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E-raamat: Ultra-Dense Networks for 5G and Beyond: Modelling, Analysis, and Applications

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  • Ilmumisaeg: 31-Jan-2019
  • Kirjastus: John Wiley & Sons Inc
  • Keel: eng
  • ISBN-13: 9781119473725
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  • Formaat: PDF+DRM
  • Ilmumisaeg: 31-Jan-2019
  • Kirjastus: John Wiley & Sons Inc
  • Keel: eng
  • ISBN-13: 9781119473725

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"A comprehensive insight into the theory, models and techniques of ultra-dense networks and applications in 5G and other emerging wireless networks -Ultra-dense networks and communications systems are emerging topics, having many applications that have potential to solve varieties of real-life problems -Presents recent advances in ultra-dense networks for 5G networks and beyond, i.e., cognitive radio networks, massive MIMO, device-to-device communications, mm-wave communications, and energy harvesting communications -One of the first books to focus solely on ultra-dense networks for 5G in a complete presentation Market description: Primary: postgraduate students, researchers and engineers in the field of wireless communications who will find it an ideal reference to further explore the potential of ultra-dense networks with a view to designing high speed communications in advanced networks of the future Secondary: researchers in academia, industry, as well as practitioners in governmental agencies"--

Offers comprehensive insight into the theory, models, and techniques of ultra-dense networks and applications in 5G and other emerging wireless networks

The need for speed—and power—in wireless communications is growing exponentially. Data rates are projected to increase by a factor of ten every five years—and with the emerging Internet of Things (IoT) predicted to wirelessly connect trillions of devices across the globe, future mobile networks (5G) will grind to a halt unless more capacity is created. This book presents new research related to the theory and practice of all aspects of ultra-dense networks, covering recent advances in ultra-dense networks for 5G networks and beyond, including cognitive radio networks, massive multiple-input multiple-output (MIMO), device-to-device (D2D) communications, millimeter-wave communications, and energy harvesting communications.

Clear and concise throughout, Ultra-Dense Networks for 5G and Beyond - Modelling, Analysis, and Applications offers a comprehensive coverage on such topics as network optimization; mobility, handoff control, and interference management; and load balancing schemes and energy saving techniques. It delves into the backhaul traffic aspects in ultra-dense networks and studies transceiver hardware impairments and power consumption models in ultra-dense networks. The book also examines new IoT, smart-grid, and smart-city applications, as well as novel modulation, coding, and waveform designs.

  • One of the first books to focus solely on ultra-dense networks for 5G in a complete presentation
  • Covers advanced architectures, self-organizing protocols, resource allocation, user-base station association, synchronization, and signaling
  • Examines the current state of cell-free massive MIMO, distributed massive MIMO, and heterogeneous small cell architectures
  • Offers network measurements, implementations, and demos
  • Looks at wireless caching techniques, physical layer security, cognitive radio, energy harvesting, and D2D communications in ultra-dense networks

Ultra-Dense Networks for 5G and Beyond - Modelling, Analysis, and Applications is an ideal reference for those who want to design high-speed, high-capacity communications in advanced networks, and will appeal to postgraduate students, researchers, and engineers in the field. 

List of Contributors
xi
Preface xv
Part I Fundamentals of Ultra-dense Networks
1(90)
1 Fundamental Limits of Ultra-dense Networks
3(38)
Marios Kountouris
Van Minh Nguyen
1.1 Introduction
3(3)
1.2 System Model
6(3)
1.2.1 Network Topology
6(1)
1.2.2 Wireless Propagation Model
6(2)
1.2.3 User Association
8(1)
1.2.4 Performance Metrics
8(1)
1.3 The Quest for Exact Analytical Expressions
9(16)
1.3.1 Coverage Probability
10(6)
1.3.2 The Effect of LOS Fading
16(3)
1.3.3 The Effect of BS Height
19(6)
1.4 The Quest for Scaling Laws
25(11)
1.4.1 User Performance
26(7)
1.4.2 Network Performance
33(2)
1.4.3 Network Ordering and Design Guidelines
35(1)
1.5 Conclusions and Future Challenges
36(5)
Bibliography
37(4)
2 Performance Analysis of Dense Small Cell Networks with Line of Sight and Non-Line of Sight Transmissions under Rician Fading
41(24)
Amir Hossein Jafari
Ming Ding
David Lopez-Perez
2.1 Introduction
41(1)
2.2 System Model
42(2)
2.2.1 BS Distribution
42(1)
2.2.2 User Distribution
42(1)
2.2.3 Path Loss
43(1)
2.2.4 User Association Strategy (UAS)
44(1)
2.2.5 Antenna Radiation Pattern
44(1)
2.2.6 Multi-path Fading
44(1)
2.3 Coverage Probability Analysis Based on the Piecewise Path Loss Model
44(2)
2.4 Study of a 3GPP Special Case
46(6)
2.4.1 The Computation of TL1
47(1)
2.4.2 The Computation of TNL1
48(9)
2.4.3 The Computation of TL2
51(1)
2.4.4 The Computation of TNL2
51(1)
2.4.5 The Results of pcov(λ, γ) and AASE(λ, γ0)
52(1)
2.5 Simulation and Discussion
52(3)
2.5.1 Validation of the Analytical Results of pcov(λ, γ) for the 3GPP Case
52(2)
2.5.2 Discussion on the Analytical Results of AASE(λ, γ) for the 3GPP Case
54(1)
2.6 Conclusion
55(10)
Appendix A Proof of Theorem 1.1
55(5)
Appendix B Proof of Lemma 2.2
60(1)
Appendix C Proof of Lemma 2.3
61(1)
Appendix D Proof of Lemma 2.4
62(1)
Bibliography
62(3)
3 Mean Field Games for 5G Ultra-dense Networks: A Resource Management Perspective
65(26)
Mbazingwa E. Mkiramweni
Chungang Yang
Zhu Han
3.1 Introduction
65(2)
3.2 Literature Review
67(4)
3.2.1 5G Ultra-dense Networks
67(4)
3.2.2 Resource Management Challenges in 5G
71(1)
3.2.3 Game Theory for Resource Management in 5G
71(1)
3.3 Basics of Mean field game
71(5)
3.3.1 Background
72(1)
3.3.2 Mean Field Games
73(3)
3.4 MFGs for D2D Communications in 5G
76(2)
3.4.1 Applications of MFGs in 5G Ultra-dense D2D Networks
76(1)
3.4.2 An Example of MFGs for Interference Management in UDN
77(1)
3.5 MFGs for Radio Access Network in 5G
78(6)
3.5.1 Application of MFGs for Radio Access Network in 5G
79(2)
3.5.2 Energy Harvesting
81(1)
3.5.3 An Example of MFGs for Radio Access Network in 5G
81(3)
3.6 MFGs in 5G Edge Computing
84(1)
3.6.1 MFG Applications in Edge Cloud Communication
85(1)
3.7 Conclusion
85(6)
Bibliography
85(6)
Part II Ultra-dense Networks with Emerging 5G Technologies
91(112)
4 Inband Full-duplex Self-backhauling in Ultra-dense Networks
93(20)
Dani Korpi
Taneli Riihonen
Mikko Valkama
4.1 Introduction
93(1)
4.2 Self-backhauling in Existing Literature
94(1)
4.3 Self-backhauling Strategies
95(4)
4.3.1 Half-duplex Base Station without Access Nodes
97(1)
4.3.2 Half-duplex Base Station with Half-duplex Access Nodes
97(1)
4.3.3 Full-Duplex Base Station with Half-Duplex Access Nodes
98(1)
4.3.4 Half-duplex Base Station with Full-duplex Access Nodes
99(1)
4.4 Transmit Power Optimization under QoS Requirements
99(2)
4.5 Performance Analysis
101(8)
4.5.1 Simulation Setup
101(2)
4.5.2 Numerical Results
103(6)
4.6 Summary
109(4)
Bibliography
110(3)
5 The Role of Massive MIMO and Small Cells in Ultra-dense Networks
113(22)
Qi Zhang
Howard H. Yang
Tony Q. S. Quek
5.1 Introduction
113(2)
5.2 System Model
115(2)
5.2.1 Network Topology
115(1)
5.2.2 Propagation Environment
116(1)
5.2.3 User Association Policy
117(1)
5.3 Average Downlink Rate
117(6)
5.3.1 Association Probabilities
117(2)
5.3.2 Uplink Training
119(1)
5.3.3 Downlink Data Transmission
120(1)
5.3.4 Approximation of Average Downlink Rate
121(2)
5.4 Numerical Results
123(4)
5.4.1 Validation of Analytical Results
123(1)
5.4.2 Comparison between Massive MIMO and Small Cells
124(2)
5.4.3 Optimal Network Configuration
126(1)
5.5 Conclusion
127(8)
Appendix
128(1)
A.1 Proof of Theorem 5.1
128(1)
A.2 Proof of Corollary 5.1
129(1)
A.3 Proof of Theorem 5.2
129(1)
A.4 Proof of Theorem 5.3
130(1)
A.5 Proof of Proposition 5.1
130(1)
A.6 Proof of Proposition 5.2
130(1)
Bibliography
131(4)
6 Security for Cell-free Massive MIMO Networks
135(16)
Tiep M. Hoang
Hien Quoc Ngo
Trung O. Duong
Hoang D. Tuan
6.1 Introduction
135(1)
6.2 Cell-free Massive MIMO System Model
136(3)
6.3 Cell-free System Model in the presence of an active eavesdropper
139(4)
6.4 On Dealing with Eavesdropper
143(3)
6.4.1 Case 1: Power Coefficients Are Different
143(2)
6.4.2 Case 2: Power Coefficients Are the Same
145(1)
6.5 Numerical Results
146(2)
6.6 Conclusion
148(3)
Appendix
149(1)
Bibliography
150(1)
7 Massive MIMO for High-performance Ultra-dense Networks in the Unlicensed Spectrum
151(24)
Adrian Garcia-Rodriguez
Giovanni Geraci
Lorenzo Galati-Giordano
David Lopez-Perez
7.1 Introduction
151(1)
7.2 System Model
152(2)
7.3 Fundamentals of Massive MIMO Unlicensed (mMIMO-U)
154(6)
7.3.1 Channel Covariance Estimation
154(1)
7.3.2 Enhanced Listen Before Talk (eLBT)
155(2)
7.3.3 Neighboring-Node-Aware Scheduling
157(2)
7.3.4 Acquisition of Channel State Information
159(1)
7.3.5 Beamforming with Radiation Nulls
160(1)
7.4 Performance Evaluation
160(5)
7.4.1 Outdoor Deployments
160(1)
7.4.1.1 Cellular/Wi-Fi Coexistence
161(1)
7.4.1.2 Achievable Cellular Data Rates
162(3)
74.2 Indoor Deployments
165(5)
7.4.2.1 Channel Access Success Rate
166(1)
7.4.2.2 Downlink User SINR
166(3)
7.4.2.3 Downlink Sum Throughput
169(1)
7.5 Challenges
170(2)
7.5.1 Wi-Fi Channel Subspace Estimation
170(1)
7.5.2 Uplink Transmission
170(1)
7.5.3 Hidden Terminals
171(1)
7.6 Conclusion
172(3)
Bibliography
172(3)
8 Energy Efficiency Optimization for Dense Networks
175(28)
Quang-Doanh Vu
Markku Juntti
Een-Kee Hong
Le-Nam Tran
8.1 Introduction
175(1)
8.2 Energy Efficiency Optimization Tools
176(5)
8.2.1 Fractional Programming
176(1)
8.2.2 Concave Fractional Programs
177(1)
8.2.2.1 Parameterized Approach
177(1)
8.2.2.2 Parameter-free Approach
178(1)
8.2.3 Max--Min Fractional Programs
179(1)
8.2.4 Generalized Non-convex Fractional Programs
179(1)
8.2.5 Alternating Direction Method of Multipliers for Distributed Implementation
180(1)
8.3 Energy Efficiency Optimization for Dense Networks: Case Studies
181(19)
8.3.1 Multiple Radio Access Technologies
181(1)
8.3.1.1 System Model and Energy Efficiency Maximization Problem
182(2)
8.3.1.2 Solution via Parameterized Approach
184(1)
8.3.1.3 Solution via Parameter-free Approach
184(1)
8.3.1.4 Distributed Implementation
185(4)
8.3.1.5 Numerical Examples
189(2)
8.3.2 Dense Small Cell Networks
191(1)
8.3.2.1 System Model
191(2)
8.3.2.2 Centralized Solution via Successive Convex Approximation
193(2)
8.3.2.3 Distributed Implementation
195(3)
8.3.2.4 Numerical Examples
198(2)
8.4 Conclusion
200(3)
Bibliography
200(3)
Part III Applications of Ultra-dense Networks
203(86)
9 Big Data Methods for Ultra-dense Network Deployment
205(26)
Weisi Guo
Maria Liakata
Guillem Mosquera
Weijie Qi
Jie Deng
Jie Zhang
9.1 Introduction
205(2)
9.1.1 The Economic Case for Big Data in UDNs
205(2)
9.1.2
Chapter Organization
207(1)
9.2 Structured Data Analytics for Traffic Hotspot Characterization
207(12)
9.2.1 Social Media Mapping of Hotspots
207(4)
9.2.2 Community and Cluster Detection
211(2)
9.2.3 Machine Learning for Clustering in Heterogeneous UDNs
213(6)
9.3 Unstructured Data Analytics for Quality-of-Experience Mapping
219(7)
9.3.1 Topic Identification
220(1)
9.3.2 Sentiment
221(1)
9.3.3 Data-Aware Wireless Network (DAWN)
222(4)
9.4 Conclusion
226(5)
Bibliography
227(4)
10 Physical Layer Security for Ultra-dense Networks under Unreliable Backhaul Connection
231(16)
Huy T. Nguyen
Nam-Phong Nguyen
Trung Q. Duong
Won-Joo Hwang
10.1 Backhaul Reliability Level and Performance Limitation
232(3)
10.1.1 Outage Probability Analysis under Backhaul Reliability Impacts
233(1)
10.1.2 Performance Limitation
234(1)
10.1.3 Numerical Results
234(1)
10.2 Unreliable Backhaul Impacts with Physical Layer Security
235(12)
10.2.1 The Two-Phase Transmitter/Relay Selection Scheme
237(3)
10.2.2 Secrecy Outage Probability with Backhaul Reliability Impact
240(1)
10.2.3 Secrecy Performance Limitation under Backhaul Reliability Impact
240(1)
10.2.4 Numerical Results
241(1)
Appendix A
242(1)
Appendix B
243(1)
Appendix C
244(1)
Bibliography
245(2)
11 Simultaneous Wireless Information and Power Transfer in UDNs with Caching Architecture
247(20)
Sumit Gautam
Thang X. Vu
Symeon Chatzinotas
Bjorn Ottersten
11.1 Introduction
247(2)
11.2 System Model
249(3)
11.2.1 Signal Model
250(1)
11.2.2 Caching Model
251(1)
11.2.3 Power Assumption at the Relay
252(1)
11.3 Maximization of the serving information rate
252(3)
11.3.1 Optimization of TS Factors and the Relay Transmit Power
253(2)
11.3.2 Relay Selection
255(1)
11.4 Maximization of the Energy Stored at the Relay
255(5)
11.4.1 Optimization of TS Factors and the Relay Transmit Power
256(3)
11.4.2 Relay Selection
259(1)
11.5 Numerical Results
260(3)
11.6 Conclusion
263(4)
Acknowledgment
265(1)
Bibliography
265(2)
12 Cooperative Video Streaming in Ultra-dense Networks with D2D Caching
267(22)
Nguyen-Son Vo
Trung Q. Duong
12.1 Introduction
267(1)
12.2 5G Network with Dense D2D Caching for Video Streaming
268(5)
12.2.1 System Model and Assumptions
269(1)
12.2.2 Cooperative Transmission Strategy
270(1)
12.2.3 Source Video Packetization Model
271(2)
12.3 Problem Formulation and Solution
273(3)
12.3.1 System Parameters Formulation
273(1)
12.3.1.1 Average Reconstructed Distortion
273(1)
12.3.1.2 Energy Consumption Guarantee
274(1)
12.3.1.3 Co-channel Interference Guarantee
275(1)
12.3.2 RDO Problem
275(1)
12.3.3 GAs Solution
276(1)
12.4 Performance Evaluation
276(9)
12.4.1 D2D Caching
276(1)
12.4.2 RDO
277(1)
12.4.2.1 Simulation Setup
277(3)
12.4.2.2 Performance Metrics
280(5)
12.4.2.3 Discussions
285(1)
12.5 Conclusion
285(4)
Bibliography
285(4)
Index 289
TRUNG Q. DUONG, PHD, is a Reader at Queen's University Belfast, UK, and is currently serving as an Editor for IEEE Transactions on Wireless Communications and IEEE Transactions on Communications.

XIAOLI CHU, PHD, is a Reader at the University of Sheffield, UK, and is an Editor for the IEEE Wireless Communications Letters and the IEEE Communications Letters.

HIMAL A. SURAWEERA, PHD, is a Senior Lecturer at the University of Peradeniya, Sri Lanka, and serves as an Editor of the IEEE Transactions on Wireless Communications, IEEE Transactions on Communications and IEEE Transactions on Green Communications and Networking.