Energy and spectrum efficient wireless network design:
"Covering the fundamental principles and state-of-the-art cross-layer techniques, this practical guide provides the tools needed to design MIMO- and OFDM-based wireless networks that are both energy- and spectrum-efficient. Technologies are introduced in parallel for both centralized and distri...
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Cambridge
Cambridge Univ. Press
2015
|
| Ausgabe: | 1. publ. |
| Schlagworte: | |
| Online-Zugang: | Klappentext Inhaltsverzeichnis |
| Zusammenfassung: | "Covering the fundamental principles and state-of-the-art cross-layer techniques, this practical guide provides the tools needed to design MIMO- and OFDM-based wireless networks that are both energy- and spectrum-efficient. Technologies are introduced in parallel for both centralized and distributed wireless networks to give you a clear understanding of the similarities and differences between their energy- and spectrum-efficient designs, which is essential for achieving the highest network energy saving without losing performance. Cutting-edge green cellular network design technologies, enabling you to master resource management for next-generation wireless networks based on MIMO and OFDM, and detailed real-world implementation examples are provided to guide your engineering design in both theory and practice. Whether you are a graduate student, a researcher or a practitioner in industry, this is an invaluable guide"-- |
| Beschreibung: | XVIII, 368 S. Ill., graph. Darst. |
| ISBN: | 9781107039889 |
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Datensatz im Suchindex
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| adam_text | ENERGY AND SPECTRUM EFFICIENT
WIRELESS NETWORK DESIGN
Covering the fundamental principles and state-of-the-art cross-layer techniques, this
practical guide provides the tools needed to design MIMO- and OFDM-based wireless
networks that are both energy- and spectrum-efficient. Technologies are introduced
in parallel for both centralized and distributed wireless networks to give you a clear
understanding of the similarities and differences between their energy- and spectrum-
efficient designs, which is essential for achieving the highest network energy saving
without losing performance. Cutting-edge green cellular network design technologies,
enabling you to master resource management for next-generation wireless networks
based on MIMO and OFDM, and detailed real-world implementation examples are provided
to guide your engineering design in both theory and practice. Whether you are a graduate
student, a researcher, or a practitioner in industry, this is an invaluable guide.
Guowang Miao is an Assistant Professor in the Department of Communications Systems
at KTH Royal Institute of Technology, Sweden. After receiving his Ph.D. in electrical and
computer engineering from Georgia Institute of Technology, USA, in 2009, he spent two
years working in industry as a Senior Standard Engineer at Samsung Telecom America. His
current research interests are in the design and optimization of wireless communications
and networking.
Guocong Song is currently the Principal Research Engineer at ShareThis, Palo Alto,
California. He has been working in wireless communications and networks for a decade,
since receiving his Ph.D. in electrical and computer engineering from Georgia Institute
of Technology. He received the 2010 IEEE Stephen 0. Rice Prize for the best paper in the
field of communications theory, and he is recently active in the area of data science and
machine learning.
Contents
Preface page xv
Acronyms xvii
Introduction 1
1.1 Motivation 1
1.2 Wireless networks 2
1.2.1 Overview 2
1.2.2 Traditional layered architecture 4
1.2.3 Necessity of cross-layer optimization 6
1.3 Book outline 8
Basic concepts 1 1
Wireless channel properties 15
2.1 Path loss 15
2.2 Shadowing 16
2.3 Small-scale lading 17
2.3.1 Flat-fading channels 18
2.3.2 Frequency-selective fading channels 20
2.4 Channel estimation 20
2.4.1 Flat slow-fading channels 21
2.4.2 Frequency-selective slow-fading channels 22
2.4.3 Fast-fading channels 23
2.4.4 Conclusion 23
2.5 Other challenges 23
Spectral and energy efficiency of wireless networks 24
3.1 Spectral efficiency 24
3.2 Energy efficiency 25
3.3 Link metrics versus network metrics 26
viii
Contents
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3.3.1 Link spectral efficiency 26
3.3.2 Network spectral efficiency 27
3.3.3 Link energy efficiency 29
3.3.4 Network energy efficiency 29
4 Centralized resource management in wireless networks 31
4.1 Overview 31
4.2 Wireless scheduling challenges 32
4.3 Centralized scheduling algorithms 34
4.3.1 Round-robin scheduling 35
4.3.2 Max throughput scheduling 36
4.3.3 Proportional fair scheduling 37
4.3.4 Max-min scheduling 38
4.3.5 Max utility scheduling 39
5 Distributed resource management in wireless networks 43
5.1 Overview 43
5.2 Aloha 45
5.2.1 Pure Aloha 45
5.2.2 Slotted Aloha 46
5.3 Carrier sense multiple access (CSMA) 46
5.3.1 Non-persistent CSMA 47
5.3.2 1-persistent CSMA 47
5.3.3 p-persistent CSMA 47
5.3.4 Effect of detection delay 47
5.4 CSMA with collision detection 48
5.5 Carrier sense multiple access with collision avoidance (CSMA/CA) 49
5.5.1 Hidden and exposed terminal problems 49
5.5.2 CSMA/CA protocol 50
Part II Centralized cross-layer optimization 53
6 Overview 55
6.1 System model and problem description 56
6.1.1 Channel characteristics in OFDM 56
6.1.2 Rate adaptation in OFDM 58
6.1.3 Dynamic subcarrier assignment and adaptive power allocation 58
6.1.4 Queue structure 5 9
6.1.5 Problem description 59
6.2 Approach 59
Contents ix
7 Utility-based optimization framework for OFDMA 61
7.1 Rate-based utility functions 61
7.2 Theoretical framework 62
7.2.1 Problem formulation 62
7.2.2 Dynamic suhcarrier assignment 63
7.2.3 Adaptive power allocation 66
7.2.4 Properties of cross-layer optimization 69
8 Algorithm development for utility-based optimization 72
8.1 Dynamic subcarrier assignment (DSA) algorithms 72
8.1.1 Optimality conditions 73
8.1.2 Sorting-search algorithm of subcarrier assignment 75
8.2 Adaptive power allocation (APA) algorithms 77
8.2.1 APA for fixed suhcarrier assignment 77
8.2.2 Sequential-linear-approximation water-filling algorithm for
continuous rate adaptation 78
8.2.3 Greedy power allocation algorithm based on maximizing total
utility for discrete rate adaptation 78
8.3 Joint dynamic suhcarrier assignment and adaptive power allocation 80
8.4 Algorithm modification for non-concave utility functions 81
8.5 Maximum utility with respect to average data rates 81
8.6 Efficiency and fairness 84
8.6.1 Fairness of “extreme OFDM” using utility functions with respect
to instantaneous data rates 85
8.6.2 Fairness of “practical OFDM” using utility functions with respect
to average data rates 85
8.7 Simulation results 87
8.8 Summary 93
9 Joint channel- and queue-aware multi-carrier scheduling using delay-based
utility functions 94
9.1 Introduction 94
9.2 Extending scheduling rules in single-carrier networks into
OFDMA networks 95
9.2.1 Max-sum-capacity (MSC) rule 95
9.2.2 Proportional fair (PF) scheduling 96
9.2.3 Modified largest weighted delay first (M-LWDF) rule 96
9.2.4 Exponential (EXP) rule 96
9.3 Max-delay-utility (MDU) scheduling 97
9.3.1 Utility functions 97
9.3.2 Optimization objective 97
9.3.3 Problem formulation in OFDMA 99
Contents
93.4 Algorithms 100
9.4 Stability 100
9.4.1 Background and definition of stability 100
9.4.2 Capacity region 101
9.4.3 Maximum stability region 102
9.5 Proof of Theorem 9.4 106
9.6 Further improvement through delay transmit diversity and adaptive
power allocation 110
9.6.1 Joint dynamic subcarrier assignment and adaptive power allocation 110
9.6.2 Delay transmit diversity 111
9.7 Simulation results and performance comparison 112
9.7.1 Performance comparison 112
9.7.2 Improvement in delay transmit diversity and adaptive power
allocation 116
9.8 Summary 116
10 Utility-based generalized QoS scheduling for heterogeneous traffic 117
10.1 Introduction 117
10.2 MDU scheduling for heterogeneous traffic 118
10.2.1 Mechanisms of MDU scheduling for diverse QoS requirements 118
10.2.2 Marginal utility functions for MDU scheduling 119
10.3 Simulation 120
10.3.1 Simulation conditions 120
10.3.2 Simulation results 121
10.4 Summary 125
11 Asymptotic performance analysis for channel-aware scheduling 126
11.1 Extreme value theory 126
11.2 Asymptotic throughput analysis of single-carrier networks 129
11.2.1 System model 129
11.2.2 Throughput analysis for Rayleigh fading 130
11.2.3 Throughput analysis for general channel distributions 133
11.2.4 Throughput analysis for normalized-SNR-based scheduling 136
11.2.5 Numerical results 138
11.3 Asymptotic delay analysis of single-carrier networks 139
11.3.1 Asymptotic distribution of service time 140
11.3.2 Average waiting time 141
11.4 Asymptotic performance analysis of multi-carrier networks 142
11.4.1 Asymptotic throughput analysis 142
11.4.2 Asymptotic delay analysis 143
11.4.3 Delay performance comparison 144
11.5 Summary 146
xi
147
149
149
150
151
154
154
157
159
160
164
164
166
167
168
169
170
173
173
175
178
178
180
182
183
186
190
191
192
195
198
203
204
206
208
Contents
Distributed cross-layer optimization
Overview
12.1 Design objective
12.2 Distributed multi-user diversity
12.3 Approaches
Opportunistic random access: single-cell cellular networks
13.1 Channel-aware Aloha
13.1.1 Protocol design and parameter optimization
13.1.2 Performance analysis
13.2 Opportunistic splitting algorithms
Opportunistic random access: any network topology
14.1 Network model
14.2 Optimal design rules
14.2.1 MAC layer analysis
14.2.2 Physical layer analysis
14.2.3 Criterion for cross-layer design
14.3 Low-complexity MAC
14.4 Optimal PHY operation
14.4.1 Physical layer optimization with channel inversion
14.4.2 Physical layer optimization with adaptive modulation and power
allocation
14.5 System performance
14.5.1 Network performance improvement
14.5.2 Suboptimality gap
Optimal channel-aware distributed MAC
15.1 System description
15.2 Channel-aware medium access control
15.3 Optimization
15.3.1 CRS 1
15.3.2 CRS C k 1
15.4 Robustness analysis
15.5 Simulation results
Opportunistic random access with intelligent interference avoidance
16.1 Intelligent interferer recognition
16.2 Co-channel interference avoidance MAC
16.3 Parameter optimization
xii Contents
16.3.1 Trigger selection 208
16.3.2 An alternate trigger mechanism using location knowledge 210
16.4 Network performance 211
16.4.1 Relationship of trigger and SNR 212
16.4.2 Performance improvement 213
17 Distributed power control 217
17.1 Systemmodel 217
17.2 Power control for real-time traffic 218
17.2.1 Distributed power control 220
17.3 Power control for elastic traffic 221
17.3.1 Existence of equilibrium 224
17.3.2 Uniqueness of equilibrium in single-channel systems 225
17.3.3 Uniqueness of equilibrium in multi-channel systems 228
17.3.4 Distributed power control with pricing 231
Part IV Cross-layer optimization for energy-efficient networks 235
18 Overview 237
18.1 Lighting analogy 238
18.2 Methodology 240
19 Energy-efficient transmission 244
19.1 Energy efficiency capacity 244
19.2 Ideal transmission 245
19.3 Energy-efficient transmission in practice 246
19.4 Energy-efficient link adaptation in frequency-selective channels 250
19.4.1 Modeling of energy-efficient link adaptation 252
19.4.2 Design principles 253
19.4.3 Constrained energy-efficient link adaptation 256
19.4.4 Energy-efficient downlink OFDMA transmission 257
19.4.5 Iterative algorithm design 258
19.4.6 Energy efficiency gain 262
19.5 Low-complexity energy-efficient link adaptation 263
19.6 Energy-efficient MIMO and MU-MIMO link adaptation 266
19.6.1 Energy-efficient MU-MIMO modeling 267
19.6.2 Principles of energy-efficient MU-MIMO power allocation 270
19.6.3 Energy-efficient MU-MIMO with improved circuit management 271
19.6.4 Energy efficiency gain 277
20 Centralized energy-efficient wireless resource management 282
20.1 Overview 282
Contents xiii
20.1.1 Circuit component management 282
20.1.2 Time-domain resource management 283
20.1.3 Frequency-domain resource management 284
20.1.4 Spatial-domain resource management 284
20.2 Energy-efficient OFDMA in flat-fading channels 285
20.2.1 Resource allocation without fairness 287
20.2.2 Resource allocation with fairness 288
20.2.3 Performance comparisons 289
20.3 Energy-efficient scheduling in frequency-selective channels 291
20.3.1 Time-averaged network energy efficiency 292
20.3.2 Energy-efficient scheduler 294
20.3.3 Network performance 297
21 Distributed energy-efficient wireless resource management 301
21.1 Distributed energy-efficient MAC design 301
21.1.1 General rules of distributed MAC design 302
21.1.2 Impact of traffic load on energy consumption 304
21.2 Energy-efficient communications in special regimes 308
21.2.1 Circuit power dominated regime 309
21.2.2 Transmit power dominated regime 309
21.23 Noise dominated regime 310
21.2.4 Interference dominated regime 310
21.3 Distributed energy-efficient power control in frequency-selective channels 312
21.3.1 Non-cooperative energy-efficient power optimization game 313
21.3.2 Existence of equilibrium 314
21.3.3 Uniqueness of equilibrium in flat-fading channels 315
21.3.4 Uniqueness of equilibrium in frequency-selective channels 316
21.3.5 Conservative nature of power control 317
21.3.6 Spectral efficiency and energy efficiency improvement 318
22 Energy-efficient cellular network design 321
22.1 Fundamental tradeoffs in network resource utilization 321
22.1.1 Spectral and energy efficiency in single-user systems 322
22.1.2 Spectral and energy efficiency in multi-user systems with
orthogonal selective channels 323
22.1.3 Spectral and energy efficiency in multi-user systems with
interference channels 325
22.2 Energy-efficient homogeneous network deployment 327
22.3 Energy-efficient heterogeneous network deployment 330
22.4 Energy-efficient cellular network operation 332
22.4.1 Energy-efficient cell breathing 332
XIV
Contents
22.4.2 Energy-efficient BS sleeping 332
22.4.3 Cell size adaptation techniques 333
22.4.4 Other energy-efficient designs 334
23 Implementation in practice 335
Appendix A Proofs of Theorems and Lemmas 338
References 355
Index 365
|
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| discipline | Elektrotechnik / Elektronik / Nachrichtentechnik |
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| indexdate | 2024-07-10T01:18:35Z |
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| isbn | 9781107039889 |
| language | English |
| lccn | 2014020418 |
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| publisher | Cambridge Univ. Press |
| record_format | marc |
| spelling | Miao, Guowang Verfasser aut Energy and spectrum efficient wireless network design Guowang Miao ; Guocong Song 1. publ. Cambridge Cambridge Univ. Press 2015 XVIII, 368 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier "Covering the fundamental principles and state-of-the-art cross-layer techniques, this practical guide provides the tools needed to design MIMO- and OFDM-based wireless networks that are both energy- and spectrum-efficient. Technologies are introduced in parallel for both centralized and distributed wireless networks to give you a clear understanding of the similarities and differences between their energy- and spectrum-efficient designs, which is essential for achieving the highest network energy saving without losing performance. Cutting-edge green cellular network design technologies, enabling you to master resource management for next-generation wireless networks based on MIMO and OFDM, and detailed real-world implementation examples are provided to guide your engineering design in both theory and practice. Whether you are a graduate student, a researcher or a practitioner in industry, this is an invaluable guide"-- Energieeffizienz (DE-588)7660153-5 gnd rswk-swf Funknetz (DE-588)4216130-7 gnd rswk-swf Drahtloses lokales Netz (DE-588)4633975-9 gnd rswk-swf Drahtloses lokales Netz (DE-588)4633975-9 s DE-604 Funknetz (DE-588)4216130-7 s Energieeffizienz (DE-588)7660153-5 s Song, Guocong Verfasser aut Digitalisierung UB Bayreuth - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027766343&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Klappentext Digitalisierung UB Bayreuth - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027766343&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Miao, Guowang Song, Guocong Energy and spectrum efficient wireless network design Energieeffizienz (DE-588)7660153-5 gnd Funknetz (DE-588)4216130-7 gnd Drahtloses lokales Netz (DE-588)4633975-9 gnd |
| subject_GND | (DE-588)7660153-5 (DE-588)4216130-7 (DE-588)4633975-9 |
| title | Energy and spectrum efficient wireless network design |
| title_auth | Energy and spectrum efficient wireless network design |
| title_exact_search | Energy and spectrum efficient wireless network design |
| title_full | Energy and spectrum efficient wireless network design Guowang Miao ; Guocong Song |
| title_fullStr | Energy and spectrum efficient wireless network design Guowang Miao ; Guocong Song |
| title_full_unstemmed | Energy and spectrum efficient wireless network design Guowang Miao ; Guocong Song |
| title_short | Energy and spectrum efficient wireless network design |
| title_sort | energy and spectrum efficient wireless network design |
| topic | Energieeffizienz (DE-588)7660153-5 gnd Funknetz (DE-588)4216130-7 gnd Drahtloses lokales Netz (DE-588)4633975-9 gnd |
| topic_facet | Energieeffizienz Funknetz Drahtloses lokales Netz |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027766343&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027766343&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT miaoguowang energyandspectrumefficientwirelessnetworkdesign AT songguocong energyandspectrumefficientwirelessnetworkdesign |