback of OFDM system.
Significant difficulties faced by the communication designer to understand the theoretical side of OFDM systems. This causes a gap between theoretical and
processing method providers new software application in improving the reliability of digital transmission. Furthermore, new emerging technology of defined radio platform can provide a real–time communication where the message may not be delayed, also the additional of redundant bits dictates a faster rate of transmission (faster signaling, less energy per channel symbol and more errors out of the demodulator) which of course means more bandwidth.
1.3 Research Objectives
The severe channel conditions have placed a major obstruction upon designing efficient transmission systems over wireless environments. Objectives of the research are listed below:
1. To develop a novel coded OFDM (COFDM) technique, to improve OFDM system drawbacks and its features by using Reed-Solomon codes and convolutional codes (RS-CC), and combining these two codes in a concatenation technique.
2. To design an Adaptive Coding and modulation system (ACM) to improve OFDM system based on the concatenated RS-CCOFDM WiMaX protocol.
Each multistage level of mapper design, involves specific parameters of codes pairing with appropriate level of constellation, and is controlled by ACM system design related to channel condition, to increase the amount of received bit rate.
3. To implement and analyze the proposed COFDM system in real time application using software-defined radio platforms.
1.4 Research Scope
The requirement for real-time processing indeed poses challenges on implementing channel coding algorithms. Trade-off between the complexity and the effectiveness of channel coding algorithms should be taken into consideration in this work. The Small Form Factor Software defined Radio Development Platform (SFF SDR DP) is conceived and designed to be used in the development of applications in the field of software-defined radio. By separating the base band, IF, and RF from one another as distinct modules in order to extend the radio development capabilities and optimize costs and power consumption. This research work is more focus in the advanced signal processing techniques involving channel coding technique algorithms, the 4 G mobile transmissions (OFDM) System, and adaptive modulation techniques that can be easily implemented without necessitating major hardware changes in the transceiver.
1.5 Summary of Contribution
The original contribution in this work is to design of a new ACM system, based on developed concatenation of RS-CCOFDM system to increase the bit rate. Multilevel mapper is a new technique comprised of coding, decoding and feedback mechanism.
This involves the combination of adaptive coding and modulation (ACM). This combination gives more flexibility to choose specific parameters to match channel
error rate (BER) performance. This work also investigates new way of hardware implementation. New real time fills the gap between theoretical and practical sides of OFDM system by applying channel coding as new technique. The hardware is implemented using the small form factor (SFF) software-defined radio (SDR) development platforms (DP) to improve the system. The contribution of this thesis can be classified into three categories.
I. Conventional OFDM
This is an approach to improve some features of conventional OFDM system and to rectify its drawbacks. The system is tested under Rayleigh fading channel, assuming that the synchronization sometimes is lost. A relatively small size of FFT (26) under good channel conditions achieved good gain compared with bad channel conditions, the amount of information is increased relative to the size of FFT.
II. Single Carrier Transceiver
In the second testing system design, the features of block and CCs are exploited to overcome the drawbacks of each other and the performance of each code is observed in order to choose the effective parameters, this technique is then applied for OFDM system over selective fading channel, to improve the system. Hence, the benefit of increased redundancy would be the improvement in bit-error performance. Making the choice of appropriate coding and modulation techniques that are available in improving the complexity of a high-speed implementation, increases with redundancy especially for high-speed devices.
III. Coded OFDM
The Contribution of this subsection can be further classified into three categories:
1. Coded OFDM with Single Code are Categorize as Below:
A. Reed-Solomon Coded OFDM (RSCOFDM)
The improvements stem from applying RS codes making the OFDM system more robust to combat frequency selective fading which stem from multipath channels.
Therefore such a code is active for various types of channels, and offers a good improvement at BER level for a variable-rate coding scheme that depends on the channel conditions with various ranges of SNR in order to offer optimal error protection levels to the users. The technique is employed in IEEE802.16e standard.
B. Convolutional Coded OFDM (CCOFDM)
The advantage of applying CC with OFDM system gets significant benefit without affecting any of its original structure. CC improves the OFDM system under various conditions over Rayleigh fading and AWGN without fading channel, at high SNR.
However, it will be an advantage to choose convenient code rate that has trade-off between code gain and efficient spectrum with low code rate and bandwidth expansion, where it holds the constraint length at fixed value. Therefore, performance of CC is still worse if the constraint length is increased. Otherwise small constraint length gives significant improvement at low SNR.
2. Coded OFDM with Concatenated Codes (RS-CCOFDM)
Some new design and parameters are established in this subsection. These new parameters are expected to yield significant improvement to develop a concatenated code that can perform well, both at low and high SNR. It will reduce the processing
3. The Effect of Interleaver
However, real-time systems must consider tradeoffs between coding delay and error protection. Therefore, such codes perform poorly in a real-time communication system. The types of such interleavers depend on the nature of structure and its parameters; the delay time is increased with the presence of more than one inter- leaver.
1.6 Thesis Outline
The remaining chapters of this thesis are organized as follows:
In Chapter Two, literature review will be presented to highlight the systems used in this thesis, such as types of Error Correction and Detection codes. RS codes and CC in the communication system are investigated. The performance of interleaved block and CC are also investigated. The concept of concatenated multilevel codes and performance of conventional OFDM over the Size of FFT are presented in this chapter. ACM literature review, the issues of adaptive coding and modulation (ACM) associated with the previous works compared with the ACM of the present study are also presented. Finally implementation of communications systems on SFF SDR DP related with this work is presented.
In Chapter Three methodologies of proposed OFDM and channel coding scheme are presented, also this chapter describes an OFDM transceiver. The channel model was described, which is used to simulate the performance of the OFDM system. In addition the RS and CC theory is presented as optimum channel coding, followed by brief explanation about concatenated codes, and interleaver. Finally Adaptive Transmission Technique is presented in this chapter.
In Chapter Four development of the proposed system is presented. This chapter also provides a brief review on the evaluated conventional OFDM system model without any code, and with single code including RS, or CC. Conventional concatenation of RS –CC come after that, with OFDM system. Subsequently the proposed RS-CCOFDM is presented, and ACM based on the proposed COFDM transceiver is also given in this chapter.
Chapter Five is the core of this dissertation. Results and discussion for the proposed system schemes are presented, followed by evaluation of conventional OFDM system with no code, with single and concatenated codes, to enlighten the amount of improvement stem from adding each one.
Chapter Six presented new technique in analyzing developed software system design through an implementation method based on RS-CCOFDM. Real time hardware implementation COFDM are done by the small form factor (SFF) software- defined radio (SDR) development platforms (DP), making the design simple and perfect for any type of SDR application.
Chapter Seven contains conclusions and suggestions for future research.
Appendix A gives the procedure of RS decoding process and worked example.
Appendix B includes the application of Viterbi algorithm.
Appendix C includes, the implementation and applications in real-time by the SFF SDR DP.
Appendix D presents RS codes fundamentals and description of paramount features.
Appendix E describes the performance analysis of CC.
Appendix F provides the design of digital communication systems.
Finally Appendix G includes Matlab M-Files Simulation Programs.
CHAPTER 2
LITERATURE REVIEW
2.0 Introduction
Reliable data communication on wireless channels is a very challenging task that involves various different problems. In contrast to fixed line communication channels, radio channels are usually described as space, time and frequency varying channel. This is due to the severe conditions that a transmitted signal is subjected to.
Radio communication systems should be tolerant to the effect of fading of the signal due to propagation over multipath or due to shadowing (Mahmoud, 2008). The incoming signal may also suffer from Inter Symbol Interference (ISI) due to multipath propagation of the signal. Also, the wireless channel is very noisy due to interference from other communication systems and the background noise (Al- Askary, 2006).
Mobile data communication is even more challenging. In addition to the problems mentioned above, that are common to all wireless systems, there are further considerations. For example, a moving mobile unit might lead to total change of the channel conditions which requires continuous measurement and updating of the Channel State Information (CSI) and adaptation of the coding/modulation strategy to the new conditions. There are also some requirements that stem from the nature of the services in mobile communications. One of these requirements is that the mobile units should be small and energy efficient. Therefore, there is relatively little margin for energy consuming extensive signal processing. A seamless and uninterrupted
service quality for a user regardless of the system he/she is using will be one of the main goals of future systems (Tachikawa, 2003).The expected systems will require an extensive amount of bandwidth per user. Figure 2.1shows the current and future mobile systems. The general trend will be to provide higher data rates and greater mobility.
Figure 2.1: Current and Future Mobile Systems. (Tjelta et al., 2001and DoCoMo, 2000).
2.1 Motivation Toward Error Detection and Correction Techniques
The basic purpose of error detection and error correction techniques is to introduce redundancies in the data to improve wireless link performance. The introduction of redundant bits increases the raw data rate used in the link hence, increases the bandwidth requirement for a certain data rate. This reduces the bandwidth efficiency
0.03 0.1 0.3 1 3 10 30 100 Data rate Mbps
2G systems 3G systems
(2003)
4G systems (2012)
5G systems (2020)
Hiperlan/2 (2002) Stationary
Pedestrian Vehicular
Mobility
SNR values. A channel coder operates on digital message (or source) data by encoding the source information into a code sequence for transmission through the channel.
Channel coding is a common strategy to make digital transmission more reliable, or, equivalently, to achieve the same required reliability for a given data rate at a lower power level at the receiver. This gain in power efficiency is called coding gain. For mobile communication systems, channel coding is often indispensable. The bit error rate in a fading channel increases, which would require an unacceptable high transmit power to achieve a sufficiently low bit error rate. Channel coding is used with digital data to detect and to correct the errors by selectively introducing redundancies in the transmitted data. The codes that are used to detect errors are called error detection codes, while codes that can detect and correct errors are called error correction codes.
There are several ways to gain performance of an OFDM system, e.g. use of channel equalization, multiple antennas (MIMO) and channel coding. The latter one is the focus of this thesis. Forward Error Correction (FEC) is an effective tool to mitigate OFDM influences which stems from multipath fading channel, high speed data rate, and frequency Doppler shift emanated due to user movements (Maciel and Klein, 2010).
Forward Error Correction coding refers to the class of signal transformations designed to improve system performance by enabling the transmitted signal to better withstand the effects of various channel impairments, such as noise, interference, and
fading. Error correction coding is very popular because it is typically a less expensive means of improving performance when compared to other methods such installing higher power transmitters and larger antennas. This is especially true for such modern communications. The improved system performance usually involves system trade-offs such as error-performance versus bandwidth and power versus bandwidth. In digital communication systems that are both bandwidth-limited and power-limited, error-correction coding (often called channel coding) can be used to save power or to improve error performance at the expense of bandwidth. It is necessary to choose a coding technique that increases performance with minimal trade-offs in power and bandwidth (Shannon, 1948b).
2.2 Types of Error Correction and Detection Codes
Among the popular coding techniques are block codes and convolutional codes.
These techniques, however, improve system performance at the expense of expanding the bandwidth by an amount proportional to the reciprocal of the code rate. There are two basic types of error correction and detection codes: block codes, and CCs:
I. In Block Codes, parity bits are added to blocks of message bits to make codewords or code blocks. In a block encoder, k information bits are encoded into n code bits. A total of n-k redundant bits are added to the k information bits for the purpose of detecting and correcting errors. One of most important types of block codes is Reed-Solomon (RS) codes. The ability of a block code to correct errors is a function of the code distance. Many families of codes exist
II. Hamming Codes were among the first of the nontrivial error correction codes.
These codes and their variations have been used for error control in digital communication systems. There are both binary and nonbinary Hamming codes.
A binary Hamming code has the property that,
( )
n,k =(
2m−1,2m −1−m)
, where kthe number of information bits is used to form a n bit codeword, andm is any positive integer. The number of parity symbols is n−k =m.
III. Cyclic Codes are a subset of the class of linear codes which satisfy the cyclic property. As a result of this property, these codes possess a stirring amount of structure which can be exploited. Encoding for a cyclic code is usually performed by a linear feedback shift register based on either the generator or parity polynomial (Hamming, 1950).
IV. BCH Codes are among the most important block codes since they exist for a wide range of rates, achieve significant coding gains, and can be implemented even at high speeds. The block length of the codes is n=2m−1 for m≥3, and the number of errors that they can correct is bounded by t<
(
2m −1)
/2. Thebinary BCH codes can be generalized to create classes of non-binary codes which use m bits per code symbol. The most important and common class of non-binary BCH codes is the family of codes known as RS codes (Gabay et al., 2007).
2.3 Performance of Parallel Concatenated Codes
The most recent breakthrough in coding theory is the discovery of a class of codes called turbo codes that exhibit near Shannon-limit performance with iterative
decoding algorithms (Berrou et al., 1993). The astounding performance of turbo codes resulted in a surge in the research activity on iterative de-coding. For example, Gallager's low density parity check (LDPC) codes discovered with iterative decoding in the 60's by Gallager (1962), has drawn tremendous attention in the past few years.
Although the above mentioned turbo codes have excellent bit error performance, there still exists some problems. First of all, their error performance tails of, or exhibits an error “floor" at high signal-to-noise ratio (SNR). Moreover, the complexity of the required soft-input, soft-output (SISO) decoder is such that a cost- effcient decoder was unavailable for most commercial applications (Wadayama, 2005). For these reasons, RS codes are still widely employed in many practical applications because of its efficient decoder implementation and excellent error correction capabilities (Reed and Solomon, 1960).
McEliece et al., the first describes the close connections between the iterative turbo decoding algorithms with Pearl’s belief propagation algorithm. Turbo principle as an example is a strategy exploiting the iterative process with significantly shorter block lengths. The performance of parallel and serial concatenated convolutional codes are presented by Yuan et al. (2002) based on the derived analytical bounds are compared over independent fading channels on frequency-nonselective Rician fading channels. Soft-output Viterbi algorithm (SOVA) decoding methods iterative decoding methods, with and without channel state information, on fading channels with and without CSI are considered. Yuan et al. (2002)concluded that the serial concatenated codes perform better than parallel concatenated codes on correlated fading channels. Channel encoder is considered parallel and serial concatenated
respectively. Random interleaver is linked between the inner encoder and the outer encoder. Simulation results observed that the parallel code has a better performance at low SNR than the serial one but the serial code outperforms the parallel code at high SNR, as shown from the graphs in Figure 2 .4.
Figure 2.2: Turbo Encoder Implemented by Yuan et al. (2002).
Figure 2.3: Serial Concatenated Encoder Implemented by Yuan et.al (2002).
V1
V0
V2
Interleaver
RSC Encoder 2
RSC Encoder1 C
C’
Inner Code Encoder Interleaver
Outer Code Encoder
Figure 2.4 show the performance comparison for the four-state, rate 1/3 parallel and serial codes on an independent Rayleigh fading channel, the message length N = 1024and 4096. Rahman et.al (1999) presented the performance of serial concatenated convolutional code (SCCC) in frequency selective Rayleigh fading (FSRF) channel.
Figure 2.4: BER Performance Parallel Concatenated Codes over Serial Codes on Rayleigh Fading Channel (Yuan et al., 2002).
The decoding procedure considered a block called SISO (Soft-Input Soft-Output, used within the iterative decoding algorithm. The BER improvement is low compared to higher iteration with the increment in SNR; increase in number of iteration does not improve gain but provides a BER improvement, while the performance of parallel concatenated interleaved codes is investigated by Lal et.al (1999) for high-bit-rate data transmission in a wideband DS-CDMA system. The authors demonstrated that turbo codes introduced lower coding gain when channel correlation is increased.
In order to improve the performance of OFDM based wireless communications several papers are available in literature that deals with different coding schemes to improve the performance of multicarrier wireless communication systems.
A concatenated coding scheme over different channel conditions investigated by Shahana et al. (2008),which used the Redundant Residue Number System (RRNS) code as the outer code and a convolutional code as the inner code. The BER performances is significant improvement for the proposed RRNS-Convolutional Concatenated coding (RCCC) scheme in presence of additive white Gaussian noise and multipath delay spread by exploiting the inherent properties of RRNS. The authors concluded that the proposed coding scheme makes the OFDM system more robust against multipath effects, timing errors, and to reduce the PAPR without significant increase in BER for the RCCC OFDM system.
2.4 RS Codes In the Communication Systems
Digital communications possess the ability to detect and correct errors introduced by the channel. The realm of coding theory is a rich and interesting field. A major pioneer and the father of modern information theory was Claude Shannon. Shannon showed for an Additive White Gaussian Noise (AWGN) channel that the probability of error could be made vanishingly small, provided the data rate is less than or equal to the channel capacity, this proof used randomly generated code words and sub- optimal jointly-typical decoding (Gallager, 1962).
Figure 2.5: Schematic Diagram of Basic Structure of Communication System.
Figure 2.5 shows the block diagram of basic structure of a communication system.
Shanon (1948a) had shown that arbitrarily reliable communication is possible as long as the signal transmission rate does not exceed a certain limit called the channel capacity. This stimulated numerous research efforts on error control coding.
Following the first class of error control codes, namely Hamming codes, powerful algebraic codes such as Golay codes, Bose-Chaudhuri-Hocquenghem (BCH) codes, and RS codes were found. As the coding theory evolved, various important properties of codes were identified and studied, such as minimum distance and weight distribution (Whitaker et al., 1991).
The discovery of CCs, which were originally called recurrent codes, was another important landmark in the history of error control coding. CCs have many important properties such as the existence of efficient encoding and decoding algorithms and the impressive performance over AWGN channels. Another important landmark of error control coding theory was the discovery of concatenated coding schemes.
More important discovery was by Forney (1973), who showed that the weakness of CCs against bursty errors could be compensated by serially concatenating a CC with
a wide range of applications in digital communications and storage. RS is based in finite field arithmetic, an example of RS code for the Asymmetric Digital Subscriber Line (ADSL) application is implemented by (Shih, 2000), encoding and decoding parameters of symbol width (m=8), message length (k=239), block length (n=255), and maximum capability of error correction (t=8) in the generator was investigated.
Shih (2000) demonstrated that RS codes could achieve a largest possible minimum distance for the given block and information length. The major advantage of RS codes is that the code can correct up to t random symbol errors within a block no matter how many bits are in error in each symbol. The disadvantage of this method is however, RS codes send n symbols in every k input symbols; this expands the system bandwidth utilization, and imposes more noise to the system. As a result, the SNR at the input to the demodulator will be reduced to k/n of uncoded system. Figure 2.6 shows the system block diagram of FEC code using RS code in the communication system used by Shih (2000).
Shih had also demonstrated that the ADSL transmitter and receiver each have two associated paths. The main advantage between the two is that the interleaved path contains an interleaving function in the transmitter and de-interleaving function in the receiver, whereas the fast path does not. This is the advantage of this method.
Figure 2.6: FEC Using RS Code in the Communication System (Shih, 2000).
Based on Shih’s work another researcher (Julien, 2007) presented another example to enhance the Wi-OFDM and DSL application systems. The system model as shown in the Figure 2.7, involved a two level coded structure, used an outer RS code ,level I as a coded bit and level II as uncoded bit, the researcher used the same parameters which was used by Shih (2000).
Julien (2007 ) has also considered the same major advantage of RS codes (the code can correct up to t random symbol errors within a block no matter how many bits are in error in each symbol, so we can here demonstrate the same disadvantages of this method as in the system used by Shih (2000). It was concluded that a RS outer code could not be considered as the best option for more improvement the system in a fading environment.
Figure 2.7: FEC Coded OFDM Communication Systems Used by Julien (2007).
Therefore, Julien (2007) has proposed another coding scheme to enhance the Wi- OFDM system in a fading environment with perfect CSI based on a 64-state CC (Wi- Fi and Wimax).
The disadvantage of the last proposed scheme by Julien, was that it still suffered from a high error floor caused uncoded bit. To solve this problem in an AWGN could be mitigated by using outer RS code, instead of a turbo code.
In fact the origin of ECC schemes tracks back to the work of Shannon (1948b) who demonstrated the fundamental principle of error-correction coding schemes. He had shown in this work that even though communication channels were subjected to noise and errors, if some amount of redundancy was encoded into the signal errors could be accounted for and corrected at the receiving end.
This led to the development of various encoding schemes, including RS coding.
Many optimization techniques that were modified to ensure low-energy operations
through the use of several circuit-level energy, were investigated by Bello (1963) and Miller et al. (1981).
For better signal processing performance based on microprocessors, many algorithms had been implemented using DSP microcontrollers to develop various error corrections RS coding schemes. As for ranging RS coding scheme was implemented by Dust (1998) in order to correct errors, the optical drive of CD players was implemented for NASA’s wireless deep-space communications.
A study was reported by Al-Lawati et al., (2007) based on RS of 127 symbol codeword and the number of information (k) of 65 symbols to identify for which perfect interleaving of RS codes. The analytical derivation of simulations were implemented using the Berlekamp-Massey decoding algorithm, the channel model was considered a binary additive Markov noise channel.
Al-Lawati et al., (2007) concluded some disadvantages of using interleaving to render the channel memoryless, also they demonstrated that addition of interleaver introduced delay and caused complexity to the system.
Building on previous result, they also demonstrated that, symbol interleaving could be avoided by RS (127, 65) for the probability of codeword error (PCE) chosen was between 10-5 and 10-1, On another hand, it is not necessary to use bit interleaver, it also advantageous to avoid the delay time and complexity system, but improved performance can also be achieved.
Edwards et al. (1997) has investigated the bandwidth efficiency coded modulation technique based on the concatenated 2FSK/8PSK modulation with RS (127, k) code, where k is the number of information symbol over GF (128). This modulation scheme was combined with RS-127 symbol, with different numbers of k, and each RS codeword consisted of 127 symbols.
Error detection and error correction by redundant codes was useful in order to reduce the necessary SNR as reported by Hagenauer and Erich (1987). The researchers focused on forward error correction (FEC) coding and demonstrated that the errors which were introduced in the channel for any encoding information could be reduced to any desired level without a severe decrease in transmission rate. Also Automatic Repeat Request (ARQ) design required a much more specific system design.
Another FEC decoding scheme (YHAH-Viterbi) was implemented in the same work by Hagenauer and Erich (1987), and including an interleaver of variable size was tested over simulated and stored fading channels.
The advantages of the method implemented by Hagenauer and Erich (1987), a) it is a robust method to transform bursts into statistically independent errors, b) The burst errors are, in principle, easier to decode than random errors with the same error rate.
The disadvantages of this method are : a) The CCs are not directly suitable for the usage on fading channels, because Viterbi as well as sequential decoders are sensitive to bursty errors, b) The interleaving is commonly applied to spread the bursts of error, it destroys the memory of the channel.
