Iterative source-channel decoding [Elektronische Ressource] : design and optimization for heterogeneous networks / Laurent Schmalen

Informations

• Publié par: rheinisch-westfalischen_technischen_hochschule_-rwth-_aachen
• Publié le: 01 janvier 2011
• Nombre de lectures: 21
• Langue: Deutsch
• Poids de l'ouvrage: 4 Mo

Extrait

Iterative Source-Channel Decoding:
Design and Optimization for Heterogeneous Networks
Von der Fakultät für Elektrotechnik und Informationstechnik
der Rheinisch-Westfälischen Technischen Hochschule Aachen
zur Erlangung des akademischen Grades eines
Doktors der Ingenieurwissenschaften genehmigte Dissertation
vorgelegt von
Diplom-Ingenieur
Laurent Schmalen
aus Luxemburg, Luxemburg
Berichter: Universitätsprofessor Dr.-Ing. Peter Vary
Univ D Gerd Ascheid
Tag der mündlichen Prüfung: 29. April 2011
Diese Dissertation ist auf den Internetseiten der Hochschulbibliothek online verfügbar.AACHENER BEITRÄGE ZU DIGITALEN NACHRICHTENSYSTEMEN
Herausgeber:
Prof. Dr.-Ing. Peter Vary
Institut für Nachrichtengeräte und Datenverarbeitung
Rheinisch-Westfälische Technische Hochschule Aachen
Muffeter Weg 3a
52074 Aachen
Tel.: [phone]
Fax.: [phone]
Bibliografische Information der Deutschen Bibliothek
Die Deutsche Bibliothek verzeichnet diese Publikation in der
Deutschen Nationalbibliografie; detaillierte bibliografische
Daten sind im Internet über http://dnb.ddb.de abrufbar
1. Auflage Aachen:
Wissenschaftsverlag Mainz in Aachen
(Aachener Beiträge zu digitalen Nachrichtensystemen, Band 29)
ISSN 1437-6768
ISBN 3-86130-268-3
© 2011 Laurent Schmalen
Wissenschaftsverlag Mainz
Süsterfeldstr. 83, 52072 Aachen
Tel.: 02 41 / 2 39 48 oder 02 41 / 87 34 34
Fax: 02 41 / 87 55 77
www.Verlag-Mainz.de
Herstellung: Druckerei Mainz GmbH,
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Tel.: 02 41 / 87 34 34; Fax: 02 41 / 87 55 77
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Gedruckt auf chlorfrei gebleichtem Papier
"D 82 (Diss. RWTH Aachen University, 2011)"Acknowledgments
ThisthesiswaswrittenduringmytimeasresearchassistantattheInstitute of Com-
munication Systems and Data Processing (IND) at the Rheinisch-Westfälische Tech-
nische Hochschule Aachen (RWTH Aachen University). I would like to take the
opportunity to thank the people who contributed to the success of this work.
At first, I am deeply grateful to my supervisor Prof. Dr.-Ing. Peter Vary for his con-
tinuous support of my work by numerous ideas and suggestions and for encouraging
me in my scientific interests. I am also indebted to Prof. Dr.-Ing. Gerd Ascheid for
being the co-supervisor of this thesis and showing much interest in my work.
Furthermore, I want to thank all my colleagues for providing an enjoyable at-
mosphere and a pleasant working environment. I am particularly thankful to
Dr.-Ing. Marc Adrat and Dr.-Ing. Thorsten Clevorn. The discussions with them
have always been an indispensable source of inspiration. I also owe special
thanks to Dr.-Ing. Christiane Antweiler, Dipl.-Ing. Moritz Beermann, Dipl.-Ing. To-
bias Breddermann, Dipl.-Ing. Benedikt Eschbach, Dipl.-Ing. Matthias Pawig, and
Dipl.-Ing. Matthias Rüngeler. Their proof-reading of parts of the manuscript resulted
in many valuable improvements.
I would like to express my appreciation to the students who made significant contri-
butions to my work. In particular, I would like to mention Dipl.-Ing. Yang Cui, Dipl.-
Ing. Ulrich Engel, M. Sc. Enrique Monzó, Dipl.-Ing. Jan Reimes, Dipl.-Ing. Thomas
Schlien, Dipl.-Ing. Matthias Tschauner, and Martin Volmer.
I would also like to thank the European Union for financing most of the work of this
thesis and for giving me the opportunity to work in an international environment
within the FlexCode project. I also wish to express my appreciation to Prof. W. Bas-
tiaan Kleijn and his team at KTH Stockholm for many fruitful discussions, especially
during my stay in their lab.
Finally, I want to thank my parents Aloyse and Mariette Schmalen for their continuous
support over the years. I would also like to thank Joffrey, Julien, Luken, Michel,
Philippe, and Yann for some unforgettable moments during my thesis. Dear Angela,
thank you for your love, encouragement, patience, and understanding.
Stuttgart, May 2011 Laurent SchmalenAbstract
The source-channel separation theorem postulated by Shannon has influenced the
design of communication systems for multimedia content over the last decades: Source
encoding and channel encoding are performed as two separate steps. However, the
conditions of the separation theorem are almost never fulfilled in practical systems;
a joint consideration of source and channel coding can thus be of special interest.
Such a joint consideration with iterative decoding based on the Turbo principle has
been found to be especially advantageous with regard to the realization of efficient
multimedia communication systems.
In the first part of this thesis, the concept of Iterative Source-Channel Decoding
(ISCD) is fundamentally extended and optimized, especially in view of a possible
practical implementation. New design guidelines and optimization criteria lead to a
flexible and versatile system design. Special care is taken to optimize the components
such that a residual error rate, which shall be as low as possible, results. Besides
an extended, iterative receiver architecture leading to an improved exploitation of
the correlation between consecutive frames, a simple yet effective stopping criterion
is presented. This stopping criterion leads to an ISCD system with incremental
redundancy transmission. It is additionally shown how a complexity-reduced ISCD
receiver can be designed by employing a novel way of signal quantization.
While the first part of this thesis treats the source encoding as given, it is con-
sequently incorporated into the system design in the second part. As a novelty, an
efficient method for the compression of parameter sources is introduced. This method
shows the advantage of an easy adaptivity to varying transmission conditions. It is
additionally shown how the ISCD concept can be applied for decoding multiple de-
scriptions in order to improve the signal reconstruction quality in the presence of bit
errors and packet losses. Besides optimized system designs, an innovative concept for
the robust packet-based transmission of correlated source signals is presented.
All variants and proposals are thoroughly analyzed using theoretical methods, by
convergence analysis, or with computer simulations. The contribution of this thesis
is the improvement of the error robustness and the spectral efficiency of future digital
multimedia communication systems.Contents
Notations, Symbols & Abbreviations vii
1 Introduction 1
2 Turbo-Like Codes & Transmission Systems 7
2.1 Linear Block and Convolutional Channel Codes ............. 8
2.2 Turbo and Turbo-Like Channel Codes . . . ............... 10
2.2.1 TurboCodes............................ 10
2.2.2 Turbo-Like Channel Codes .................... 12
2.2.3 Turbo-Like Receivers........................ 16
2.3 ConvergenceAnalysisUsingEXITCharts................ 16
2.4 Iterative Source-Channel Decoding (ISCD) ............... 21
2.4.1 Baseband Block Diagram ..................... 23
2.4.2 ISCDforVariable-LengthCodes................. 25
2.4.3 ISCDforFixed-LengthCodes................... 25
3 Advances in Iterative Source-Channel Decoding 27
3.1 Iterative Source-Channel Decoding .................... 27
3.1.1 Source Model . . . ......................... 28
3.1.2 TransmiteroftheISCDScheme................. 29
3.1.3 Receiver of the ISCD Scheme ................... 32
3.1.4 SimulationExamples........................ 35iv Contents
3.1.5 Source Coding Related Rates ................... 43
3.1.6 EXITChartAnalysisofISCD .................. 46
3.2 ImprovedInter-FrameDecoding...................... 51
3.3 Irregular Redundant Bit Mappings .................... 54
3.3.1 SimulationExample........................ 56
3.3.2 UnequalErorProtectiononParameterLevel.......... 60
3.4 ErorFloorReduction........................... 62
3.4.1 Distance Optimized Bit Mapping ................. 62
3.4.2 Multi-Dimensional Bit Mappings 67
3.5 Stopping Criteria .............................. 72
3.6 HybridARQTechniques.......................... 75
3.7 Conclusions................................. 80
4 Implementation and Complexity Reduction 83
4.1 Conditional Quantization . . . ...................... 83
4.1.1 Soft Decision Source Decoder Implementation.......... 85
4.1.2 Performance Evaluation of Conditional Quantization . . . . . . 86
4.1.3 ImprovementoftheWaterfalBehavior ............. 89
4.1.4 SimulationExample........................ 90
4.2 Reduced Search SDSD (M-Soft Decision Source Decoding (SDSD)) . . 91
4.3 Combination of Conditional Quantization and M-SDSD........ 94
4.4 ComparisonofComplexityReductionApproaches ........... 96
4.5 FurtherComplexityReductionApproaches ............... 9
4.6 Conclusions.................................100
5 Near-Lossless Source Coding Based on ISCD 101
5.1 CompresionUsingIregularComponentCodes.............102
5.1.1 Variant 1: Irregular Redundant Bit Mappings..........102
5.1.2 Variant2:IregularInnerCodes.................105
5.1.3 Variant3:InnerandOuterIregularCodes...........107
5.2 SimulationExamples............................109
5.3 Conclusions.................................18Contents v
6 Iterative Source-Channel Decoding of Multiple Descriptions 121
6.1 MultipleDescriptionCoding......................