Compressive sensing for wireless networks:
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| Main Authors: | , , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Cambridge [u.a.]
Cambridge Univ. Press
2013
|
| Edition: | 1. publ. |
| Subjects: | |
| Online Access: | Volltext Inhaltsverzeichnis |
| Item Description: | Includes bibliographical references (pages 268-290) and index |
| Physical Description: | XIV, 293 S. graf. Darst. |
| ISBN: | 9781107018839 |
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MARC
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| 245 | 1 | 0 | |a Compressive sensing for wireless networks |c Zhu Han ; Husheng Li ; Wotao Yin |
| 250 | |a 1. publ. | ||
| 264 | 1 | |a Cambridge [u.a.] |b Cambridge Univ. Press |c 2013 | |
| 300 | |a XIV, 293 S. |b graf. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 500 | |a Includes bibliographical references (pages 268-290) and index | ||
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Record in the Search Index
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| adam_text |
Contents
Preface
page
xiii
Introduction l
1.1
Motivation and objectives
1
1.2
Outline
2
Overview of wireless networks
6
2.1
Wireless channel models
6
6
11
2.2
Categorization of wireless networks
13
13
17
19
22
28
32
2.3
Advanced wireless technology
36
36
39
41
43
45
Part I
Compressive
Sensing Technique
3
Compressive
sensing framework
51
3.1
Background
51
3.2
Traditional sensing versus
compressive
sensing
56
3.3
Sparse representation
57
3.3.1
Extensions of sparse models
59
Wireless channel models
2.1
.1
Radio propagation
2.1
2
Interference channel
Categorization of wireless networks
2.2.
.1
3G cellular networks and beyond
2.2.
2
WiMAX networks
2.2.
,3
WiFi networks
2.2
.4
Wireless personal area networks
2.2
.5
Wireless ad hoc networks
2.2
.6
Wireless sensor networks
Advanced wireless technology
2.3
.1
OFDM technology
2.3
.2
Multiple antenna system
2.3
.3
Cognitive radios
2.3
.4
Scheduling and multiple access
2.3
.5
Wireless positioning and localization
viii Contents
3.4
CS
encoding and decoding
60
3.5
Examples
67
Sparse optimization algorithms
69
4.1
A brief introduction to optimization
70
4.2
Sparse optimization models
73
4.3
Classic solvers
74
4.4
Shrinkage operation
76
4.4.1
Generalizations of shrinkage
78
4.5
Prox-linear algorithms
79
4.5.1
Forward-backward operator splitting
80
4.5.2
Examples
81
4.5.3
Convergence rates
83
4.6
Dual algorithms
83
4.6.1
Dual formulations
84
4.6.2
The augmented Lagrangian method
85
4.6.3
Bregman method
86
4.6.4
Bregman iterations and denoising
88
4.6.5
Linearized Bregman and augmented models
90
4.6.6
Handling complex data and variables
92
4.7
Alternating direction method of multipliers
93
4.7.1
Framework
94
4.7.2
Applications of ADM in sparse optimization
96
4.7.3
Applications in distributed optimization
100
4.7.4
Applications in decentralized optimization
102
4.7.5
Convergence rates
102
4.8
(Block) coordinate minimization and gradient descent
103
4.9
Homotopy algorithms and parametric quadratic programming
105
4.10
Continuation, varying step sizes, and line search
107
4.11
Non-convex approaches for sparse optimization
109
4.12
Greedy algorithms
110
4.12.1
Greedy pursuit algorithms
110
4.12.2
Iterative support detection
112
4.12.3
Hard thresholding
113
4.13
Algorithms for low-rank matrices
114
4.14
How to choose an algorithm
115
CS analog-to-digital converter
118
5.1
Traditional ADC basics
118
5.1.1
Sampling theorem
118
5.1.2
Quantization
120
5.1.3
Practical implementation
121
Contents
¡χ
5.2 Random
demodulator
ADC
125
5.2.1
Signal model
125
5.2.2
Architecture
125
5.3
Modulated wideband converter ADC
127
5.3.1
Architecture
127
5.3.2
Comparison with random demodulator
129
5.4
Xampling
129
5.4.1
Union of subspaces
130
5.4.2
Architecture
130
5.4.3
X-ADC and hardware implementation
131
5.4.4
X-DSP and subspace algorithms
132
5.5
Other architecture
135
5.5.1
Random sampling
135
5.5.2
Random filtering
136
5.5.3
Random delay line
136
5.5.4
Miscellaneous literature
136
5.6
Summary
138
Part II CS-Based Wireless Communication
6
Compressed channel estimation
141
6.1
Introduction and motivation
141
6.2
Multipath channel estimation
143
6.2.1
Channel model and training-based method
143
6.2.2
Compressed channel sensing
143
6.3
OFDM channel estimation
146
6.3.1
System model
147
6.3.2
Compressive
sensing OFDM channel estimator
148
6.3.3
Numerical algorithm
151
6.3.4
Numerical simulations
154
6.4
Underwater acoustic channel estimation
159
6.4.1
Channel model
159
6.4.2
Compressive
sensing algorithms
160
6.5
Random field estimation
162
6.5.1
Random field model
163
6.5.2
Matrix completion algorithm
166
6.5.3
Simulation results
168
6.6
Other channel estimation methods
171
6.6.1
Blind channel estimation
171
6.6.2
Adaptive algorithm
171
6.6.3
Group sparsity method
172
6.7
Summary
172
Contents
7
Ultra-wideband systems
173
7.1
A brief introduction to UWB
173
7.1.1
History and applications
173
7.1.2
Characteristics of UWB
174
7.1.3
Mathematical model of UWB
174
7.2
Compression of UWB
175
7.2.1
Transmitter side compression
175
7.2.2
Receiver side compression
177
7.3
Reconstruction of UWB
180
7.3.1
Block reconstruction
180
7.3.2
Bayesian reconstruction
184
7.3.3
Computational issue
186
7.4
Direct demodulation in UWB communications
189
7.4.1
Transceiver structures
189
7.4.2
Demodulation
190
7.5
Conclusions
192
8
Positioning
193
8.1
Introduction to positioning
193
8.2
Direct application of
compressive
sensing
194
8.2.1
General principle
194
8.2.2
Positioning in WLAN
195
8.2.3
Positioning in cognitive radio
198
8.2.4
Dynamic
compressive
sensing
203
8.3
Indirect application of
compressive
sensing
205
8.3.1
UWB positioning system
205
8.3.2
Space-time
compressive
sensing
207
8.3.3
Joint
compressive
sensing and TDOA
210
8.4
Conclusions
212
9
Multiple access
214
9.1
Introduction
214
9.2
Introduction to multiuser detection
215
9.2.1
System model for CDMA
216
9.2.2
Comparison between multiuser detection and
compressive
sensing
216
9.2.3
Various algorithms of multiuser detection
217
9.2.4
Optimal multiuser detector
217
9.3
Multiple access in cellular systems
221
9.3.1
Uplink
221
9.3.2
Downlink
226
9.4
Multiple access in sensor networks
227
Contents xi
9.4.1 Single
hop
227
9.4.2 Multiple hops 229
9.5
Conclusions
231
10
Cognitive radio networks
232
I O.I Introduction
232
1
0.2
Literature review
234
10.3
Compressive
sensing-based collaborative spectrum sensing
236
10.3.1
System model
236
10.3.2
CSS matrix completion algorithm
237
10.3.3
CSS joint sparsity recovery algorithm
240
10.3.4
Discussion
243
10.3.5
Simulations
244
10.4
Dynamic approach
251
10.4.1
System model
252
10.4.2
Dynamic recovery algorithm
253
10.4.3
Simulations
255
10.5
Joint consideration with localization
259
10.5.1
System model
259
10.5.2
Joint spectrum sensing and localization algorithm
261
10.5.3
Simulations
264
10.6
Summary
267
References
268
Index
291 |
| any_adam_object | 1 |
| author | Han, Zhu 1974- Li, Husheng 1975- Yin, Wotao ca. 20./21. Jh |
| author_GND | (DE-588)1038496136 (DE-588)103849592X (DE-588)103849625X |
| author_facet | Han, Zhu 1974- Li, Husheng 1975- Yin, Wotao ca. 20./21. Jh |
| author_role | aut aut aut |
| author_sort | Han, Zhu 1974- |
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| building | Verbundindex |
| bvnumber | BV041196663 |
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| edition | 1. publ. |
| format | Book |
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| indexdate | 2025-03-09T05:00:40Z |
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| isbn | 9781107018839 |
| language | English |
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| spelling | Han, Zhu 1974- Verfasser (DE-588)1038496136 aut Compressive sensing for wireless networks Zhu Han ; Husheng Li ; Wotao Yin 1. publ. Cambridge [u.a.] Cambridge Univ. Press 2013 XIV, 293 S. graf. Darst. txt rdacontent n rdamedia nc rdacarrier Includes bibliographical references (pages 268-290) and index Funknetz (DE-588)4216130-7 gnd rswk-swf Datenkompression (DE-588)4121121-2 gnd rswk-swf Funknetz (DE-588)4216130-7 s Datenkompression (DE-588)4121121-2 s DE-604 Li, Husheng 1975- Verfasser (DE-588)103849592X aut Yin, Wotao ca. 20./21. Jh. Verfasser (DE-588)103849625X aut DE-601 text/html http://reference-tree.com/book/compressive-sensing-for-wireless-networks?utm_source=gbv&utm_medium=referral&utm_campaign=collaboration Volltext Digitalisierung UB Bamberg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=026171630&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Han, Zhu 1974- Li, Husheng 1975- Yin, Wotao ca. 20./21. Jh Compressive sensing for wireless networks Funknetz (DE-588)4216130-7 gnd Datenkompression (DE-588)4121121-2 gnd |
| subject_GND | (DE-588)4216130-7 (DE-588)4121121-2 |
| title | Compressive sensing for wireless networks |
| title_auth | Compressive sensing for wireless networks |
| title_exact_search | Compressive sensing for wireless networks |
| title_full | Compressive sensing for wireless networks Zhu Han ; Husheng Li ; Wotao Yin |
| title_fullStr | Compressive sensing for wireless networks Zhu Han ; Husheng Li ; Wotao Yin |
| title_full_unstemmed | Compressive sensing for wireless networks Zhu Han ; Husheng Li ; Wotao Yin |
| title_short | Compressive sensing for wireless networks |
| title_sort | compressive sensing for wireless networks |
| topic | Funknetz (DE-588)4216130-7 gnd Datenkompression (DE-588)4121121-2 gnd |
| topic_facet | Funknetz Datenkompression |
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