Ultra-dense Networks: Principles and Applications

Cover
Half-title
Title page
Copyright information
Contents
List of Contributors
Part I Overview
	1 Ultra-dense Networks and Sliced Network Services
		1.1 Introduction
			1.1.1 5G Network Slicing
		1.2 Cloud Computational Platforms and Networking
		1.3 Orchestrators and 5GC
			1.3.1 Boarding Virtual Network Functions
			1.3.2 Orchestrator Layers
		1.4 SDN and Overlaid Networks
		1.5 Monitoring Service and Platform
			1.5.1 Telemetry Services
			1.5.2 Application Deployment Options
		1.6 Conclusions
		References
	2 Ultra-dense Cloud Radio Access Network Architecture
		2.1 Introduction
		2.2 B5G Ultra-dense Cloud Radio Access Network Architecture
		2.3 Fronthauling via mmWave in a UDCRAN with Phantom Cells
		2.4 Fronthauling via Unlicensed Spectrum
		2.5 Fronthauling via Terrestrial FSO
		2.6 Fronthauling via UAV-Mounted FSO
		2.7 Comparison and Research Issues in B5G UDCRAN
		2.8 Conclusion
		References
Part II Physical Layer Design
	3 NOMA-Based Ultra-dense Networks
		3.1 Introduction
		3.2 Overview of NOMA-Enabled HUDNs
			3.2.1 HUDNs
			3.2.2 NOMA
			3.2.3 Understanding NOMA in HUDNs
		3.3 A Unified NOMA Framework for HUDNs
			3.3.1 Overview
			3.3.2 Uplink and Downlink Communications
			3.3.3 User Association
			3.3.4 Resource Sharing
		3.4 Case Studies for NOMA-Enabled HUDNs
			3.4.1 User Association in NOMA-Enabled HUDNs
			3.4.2 Resource Sharing in NOMA-Enabled HUDNs
		3.5 Research Challenges in NOMA-Enabled HUDNs
		3.6 Conclusions
		References
	4 Physical Layer Security in Ultra-dense Networks
		4.1 Introduction
		4.2 Key Features in Ultra-dense Networks
		4.3 Ultra-dense Network and Physical Layer Security Are a Good Match
		4.4 Physical Layer Security for Safeguarding IoT and V2X Transmissions
		4.5 Physical Layer Security for Safeguarding Edge Computing Service
		4.6 Physical Layer Security for Safeguarding Edge Caching Service
		4.7 Summary
		References
	5 Millimeter-Wave Multiantenna Ultra-dense Networks
		5.1 Introduction for Ultra-dense Networks in Millimeter-Wave Frequencies Band
			5.1.1 Next-Generation Network – UDN
			5.1.2 Millimeter-Wave Networks
			5.1.3 MmWave Antenna Pattern
		5.2 Approach and Contributions
		5.3 System Description
		5.4 Secrecy Evaluation
			5.4.1 Simplified LoS mmWave Model
			5.4.2 Uniform Linear Array
		5.5 Numerical Results and Discussions
			5.5.1 Average Achievable Secrecy Rate with UPA
			5.5.2 Average Achievable Secrecy Rate with ULA
		5.6 Conclusion
		References
	6 Interference Management in Ultra-dense Networks
		6.1 Introduction
		6.2 Features of Interference in UDNs
			6.2.1 Reduced Difference of Interference Levels
			6.2.2 Hard-Estimated Interference
			6.2.3 Interference Correlation
		6.3 A Brief Overview of Interference Management Techniques
			6.3.1 Interference Avoidance
			6.3.2 Interference Cancellation
			6.3.3 Interference Coordination
		6.4 Implementation of Interference Management in UDNs
			6.4.1 Interference Management Entity for UDNs
		6.5 Efficient Interference Management Strategy in UDNs
			6.5.1 Implementation Detail
			6.5.2 Performance Evaluation
		6.6 Open Issues of Interference Management
			6.6.1 Interference Management in mmWave Systems
			6.6.2 Interference Management in NOMA Systems
			6.6.3 Self-Organizing Interference Management
		6.7 Concluding Remarks
		References
	7 3D-Based Base Station Deployment in Ultra-dense Networks
		7.1 Introduction
		7.2 Multilayer UDN Model
			7.2.1 Network Description
			7.2.2 Base Station Association Rule
		7.3 Performance Analysis
			7.3.1 Network Interference
			7.3.2 Coverage Probability
			7.3.3 Area-Spectral Efficiency
		7.4 Numerical Results and Discussions
			7.4.1 Performance of the Single-Layer UDN
			7.4.2 Performance of the Multilayer UDN
		7.5 Conclusions
		References
	8 Power Control in Full-duplex Ultra-dense Heterogeneous Networks
		8.1 Introduction
		8.2 System Model
			8.2.1 Problem Formulation
		8.3 Simulation and Discussion
		8.4 Conclusion
		References
Part III Resource Allocation and Network Management
	9 Delay and Traffic Matching in Ultra-dense Networks
		9.1 System Model for Spatiotemporal Traffic
			9.1.1 Models Based on Stochastic Geometry and Queueing Theory
			9.1.2 Transmission Model
			9.1.3 Bounding Approaches
		9.2 Delay Analysis in Ultra-dense Networks
			9.2.1 Challenges of Delay Analysis in UDNs
			9.2.2 Promising Approaches
		9.3 Traffic Matching in Ultra-dense Networks
			9.3.1 Need for Matching the Traffic in UDNs
			9.3.2 Useful Approaches to Match Traffic
			9.3.3 Handle Spatiotemporal Traffic in UDNs
		References
	10 Traffic Offloading in Software Defined Ultra-dense Networks
		10.1 Introduction
		10.2 Architecture of Software-Defined Wireless Networks
		10.3 Contract Formulation for Traffic Offloading
			10.3.1 Transmission Model Formulation
			10.3.2 Economic Model Formulation
		10.4 Contract Design for Traffic Offloading
			10.4.1 Contract Design with Information Asymmetry
			10.4.2 Contract Design without Information Asymmetry
			10.4.3 Contract Design by Linear Pricing
		10.5 Conditions for Contract Feasibility
		10.6 Simulation Results
		10.7 Conclusion
		10.8 Proof of Lemma 10.1
		10.9 Proof of Lemma 10.2
		References
	11 Resource Allocation in Ultra-dense Networks
		11.1 Motivation and Scopes
		11.2 System Model
		11.3 Problem Formulation
		11.4 Overlapped UC Clustering
		11.5 Resource Allocation Solution
			11.5.1 Solution Portrayal
			11.5.2 Solution Analysis
		11.6 Numerical Simulations
			11.6.1 The Performance versus the Network Density
			11.6.2 The Performance versus the Number of RBs
		11.7 Conclusions
		References
	12 Wireless Edge Caching in Ultra-dense Networks
		12.1 Introduction
		12.2 Caching at the Transmitter Side
			12.2.1 Deterministic Caching
			12.2.2 Random Caching
			12.2.3 Coded Caching
		12.3 Caching at the Receiver Side
			12.3.1 Caching for Transmit Load Reduction: Coded Multicast
			12.3.2 Caching for Playback Delay Reduction in Video Streaming Services
		References
	13 User Association in Ultra-dense Networks
		13.1 Introduction
		13.2 System Model and Problem Formulation
			13.2.1 System Model
			13.2.2 Problem Formulation
		13.3 Lagrangian Dual Decomposition
			13.3.1 Dual Decomposition
			13.3.2 Energy Efficiency and Power Allocation
			13.3.3 Iterative Gradient Algorithm
			13.3.4 Complexity Analysis
		13.4 Simulation Results and Discussion
		13.5 Conclusion
		References
	14 UAV-Based Ultra-dense Networks
		14.1 Channel Modeling
			14.1.1 Air-to-Ground Channel
			14.1.2 Cellular BS-to-UAV Channel
		14.2 UAV-Enabled Base Stations
			14.2.1 Static Deployment
			14.2.2 Dynamic Trajectory Planning
		14.3 UAV-Enabled Relays
		14.4 UAV-Enabled Energy Transfer
			14.4.1 Static Time Scheduling
			14.4.2 Dynamic Trajectory Planning
		14.5 Robust Spectrum Sharing with Terrestrial Networks
		14.6 Summary
		References
	15 Generalized Low-Rank Optimization for Ultra-dense Fog-RANs
		15.1 Introduction
			15.1.1 Fog-RANs
			15.1.2 Generalized Low-Rank Models
			15.1.3 Low-Rank Optimization Algorithms
			15.1.4 Outline
		15.2 Generalized Low-Rank Models in Ultra-dense Fog-RANs
			15.2.1 A Generalized Low-Rank Framework
			15.2.2 Low-Rank Optimization Examples in Fog-RANs
		15.3 The Power of Nonconvex Paradigms for Ultra-dense Fog-RANs
			15.3.1 Low-Rank Optimization via Nonconvex Factorization
			15.3.2 The Framework of Riemannian Optimization
			15.3.3 Practical Implementation
		15.4 Matrix Optimization on Quotient Manifold
			15.4.1 Problem Structures for Fixed-Rank Matrices
			15.4.2 Matrix Representation for the Quotient Manifolds
			15.4.3 Riemannian Optimization Algorithms
			15.4.4 Convergence and Computational Complexity
		15.5 Numerical Results
		15.6 Summary and Discussion
		References
Part IV Field Trials and Tests
	16 Field Trials and Tests on Ultra-dense Networks
		16.1 UDN Prototype Test
		16.2 C-RAN-Based UDN Network Trial
			16.2.1 Test Results and Analysis
		16.3 Conclusion
		References
Index