Low-Precision Quantizer Design for Communication Problems:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Abschlussarbeit Buch |
| Sprache: | English |
| Veröffentlicht: |
München
Dr. Hut
2012
|
| Ausgabe: | 1. Aufl. |
| Schriftenreihe: | Informationstechnik
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | IX, 153 S. graph. Darst. 210 mm x 148 mm, 463 g |
| ISBN: | 9783843904391 |
Internformat
MARC
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| 245 | 1 | 0 | |a Low-Precision Quantizer Design for Communication Problems |c Georg Zeitler |
| 250 | |a 1. Aufl. | ||
| 264 | 1 | |a München |b Dr. Hut |c 2012 | |
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Datensatz im Suchindex
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|---|---|
| adam_text | IMAGE 1
V
C O N T E N T S
1. INTRODUCTION 1
2. PRELIMINARIES 5
2.1. RATE-DISTORTION THEORY 5
2.2. THE TRADEOFF BETWEEN MUTUAL INFORMATION AND RATE 9
2.2.1. PROBLEM FORMULATION 9
2.2.2. COMPUTATION OF THE INFORMATION-RATE FUNCTION 12
3. QUANTIZE-AND-FORWARD SCHEMES FOR T H E MULTIPLE-ACCESS RELAY CHANNEL
19
3.1. SYSTEM MODEL 21
3.1.1. SOURCES 21
3.1.2. CHANNEL MODEL 21
3.1.3. RELAY OPERATIONS 22
3.1.4. DESTINATION 24
3.1.5. REFERENCE SCHEMES 27
3.2. QUANTIZER DESIGN 27
3.2.1. ONE-DIMENSIONAL QUANTIZERS 28
3.2.2. TWO-DIMENSIONAL QUANTIZERS 32
3.2.3. EXAMPLES OF QUANTIZERS 34
3.3. SIMULATION RESULTS 36
3.3.1. ADDITIVE WHITE GAUSSIAN NOISE CHANNELS 36
3.3.2. BLOCK FADING CHANNELS 39
HTTP://D-NB.INFO/1022045571
IMAGE 2
VI CONTENTS
3.4. DISCUSSION 42
4. SOURCE CODING RATE ALLOCATION IN ORTHOGONAL COMPRESS-AND-FORWARD
RELAY
NETWORKS 4 3
4.1. SYSTEM MODEL 44
4.1.1. CHANNEL MODEL 44
4.1.2. COOPERATION PROTOCOL AND ACHIEVABLE RATES 45
4.2. OPTIMAL ALLOCATION OF SOURCE CODING RATE FOR GAUSSIAN MODULATION 46
4.3. RATE ALLOCATION FOR ARBITRARY MODULATION ALPHABETS AND DISCRETE
MEMORYLESS
CHANNELS 49
4.3.1. THE INFORMATION-RATE TRADEOFF 50
4.3.2. RATE ALLOCATION FOR M USERS 51
4.3.3. EVALUATION OF THE FUNCTION U 51
4.3.4. CUTTING-PLANE ALGORITHM 54
4.3.5. NUMERICAL EXAMPLE 57
4.4. RELATION TO NOISY NETWORK CODING 58
4.4.1. DESCRIPTION OF NNC AND ACHIEVABLE RATES 59
4.4.2. NNC AND CF 59
4.5. DISCUSSION 63
5. LOW-PRECISION A / D CONVERSION FOR MAXIMUM INFORMATION RATE IN
CHANNELS
WITH MEMORY 65
5.1. SYSTEM MODEL AND ACHIEVABLE RATES 66
5.2. SCALAR QUANTIZATION IN THE LIMIT OF HIGH SNR 68
5.2.1. OPTIMAL QUANTIZATION WITH J = A REGIONS A T INFINITE SNR 70
5.2.2. OPTIMAL 1-BIT/SAMPLE QUANTIZATION IS OFTEN NECESSARY FOR I.I.D.
BPSK 71
5.3. DESIGN OF SCALAR A/D CONVERTERS 72
5.3.1. PROBLEM FORMULATION 72
5.3.2. DESIGN ALGORITHM 73
IMAGE 3
C O N T E N T S VII
5.4. DESIGN OF TWO-DIMENSIONAL A/D CONVERTERS 76
5.5. UPPER BOUND ON THE INFORMATION RATE 77
5.6. SIMULATION RESULTS 78
5.6.1. EXAMPLES OF QUANTIZERS 78
5.6.2. ACHIEVABLE RATES 79
5.6.3. ERROR RATES 80
5.6.4. OPTIMIZATION OF INPUT ALPHABET AND DISTRIBUTION 80
5.7. DISCUSSION 82
6. BAYESIAN P A R A M E T E R E S T I M A T I O N USING SINGLE-BIT D I T
H E R E D QUANTIZATION 8 5
6.1. SYSTEM MODEL 86
6.2. BAYESIAN CRAMER-RAO LOWER BOUNDS 88
6.3. LOWER BOUNDS ON THE MSE USING SINGLE-BIT DITHERED QUANTIZATION 90
6.3.1. THE BCRLB FOR PARAMETER ESTIMATION WITH QUANTIZED OBSERVATIONS 90
6.3.2. TIGHTENING THE BCRLB FOR SHORT OBSERVATIONS 91
6.4. DESIGN OF ESTIMATORS AND DITHER STRATEGIES 92
6.4.1. THE LINEAR MMSE ESTIMATE AS ESTIMATOR AND DITHER SIGNAL 92
6.4.2. THE MMSE ESTIMATE AS ESTIMATOR AND DITHER SIGNAL 93
6.4.3. THE DITHER SIGNAL THAT MINIMIZES THE MSE 94
6.4.4. THE MAXIMUM LIKELIHOOD ESTIMATE AS ESTIMATOR AND DITHER SIGNAL .
. 97
6.4.5. THE MAXIMUM A POSTERIORI ESTIMATE AS ESTIMATOR AND DITHER SIGNAL
. 99
6.5. SIMULATION RESULTS 100
6.6. DISCUSSION 100
7. CONCLUSIONS 105
A . PROOFS FOR C H A P T E R 2 107
B. PROOFS FOR C H A P T E R 3 109
B.L. MESSAGE PASSING RULES 109
IMAGE 4
VIII CONTENTS
B.2. PROOF OF PROPOSITION 3.2 110
C. PROOFS FOR CHAPTER 4 111
C.L. PROOF OF THEOREM 4.3 I L L
C.2. PROOF OF THEOREM 4.4 116
C.3. PROOF OF PROPOSITION 4.6 116
C.4. PROOF OF THEOREM 4.7 117
D . PROOFS FOR CHAPTER 5 119
D.L. PROOF OF THEOREM 5.1 119
D.2. PROOF OF THEOREM 5.2 122
D.3. PROOF OF LEMMAS 5.3 AND 5.4 123
E. PROOFS FOR CHAPTER 6 125
E.L. PROOF OF THEOREM 6.2 125
E.2. PROOF OF THEOREM 6.3 128
E.2.1. CONDITIONS FOR THE APPLICABILITY OF THEOREM 6.2 128
E.2.2. COMPUTATION OF THE SECOND DERIVATIVE OF IN (PZ H[2 N H)PN(H)^ .
. . 129
E.2.3. EVALUATION OF THE BCLRB 131
E.3. PROOF OF THEOREM 6.5 133
E.4. PROOF OF THEOREM 6.6 136
E.5. PROOF OF PROPOSITION 6.7 138
F. MATHEMATICAL NOTATION AND ABBREVIATIONS 141
BIBLIOGRAPHY 145
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| spelling | Zeitler, Georg Christoph Verfasser aut Low-Precision Quantizer Design for Communication Problems Georg Zeitler 1. Aufl. München Dr. Hut 2012 IX, 153 S. graph. Darst. 210 mm x 148 mm, 463 g txt rdacontent n rdamedia nc rdacarrier Informationstechnik Zugl.: München, Techn. Univ., , Diss., 2012 (DE-588)4113937-9 Hochschulschrift gnd-content DNB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=025104708&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Zeitler, Georg Christoph Low-Precision Quantizer Design for Communication Problems |
| subject_GND | (DE-588)4113937-9 |
| title | Low-Precision Quantizer Design for Communication Problems |
| title_auth | Low-Precision Quantizer Design for Communication Problems |
| title_exact_search | Low-Precision Quantizer Design for Communication Problems |
| title_full | Low-Precision Quantizer Design for Communication Problems Georg Zeitler |
| title_fullStr | Low-Precision Quantizer Design for Communication Problems Georg Zeitler |
| title_full_unstemmed | Low-Precision Quantizer Design for Communication Problems Georg Zeitler |
| title_short | Low-Precision Quantizer Design for Communication Problems |
| title_sort | low precision quantizer design for communication problems |
| topic_facet | Hochschulschrift |
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