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E-raamat: Green Heterogeneous Wireless Networks

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  • Formaat: EPUB+DRM
  • Sari: IEEE Press
  • Ilmumisaeg: 23-Aug-2016
  • Kirjastus: Wiley-IEEE Press
  • Keel: eng
  • ISBN-13: 9781119088035
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Green Heterogeneous Wireless NetworksSuurem pilt
  • Formaat: EPUB+DRM
  • Sari: IEEE Press
  • Ilmumisaeg: 23-Aug-2016
  • Kirjastus: Wiley-IEEE Press
  • Keel: eng
  • ISBN-13: 9781119088035
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This book focuses on the emerging research topic "green (energy efficient) wireless networks" which has drawn huge attention recently from both academia and industry. This topic is highly motivated due to important environmental, financial, and quality-of-experience (QoE) considerations. Specifically, the high energy consumption of the wireless networks manifests in approximately 2% of all CO2 emissions worldwide. This book presents the authors’ visions and solutions for deployment of energy efficient (green) heterogeneous wireless communication networks. The book consists of three major parts. The first part provides an introduction to the "green networks" concept, the second part targets the green multi-homing resource allocation problem, and the third chapter presents a novel deployment of device-to-device (D2D) communications and its successful integration in Heterogeneous Networks (HetNets).

The book is novel in that it specifically targets green networking in a heterogeneous wireless medium, which represents the current and future wireless communication medium faced by the existing and next generation communication networks. The book focuses on multi-homing resource allocation, exploiting network cooperation, and integrating different and new network technologies (radio frequency and VLC), expanding the network coverage and integrating new device centric communication paradigms such as D2D Communications. Whilst the book discusses a significant research topic supported with advanced mathematical analysis, the resulting algorithms and solutions are explained and summarized in a way that is easy to follow and grasp. This book is suitable for networking and telecommunications engineers, researchers in industry and academia, as well as students and instructors.

Preface xi
Acknowledgements xiii
Dedication xv
Part I INTRODUCTION TO GREEN NETWORKS
1 Green Network Fundamentals
3(26)
1.1 Introduction: Need for Green Networks
3(2)
1.2 Traffic Models
5(4)
1.2.1 Traffic Spatial Fluctuation Modelling
6(2)
1.2.2 Traffic Temporal Fluctuation Modelling
8(1)
1.3 Energy Efficiency and Consumption Models in Wireless Networks
9(14)
1.3.1 Throughput Models
9(1)
1.3.2 Power Consumption Models
10(9)
1.3.3 Energy Efficiency and Consumption Models
19(4)
1.4 Performance Trade-Offs
23(5)
1.4.1 Network-side Trade-Offs
24(2)
1.4.2 Mobile User Trade-Offs
26(2)
1.5 Summary
28(1)
2 Green Network Solutions
29(26)
2.1 Green Solutions and Analytical Models at Low and/or Bursty Call Traffic Loads
29(9)
2.1.1 Dynamic Planning
29(5)
2.1.2 MT Radio Interface Sleep Scheduling
34(3)
2.1.3 Discussion
37(1)
2.2 Green Solutions and Analytical Models at High and/or Continuous Call Traffic Loads
38(10)
2.2.7 Scheduling for Single-Network Access
38(3)
2.2.2 Scheduling for Multi-Homing Access
41(1)
2.2.3 Scheduling with Small-Cells
41(1)
2.2.4 Relaying and Device-to-Device Communications
42(3)
2.2.5 Scheduling with Multiple Energy Sources
45(2)
2.2.6 Discussion
47(1)
2.3 Green Projects and Standards
48(1)
2.4 Road Ahead
49(3)
2.5 Summary
52(3)
Part II MULTI-HOMING RESOURCE ALLOCATION
3 Green Multi-homing Approach
55(15)
3.1 Heterogeneous Wireless Medium
55(3)
3.1.1 Wireless Networks
56(1)
3.1.2 Mobile Terminals
57(1)
3.1.3 Radio Resources and Propagation Attenuation
57(1)
3.2 Green Multi-homing Resource Allocation
58(2)
3.3 Challenging Issues
60(9)
3.3.1 Single-User versus Multiuser System
60(1)
3.3.2 Single-Operator versus Multioperator System
60(1)
3.3.3 Fairness
61(1)
3.3.4 Centralized versus Decentralized implementation
61(1)
3.3.5 In-device Coexistence Interference
62(4)
3.3.6 Computational Complexity
66(1)
3.3.7 Number of MT Radio Interfaces versus Number of Available Networks
67(2)
3.4 Summary
69(1)
4 Multi-homing for a Green Downlink
70(24)
4.1 Introduction
70(2)
4.2 Win-Win Cooperative Green Resource Allocation
72(14)
4.2.1 Non-cooperative Single-Network Solution
73(2)
4.2.2 Win-Win Cooperative Solution
75(6)
4.2.3 Benchmark: Sum Minimization Solution
81(1)
4.2.4 Performance Evaluation
81(5)
4.3 IDC Interference-Aware Green Resource Allocation
86(7)
4.3.1 IDC Interference-Aware Resource Allocation Design
87(3)
4.3.2 Performance Evaluation
90(3)
4.4 Summary
93(1)
5 Multi-homing for a Green Uplink
94(25)
5.1 Introduction
94(1)
5.2 Green Multi-homing Uplink Resource Allocation for Data Calls
95(12)
5.2.1 Optimal Green Uplink Radio Resource Allocation with QoS Guarantee
97(5)
5.2.2 Suboptimal Uplink Energy-Efficient Radio Resource Allocation
102(2)
5.2.3 Performance Evaluation
104(3)
5.3 Green Multi-homing Uplink Resource Allocation for Video Calls
107(10)
5.3.1 Energy Management Sub-system Design
109(5)
5.3.2 Performance Evaluation
114(3)
5.4 Summary
117(2)
6 Radio Frequency and Visible Light Communication Internetworking
119(22)
6.1 Introduction
119(1)
6.2 VLC Fundamentals
120(8)
6.2.7 VLC Transceivers
120(2)
6.2.2 VLC Channel
122(2)
6.2.3 Interference Issues in VLC
124(2)
6.2.4 VLC--RF Internetworking
126(2)
6.3 Green RF--VLC Internetworking
128(10)
6.3.1 Energy Efficiency Maximization
129(4)
6.3.2 Performance Evaluation
133(4)
6.3.3 Green VLC--RF Internetworking Challenging Issues
137(1)
6.4 Summary
138(3)
Part III NETWORK MANAGEMENT SOLUTIONS
7 Dynamic Planning in Green Networks
141(25)
7.1 Introduction
141(1)
7.2 Dynamic Planning with Dense Small-Cell Deployment
142(6)
7.2.1 Energy-Efficient and QoS-Aware Cell Zooming
144(1)
7.2.2 Performance Evaluation
145(3)
7.3 Dynamic Planning with Cooperative Networking
148(6)
7.3.1 Optimal Resource On-Off Switching Framework
150(2)
7.3.2 Performance Evaluation
152(2)
7.4 Balanced Dynamic Planning Approach
154(10)
7.4.1 Two-Timescale Approach
157(5)
7.4.2 Performance Evaluation
162(2)
7.5 Summary
164(2)
8 Greening the Cell Edges
166(25)
8.1 Introduction
166(3)
8.1.1 Why Cell-on-Edge Deployment?
167(1)
8.1.2 Background Work
168(1)
8.2 Two-Tier Small-Cell-on-Edge Deployment
169(2)
8.2.1 Network Layout
169(1)
8.2.2 Bandwidth Partition and Channel Allocation
170(1)
8.2.3 Mobile User Distribution
171(1)
8.3 Energy-Aware Transmission Design
171(2)
8.3.1 Path-Loss Model for Strong LOS Conditions
171
8.3.2 Composite Fading Channel for Strong LOS Conditions
111(62)
8.4 Area Spectral Efficiency of HetNets
173(3)
8.5 Analytical Bounds on ASE of HetNets
176(5)
8.5.1 Mean Achievable Capacity Based on MGF Approach
176(1)
8.5.2 Assumptions to Derive Upper and Lower Bounds
177(2)
8.5.3 Analytical Bounds on the Capacity of Macro-cell Network
179(1)
8.5.4 Analytical Bounds on the Capacity of Small-Cell Networks
180(1)
8.6 Analytical Bounds on ASE over Generalized-K Fading Channel
181(2)
8.7 Energy Analysis of HetNets
183(2)
8.7.1 Energy Consumption of Two-Tier HetNets
184(1)
8.7.2 Energy Savings of Two-Tier HetNets
184(1)
8.8 Ecology and Economics of HetNets
185(3)
8.8.1 CO2e Emissions and Reduction in CO2e Emissions
186(1)
8.8.2 Daily CO2e Emissions Profile
186(1)
8.8.3 Low-Carbon Economy
186(2)
8.9 Summary
188(3)
Appendix A Simulation Parameters
189(1)
Appendix B Proof of (8.38)
189(2)
9 D2D Communications in Hierarchical HetNets
191(20)
9.1 Introduction
191(1)
9.2 Modelling Hierarchical Heterogeneous Networks
192(5)
9.2.1 Network Architecture
193(1)
9.2.2 D2D User Density in Hierarchical HetNets
194(2)
9.2.3 Spectrum Partitioning in Hierarchical HetNets
196(1)
9.2.4 Power Control over D2D Links
196(1)
9.3 Spectral Efficiency Analysis
197(3)
9.3.1 Traditional HetNet
197(1)
9.3.2 Hierarchical HetNet
198(2)
9.4 Average User Transmission Power Analysis
200(4)
9.4.1 Discussion on Transmission Power Analysis of D2D Users
202(2)
9.5 Backhaul Energy Analysis
204(4)
9.5.1 Backhaul Power Consumption
204(1)
9.5.2 Backhaul Energy Efficiency
205(1)
9.5.3 Considerations on Backhaul Energy Efficiency of Hierarchical HetNet
206(2)
9.6 Summary
208(3)
Appendix A
209(1)
Appendix B Simulation Parameters
210(1)
10 Emerging Device-Centric Communications
211(19)
10.1 Introduction
211(1)
10.2 Emerging Device-Centric Paradigms
212(2)
10.2.1 Device-to-Device Communication Management
213(1)
10.2.2 Device-to-Device Communication Architecture
213(1)
10.2.3 Device-to-Device Communication Challenges
214(1)
10.3 Devices-to-Device Communications
214(2)
10.3.1 System Model
214(2)
10.4 Optimal Selection of Source Devices and Radio Interfaces
216(5)
10.4.1 Device Selection Criteria
217(1)
10.4.2 Ascending Proxy Auction for Device Selection
218(1)
10.4.3 Discussions on Device and Radio Interface Selection
219(2)
10.5 Optimal Packet Split among Devices
221(3)
10.6 Green Analysis of Mobile Devices
224(4)
10.6.1 Energy Consumption of Mobile Devices
225(1)
10.6.2 Electricity Cost for Mobile Charging
226(1)
10.6.3 Battery Life of Mobile Devices
227(1)
10.7 Some Challenges and Future Directions
228(1)
10.7.1 Centralized Ds2D Set-up
228(1)
10.7.2 Decentralized Ds2D Set- up
228(1)
10.8 Summary
229(1)
References 230(15)
Index 245
Muhammad Ismail: Postdoctoral Research Associate, Electrical and Computer Engineering Department, Texas A&M University at Qatar, Doha, Qatar. Dr. Ismails area of expertise is related to radio resource allocation in a heterogeneous wireless medium. He is a co-recipient of the best paper award at IEEE ICC '14 for a paper related to green resource allocation in a heterogeneous wireless medium: M. Ismail, A. T. Gamage, W. Zhuang, and X. Shen, "Energy efficient uplink resource allocation in a heterogeneous wireless medium," IEEE ICC'14, (to be listed in IEEExplore).

Muhammad Zeeshan Shakir: Assistant Research Scientist, Electrical and Computer Engineering Department, Texas A&M University at Qatar, Doha, Qatar. Dr. Shakir's research interests include design and deployment of diverse green wireless communication systems including hyper-dense heterogeneous small-cell networks with particular focus on traffic offloading techniques and backhauling technologies. He has published more than 50 technical journal and conference papers and has contributed to 6 books.

Khalid Qaraqe: Professor, Electrical and Computer Engineering Department, Texas A&M University at Qatar, Doha, Qatar. Dr. Qaraqe has over 15 years of experience in the telecommunications industry. He has worked for Qualcomm, Enad Design Systems, Cadence Design Systems/Tality Corporation, STC, SBC and Ericsson. His research interests include communication theory and its application to design and performance analysis of cellular systems and indoor communication systems. Particular interests are in the development of 4G LTE, cognitive radio systems, broadband wireless communications and diversity techniques.

Erchin Serpedin: Professor, Electrical and Computer Engineering Department, Texas A&M University, College Station, Texas, USA.  Dr. Serpedin is the author of two research monographs, one edited textbook, 100 journal papers and 180 conference papers, and has served as associate editor for approximately 12 journals including IEEE Transactions on Information Theory, IEEE Signal Processing Magazine, IEEE Transactions on Communications, and IEEE Communications Letters. His research interests include signal processing, wireless communications, computational statistics, and bioinformatics and systems biology. He is currently serving as editor in chief of the Eurasip Journal on Bioinformatics and Systems Biology, an online journal edited by Springer. He is also an IEEE Fellow.
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