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Radio Resource Management in Multi-Tier Cellular Wireless Networks [Kõva köide]

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Radio Resource Management in Multi-Tier Cellular Wireless NetworksSuurem pilt
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Püsilink: https://www.kriso.ee/db/9781118502679.html
Märksõnad:
"Providing an extensive overview of the radio resource management problem in femtocell networks, this invaluable book considers both code division multiple access femtocells and orthogonal frequency-division multiple access femtocells. In addition to incorporating current research on this topic, the book also covers technical challenges in femtocell deployment, provides readers with a variety of approaches to resource allocation and a comparison of their effectiveness, explains how to model various networks using Stochastic geometry and shot noise theory, and much more"--

"Provides MATLAB codes for simulations of resource management schemes and basics of wireless channel modelling"--

Hossain, Le, and Niyato summarize the radio resource management problem in multi-tier networks, covering small cells based on both code division multiple access (CDMA) and orthogonal frequency-division multiple access (OFDMA). Their topics include resource allocation approaches in multi-tier networks, resource allocation for clustered small cells in two-tier OFDMA networks, call admission control in fractional frequency reuse-based two-tier networks, game theory approaches for resource management in multi-tier networks, and self-organizing small cell networks. Annotation ©2014 Book News, Inc., Portland, OR (booknews.com)

Providing an extensive overview of the radio resource management problem in femtocell networks, this invaluable book considers both code division multiple access femtocells and orthogonal frequency-division multiple access femtocells. In addition to incorporating current research on this topic, the book also covers technical challenges in femtocell deployment, provides readers with a variety of approaches to resource allocation and a comparison of their effectiveness, explains how to model various networks using Stochastic geometry and shot noise theory, and much more.
Preface xv
Chapter 1 Overview Of Multi-Tier Cellular Wireless Networks
1(30)
1.1 Introduction
1(2)
1.2 Small Cells: Femtocells, Picocells, and Microcells
3(3)
1.3 Historical Perspective
6(1)
1.4 Overview of LTE Networks
6(7)
1.4.1 The Core Network
9(1)
1.4.2 The Access Network
9(1)
1.4.3 The Air Interface
10(1)
1.4.4 Radio Base Stations in LTE
11(1)
1.4.5 Mobility Management
11(2)
1.5 Overview of LTE-Advanced Networks
13(3)
1.6 LTE Femtocells (HeNBs)
16(2)
1.6.1 Access Network for HeNBs
16(1)
1.6.2 Access Modes of HeNBs
17(1)
1.6.3 Mobility Management
17(1)
1.7 3G Femtocells
18(1)
1.7.1 Network Entities
18(1)
1.7.2 Air Interface
19(1)
1.8 Channel Models for Small Cell Networks
19(3)
1.8.1 3GPP Model
20(1)
1.8.2 ITU Model
21(1)
1.9 Multi-Tier Cellular Wireless Network Modeling and Abstraction
22(1)
1.10 Technical Challenges in Small Cell Deployment
23(8)
References
28(3)
Chapter 2 Resource Allocation Approaches In Multi-Tier Networks
31(20)
2.1 Introduction
31(1)
2.2 Design Issues for Resource Allocation in Multi-Tier Networks
32(1)
2.3 Interference Management Approaches
33(13)
2.3.1 Femto-Aware Spectrum Arrangement Scheme
35(1)
2.3.2 Clustering of Small Cells
36(2)
2.3.3 Beam Subset Selection Strategy
38(1)
2.3.4 Collaborative Frequency Scheduling
38(1)
2.3.5 Power Control Approach
39(1)
2.3.6 Cognitive Radio Approach
40(2)
2.3.7 Fractional Frequency Reuse (FFR) and Resource Partitioning
42(2)
2.3.8 Resource Scheduling Strategies
44(2)
2.4 Qualitative Comparison Among Interference Management Approaches
46(1)
2.5 Future Research Directions
47(4)
References
48(3)
Chapter 3 Resource Allocation In Ofdma-Based Multi-Tier Cellular Networks
51(33)
3.1 Resource Allocation for OFDMA-Based Homogeneous Networks
52(14)
3.1.1 Physical-Layer Model
52(1)
3.1.2 Downlink Single-Cell Resource Allocation
53(6)
3.1.3 Uplink Single-Cell Resource Allocation
59(2)
3.1.4 Resource Allocation for Homogeneous Multi-Cell OFDMA Networks
61(5)
3.2 Fair Resource Allocation for Two-Tier OFDMA Networks
66(13)
3.2.1 Uplink Resource Allocation Problem
67(2)
3.2.2 Feasibility of a Sub-Channel Assignment Solution
69(2)
3.2.3 Optimal Algorithm and Its Complexity Analysis
71(1)
3.2.4 Sub-Optimal and Distributed Algorithm
71(6)
3.2.5 Numerical Examples
77(2)
3.3
Chapter Summary and Open Research Directions
79(5)
References
81(3)
Chapter 4 Resource Allocation For Clustered Small Cells In Two-Tier Ofdma Networks
84(18)
4.1 Introduction
84(1)
4.2 Related Work
85(2)
4.2.1 Clustering and Coalition Formations of Femtocells
85(1)
4.2.2 Resource Allocation in Clustered Femtocells
86(1)
4.3 System Model and Assumptions
87(1)
4.4 Joint Sub-Channel and Power Allocation in Femtocell Clusters
88(2)
4.5 Joint Sub-Channel and Power Allocation Using Convex Reformulation
90(1)
4.6 Sub-Channel Allocation
90(4)
4.6.1 Branch and Bound
91(1)
4.6.2 Linear Programming
91(1)
4.6.3 Lagrangian Relaxation
91(2)
4.6.4 Heuristic Scheme
93(1)
4.6.5 Feasibility Guarantee Algorithm
93(1)
4.7 Power Allocation
94(1)
4.8 Performance Evaluation
94(5)
4.8.1 Parameters
94(1)
4.8.2 Numerical Results
95(4)
4.9 Summary and Future Research Directions
99(3)
References
99(3)
Chapter 5 Resource Allocation In Two-Tier Networks Using Fractional Frequency Reuse
102(21)
5.1 Introduction
102(1)
5.2 Different FFR Schemes
103(3)
5.2.1 Strict FFR Scheme
103(2)
5.2.2 Soft FFR Scheme
105(1)
5.2.3 Sectored FFR (FFR-3) Scheme
106(1)
5.3 Optimal Static Fractional Frequency Reuse (OSFFR): An Improved FFR-Based Scheme
106(8)
5.3.1 System Model and Assumptions
107(1)
5.3.2 Channel Allocation
108(3)
5.3.3 Optimization of Spatial-Channel Allocation Parameters
111(3)
5.4 Performance Evaluation
114(6)
5.4.1 Performance Metrics
114(3)
5.4.2 Simulation Parameters
117(1)
5.4.3 Simulation Results
117(3)
5.5 Summary and Future Research Directions
120(3)
References
121(2)
Chapter 6 Call Admission Control In Fractional Frequency Reuse-Based Two-Tier Networks
123(32)
6.1 Related Work
123(3)
6.2 Call Admission Control Model
126(2)
6.3 Call Admission Control Policy for FFR-Based Multi-Tier Cellular Networks
128(4)
6.3.1 Problem Formulation
128(2)
6.3.2 Optimal CAC Policy
130(2)
6.4 Performance Evaluation
132(13)
6.4.1 Optimal CAC Policy
135(2)
6.4.2 Call Blocking/Dropping Probability Performance
137(5)
6.4.3 Comparison of Call-Level QoS
142(3)
6.5 Summary and Future Research Directions
145(10)
Appendix
146(1)
State Transition Probability
146(2)
Proof of Monotonically Non-Decreasing Property of Cost Function
148(3)
Proof of Convexity of Cost Function
151(3)
References
154(1)
Chapter 7 Game Theoretic Approaches For Resource Management In Multi-Tier Networks
155(51)
7.1 Introduction to Game Theory
155(11)
7.1.1 Motivations of Using Game Theory
156(1)
7.1.2 Types of Games
157(2)
7.1.3 Noncooperative Game
159(3)
7.1.4 Cooperative Game
162(3)
7.1.5 Game Theory and Radio Resource Management in Multi-Tier Networks
165(1)
7.2 Game Formulations for Power Control and Sub-Channel Allocation
166(11)
7.2.1 Utility-Based Distributed SINR Adaptation
168(3)
7.2.2 Multi-Tier Cognitive Cellular Radio Networks
171(2)
7.2.3 On-Demand Resource Sharing in Multi-Tier Networks
173(4)
7.3 Game Formulations for Pricing
177(9)
7.3.1 Price-Based Spectrum Sharing
178(5)
7.3.2 Energy-Efficient Spectrum Sharing and Power Allocation
183(3)
7.4 Game Formulations for Access Control
186(16)
7.4.1 Refunding Framework for Hybrid Access Small Cell Network
187(4)
7.4.2 Selection of Network Tier
191(1)
7.4.3 Coalitional Game for Cooperation among Macrocells and Small Cells
192(4)
7.4.4 Cooperative Interference Management
196(2)
7.4.5 Coalition-Based Access Control
198(4)
7.5 Future Research Directions
202(4)
References
203(3)
Chapter 8 Resource Allocation In Cdma-Based Multi-Tier Hetnets
206(44)
8.1 Power Control and Resource Allocation Techniques for Homogeneous CDMA Networks
208(5)
8.1.1 Target-SINR-Tracking Power Control
209(1)
8.1.2 Power Control Design from Game Theoretic View
210(2)
8.1.3 Joint Base Station Association and Power Control
212(1)
8.2 Game Theoretic Based Power Control for Two-Tier CDMA HetNets
213(9)
8.2.1 Guaranteeing QoS for Macro Users
215(2)
8.2.2 Power Adaptation and Admission Control Algorithm
217(3)
8.2.3 Numerical Examples
220(2)
8.3 Joint Base Station Association and Power Control for CDMA HetNets
222(12)
8.3.1 Base Station Association and Power Control Algorithm
223(3)
8.3.2 Hybrid Power Control Algorithm
226(2)
8.3.3 Hybrid Power Control Adaptation Algorithm
228(3)
8.3.4 Application to Two-Tier Macrocell---Femtocell Networks
231(1)
8.3.5 Numerical Examples
231(3)
8.4 Distributed Pareto-Optimal Power Control for Two-Tier CDMA HetNets
234(12)
8.4.1 Distributed Pareto-Optimal SINR Assignment
238(3)
8.4.2 Distributed Algorithm for Femtocell Utility Maximization and Macrocell SINR Balancing
241(3)
8.4.3 Numerical Examples
244(2)
8.5 Summary and Open Research Issues
246(4)
References
246(4)
Chapter 9 Self-Organizing Small Cell Networks
250(52)
9.1 Self-Organizing Networks
251(7)
9.1.1 Motivations of Self-Organization
251(1)
9.1.2 Use Cases of Self-Organizing Small Cell Networks
252(1)
9.1.3 Classification of Self-Organizing Small Cell Networks
253(1)
9.1.4 Self-x Concept
254(2)
9.1.5 Interference Management for Self-Organizing Networks
256(2)
9.2 Self-Configuration
258(12)
9.2.1 Dynamic Traffic Off-loading
259(3)
9.2.2 Coverage Optimization of Small Cells
262(3)
9.2.3 Dynamic Frequency Allocation
265(3)
9.2.4 Coordinated Spectrum Assignment
268(2)
9.3 Self-Optimization
270(19)
9.3.1 Resource Allocation for Different Service Classes
272(3)
9.3.2 Self-Organizing Small Cell Management Architecture
275(4)
9.3.3 Evolutionary and Learning-Based Power Control
279(7)
9.3.4 Coordination Mechanism and Stochastic Geometry Analysis
286(3)
9.4 Self-Healing
289(7)
9.4.1 Collaborative Resource Allocation
290(3)
9.4.2 Transfer Learning-Based Diagnosis for Configuration Troubleshooting
293(3)
9.5 Future Research Directions
296(6)
References
297(5)
Chapter 10 Resource Allocation In Multi-Tier Networks With Cognitive Small Cells
302(19)
10.1 Introduction
302(1)
10.2 Background
303(4)
10.3 Analysis of Tier-Association Probability
307(7)
10.3.1 System Model and Assumptions
307(2)
10.3.2 Tier Association Probability
309(4)
10.3.3 Numerical Results
313(1)
10.4 Cognition Techniques for Small Cells
314(4)
10.5 Discussions and Future Research Directions
318(3)
References
319(2)
Index 321
Ekram Hossain is the Editor-in-Chief for the IEEE Communications Surveys and Tutorials, editor of the IEEE Transactions on Mobile Computing, and IEEE Wireless?Communications. He was awarded the 2011 IEEE Communications Society Fred Ellersick Prize Paper Award and the 2010 University of Manitoba Merit Award. Dr. Hossain is a registered Professional Engineer in the province of Manitoba, Canada.

Long Bao Le is an Assistant Professor with the National Institute of Scientific Research - Energy, Materials, and Telecommunications (INRS-EMT), in Quebec, Canada. He is a member of the editorial board of the IEEE Communications Surveys and Tutorials and the IEEE Wireless Communications Letters. Dr. Le earned his PhD from the University of Manitoba in 2007. From 2008-2010 he was a Post-Doctoral Research Associate at MIT.

Dusit Niyato is an Assistant Professor in the School of Computer Engineering at the Nanyang Technological University, Singapore. He obtained his Bachelor of Engineering in Computer Engineering from King Mongkut's Institute of Technology Ladkrabang (KMITL), Bangkok, Thailand. He received his PhD in Electrical and Computer Engineering from the University of Manitoba, Canada. His research interests are in the areas of radio resource management in cognitive radio networks, broadband wireless access networks, and small cell networks.