6G Mobile Wireless Networks

Preface
	Disclaimer
Contents
1 Introduction
2 6G Use Cases, Requirements, and Metrics
	1 Introduction
	2 Emerging Application of 6G Wireless Network
		2.1 Virtual, Augmented, and Mixed Reality
		2.2 Holographic Telepresence
		2.3 Automation: The Future of Factories
		2.4 Smart Lifestyle with Integrated Massive IoT
		2.5 Autonomous Driving and Connected Vehicles
		2.6 Healthcare
		2.7 Non-terrestrial Communication
		2.8 Under-Water Communication
		2.9 Disaster Management
		2.10 Environment
	3 Requirements and KPI Targets of 6G
		3.1 High Data Rate
		3.2 Extremely Low Latency
		3.3 Low Power Consumption
		3.4 High Frequency Bands
		3.5 Ultra-Reliability
		3.6 Security and Privacy
		3.7 Massive Connection Density
		3.8 Extreme Coverage Extension
		3.9 Mobility
	4 Performance Metrics
		4.1 Improving Quality of Service
		4.2 Refining Quality of Experience
		4.3 Quality of Physical Experience
		4.4 Self-Sustaining Networks
	References
3 6G Enabling Technologies
	1 Introduction
	2 6G Use Cases
	3 6G Enabling Technologies
		3.1 Novel Wireless Paradigms and Frequencies Above 100GHz
		3.2 Multi-Dimensional Network Architectures
		3.3 Predictive Models for Network Operations
	4 Conclusions
	References
4 Physical Layer Design Challenges for 6G Wireless
	1 Introduction
	2 The ROle of PHY Layer in 6G
	3 6G PHY at Terahertz (THz) Band
		3.1 Signal Processing Challenges
			3.1.1 Challenge 1: Accurate Estimation of Channel
			3.1.2 Challenge 2: Robust and Selective Filtering
	4 Artificial Intelligence (AI)/Machine Learning (ML) in 6G PHY
		4.1 Hardware Architectures for AI in Radio
	5 Security Issues at 6G PHY ``enabler of confidentiality in 6G connectivity''
	6 Conclusion
	References
5 PHY-Layer Design Challenges in Reconfigurable Intelligent Surface Aided 6G Wireless Networks
	1 Introduction
	2 System Model
	3 Channel Estimation in RIS-Aided Single-User Systems
		3.1 Channel Estimation Protocol
		3.2 Ambiguity Problem in Channel Estimation
		3.3 Two-Stage Channel Estimation Approach
		3.4 Numerical Results
	4 Channel Estimation in RIS-Aided Multi-User Systems
		4.1 Channel Estimation Protocol
		4.2 Channel Model
		4.3 Virtual Channel Representation
		4.4 Problem Formulation
		4.5 Matrix-Calibration Based Cascaded Channel Estimation Algorithm
			4.5.1 Bayesian Inference
			4.5.2 Message Passing for Marginal Posterior Computation
			4.5.3 Approximations for Message Passing
		4.6 Asymptotic Mean Square Error (MSE) Analysis
		4.7 Numerical Results
			4.7.1 Simulation Results Under Channel Generation Model (5.28)–(5.30)
			4.7.2 Simulation Results Under a More Realistic Channel Generation Model
	5 Conclusions
	6 Further Readings
	References
6 Millimeter-Wave and Terahertz Spectrum for 6G Wireless
	1 Background and Motivation
	2 Introduction to mmWave and THz Spectrum
		2.1 Need for the mmWave and THz Bands
		2.2 What Can mmWave and THz Frequencies Enable?
		2.3 Available Spectrum
	3 Propagation at the mmWave and THz Frequencies
		3.1 Differences from the Communication in Conventional Bands
			3.1.1 Signal Blockage
			3.1.2 High Directivity
			3.1.3 Atmospheric Absorption
		3.2 Channel Measurement Efforts
		3.3 Propagation at mmWave and THz Frequencies
			3.3.1 Atmospheric Attenuation
			3.3.2 Rainfall Attenuation
			3.3.3 Blockage
			3.3.4 Human Shadowing and Self Blockage
			3.3.5 Reflections and Scattering
			3.3.6 Diffraction
			3.3.7 Doppler Spread
			3.3.8 Absorption Noise
			3.3.9 Scintillation Effects
		3.4 Beamforming and Antenna Patterns
			3.4.1 Analog Beamforming Patterns
			3.4.2 Antenna Patterns for Multi-User/Stream Transmission
			3.4.3 THz Beamforming
		3.5 Channel Models
			3.5.1 mmWave Channel
			3.5.2 THz Channel
	4 The mmWave Communications Systems
		4.1 Key System Design Implications
		4.2 Potential Applications of mmWave Communications in 6G
	5 The THz Communications Systems
		5.1 Potential Applications of THz Communications in 6G
			5.1.1 Macroscale THz Communication
			5.1.2 Micro/nanoscale THz Communication
		5.2 Nanonetworks
	6 Standardization Efforts
		6.1 Standardization Efforts for mmWave Communications
		6.2 Standardization Efforts for THz Communications
	7 Conclusion
	References
7 Challenges in Transport Layer Design for Terahertz Communication-Based 6G Networks
	1 Introduction
	2 Mobility Challenges in TCP
		2.1 Impact on Spurious Wireless Loss
		2.2 Inefficient Re-transmission Timers
			2.2.1 Conventional TCP RTO Algorithm
		2.3 Highly Variable Channel and Remiss Flow Control
	3 Achieving Tbps Bitrate in TCP
		3.1 Wireless TCP Adaptive Congestion Control
		3.2 Multi-Core Awareness
	4 Other Challenges in TCP
		4.1 TCP Sequence Number Limits
		4.2 TCP Buffer Tuning
	5 Summary
	References
8 Mode Hopping for Anti-Jamming in 6G WirelessCommunications
	1 Introduction
	2 MFH System Model
		2.1 MH Pattern
		2.2 MFH Pattern
	3 MH Scheme
		3.1 Transmit Signal
		3.2 Received Signal
		3.3 Performance Analysis
	4 MFH Scheme
	5 Performance Evaluations
		5.1 BERs for Single User Scenario
		5.2 BERs for Multiple Users Scenario
		5.3 Comparison Between Binary DPSK and FSK Modulations for MH and MFH Schemes
	6 Conclusions
	References
9 Hybrid Lightwave/RF Connectivity for 6G Wireless Networks
	1 Introduction
	2 Channel Model
		2.1 VLC Channel Model
		2.2 RF Channel Model
	3 Resource Allocation
		3.1 The Value of User Fairness
	4 Integration with Non-orthogonal Multiple Access
		4.1 User Grouping
		4.2 Cross-Band Selection Combining
	5 Ultra Small Cells with Lightwave Power Transfer
	6 Conclusions and Future Research
	References
10 Resource Allocation in 6G Optical Wireless Systems
	1 Introduction
	2 Transmitter and Receiver Design
		2.1 Transmitter Design
		2.2 Receiver Design
	3 Multiple Access
		3.1 Wavelength Division Multiple Access (WDMA)
		3.2 MILP Model
	4 Evaluation in Different Indoor Environments
		4.1 Office
			4.1.1 Office OWC System Configuration
			4.1.2 Office OWC System Setup and Results
		4.2 Aircraft Cabin
			4.2.1 Aircraft Cabin OWC System Configuration
			4.2.2 Aircraft Cabin OWC System Setup and Results
		4.3 Data Centre
			4.3.1 Data Centre OWC System Configuration
			4.3.2 Data Centre OWC Setup and Results
	5 Conclusions
	References
11 Machine Type Communications in 6G
	1 Introduction
	2 MTC Applications and Devices
		2.1 General, Non-critical IoT
		2.2 Connected Vehicles and Road Safety
		2.3 Smart Cities as Organic Systems
		2.4 Industry Automation
		2.5 Body Area Networks
		2.6 Low-to-Zero Energy IoT
	3 Medium Access and Network Architecture for 6G MTC
		3.1 MTC Traffic Characterization
		3.2 Service Classes
		3.3 Physical Layer
			3.3.1 Transmission Medium
			3.3.2 Modulation
		3.4 MAC Layer
	4 Network Intelligence
	5 Situation-Aware Applications
	6 Conclusion
	References
12 Edge Intelligence in 6G Systems
	1 Introduction
	2 What Is the Edge and Why Do We Need It in 6G?
		2.1 The Wireless Migration Towards the Edge
			2.1.1 Towards Massive Small Data and Denser Cells
			2.1.2 The Need for High-Rate and High-Reliability Low Latency Communications (HRLLC)
			2.1.3 Towards Privacy-Preserving Intelligence
		2.2 How to Enable Collaborative Edge Intelligence?
	3 How Is Edge Intelligence Different than Centralized AI?
		3.1 Edge Data and Established Models
			3.1.1 Addressing the Heterogeneity and Non-i.i.d.! (i.i.d.!) Data
			3.1.2 Leveraging Edge Data for an HRLLC Realm
		3.2 Edge Training and Prediction Mechanisms
			3.2.1 Towards Generalizable and Personalized Learning
			3.2.2 Towards a Robust and Transparent Learning Mechanism
	4 Summary
	References
13 6G CloudNet: Towards a Distributed, Autonomous, and Federated AI-Enabled Cloud and Edge Computing
	1 Introduction
	2 5G and Beyond Networks
		2.1 Cloud Radio Access Networks
		2.2 C-RAN Architecture
		2.3 5G RAN Architecture
		2.4 Future Mobile Systems: Beyond 5G
	3 Trends Towards Intelligent-Based Optimized Networks
		3.1 AI-Enabled Cloud and Edge Computing
		3.2 Distributed and Federated AI
		3.3 Potential Synergism Between the ML and Communications
	4 Potential Technology Transformation for 6G
		4.1 Artificial Intelligence Exploitation
			4.1.1 Quasi-Autonomous Mobile Devices with AI-Enabled D2D Communication
			4.1.2 Self-Optimizing RAN Transceivers
			4.1.3 Cognition- and D2D-Aided Cooperative NOMA
			4.1.4 Photonics-Based Cognitive Radio and Cognitive Spectrum Management
			4.1.5 Context-Aware Implementation
		4.2 New Spectrum Band Exploitation
		4.3 Network Architectures and Technologies
			4.3.1 Ultra-Dense Heterogeneous Networks with Sub-networks
			4.3.2 Innovative Network Slicing
			4.3.3 Converged Network
			4.3.4 Holographic Radio
			4.3.5 All-Photonic RANs
		4.4 New Security, Trust, and Privacy Models
	5 Conclusion
	References
14 Cloud Fog Architectures in 6G Networks
	1 Introduction
	2 The Proposed Cloud Fog Architecture
		2.1 IoT Layer
		2.2 CPE Layer
		2.3 Access Fog Layer
		2.4 Metro Fog Layer
		2.5 Cloud DC Layer
	3 MILP Model
		3.1 Network Power Consumption (net _ pc)
		3.2 Processing Power Consumption (pr _ pc)
	4 Input Data for the MILP Model
		4.1 Processing and Data Rates
		4.2 Power Consumption Data
		4.3 Power Usage Effectiveness (PUE)
	5 Scenarios and Processing Placement Results
		5.1 Energy-Aware Processing Placement
		5.2 Scenario One
		5.3 Scenario Two
		5.4 Scenario Three
		5.5 Scenario Four
		5.6 Energy and Delay Aware Processing Placement
	6 Scenarios and Results
		6.1 Evaluation One: Power and Propagation Delay Minimization
		6.2 Evaluation Two: Power and Queuing Delay Minimization
	7 Conclusions and Future Work
	References
15 Towards a Fully Virtualized, Cloudified, and Slicing-Aware RAN for 6G Mobile Networks
	1 Background on Key Concepts Towards RAN Architecture in 6G Wireless Network
	2 Legacy RAN Architectures
		2.1 C-RAN
			2.1.1 Types of C-RAN! (C-RAN!)
		2.2 H-CRAN
			2.2.1 Heterogeneous Network
			2.2.2 H-CRAN Architecture
		2.3 V-CRAN
			2.3.1 System Architecture of V-CRAN! (V-CRAN!)
		2.4 Fog-RAN
			2.4.1 System Architecture
	3 Next-Generation RAN
		3.1 The NG-RAN! (NG-RAN!) Architecture
		3.2 The Management and Orchestration of RAN! (RAN!) Slices in NG-RAN! (NG-RAN!)
	4 Key Enabling Technologies Towards 6G! (6G!) RAN! (RAN!) Architecture
		4.1 Virtualization, Cloudification, and Slicing
		4.2 Use-Case Specific RAN! (RAN!) Slices
		4.3 Slice-Aware Functional Splits and Function Placement
		4.4 New Spectrum
		4.5 Intelligent Reflecting Surfaces
		4.6 Coordinated Multi-Point
		4.7 Non-orthogonal Multiple Access
		4.8 Wireless Energy Harvesting and Wireless Power Transmission
		4.9 Non-terrestrial Communication
		4.10 Machine Learning and Artificial Intelligence
		4.11 Edge Intelligence
		4.12 Context-Awareness
		4.13 Software-Defined Networks
	5 Conclusions
	References
16 Federated Learning in 6G Mobile Wireless Networks
	1 Introduction
	2 Preliminaries of FL
		2.1 Basic Concept and Features of FL
		2.2 Flavors of FL
			2.2.1 Federated Multi-Task Learning
			2.2.2 Federated RL
			2.2.3 General FL
	3 System Model of FL Over Wireless Communication Networks
		3.1 FL Model
		3.2 Computation and Transmission Model
			3.2.1 Local Computation
			3.2.2 Wireless Transmission
			3.2.3 Information Broadcast
		3.3 Problem Formulation
	4 Optimal Resource Allocation
		4.1 Optimal Resource Allocation
	5 Simulation Results
	6 Conclusions
	References
17 Role of Open-Source in 6G Wireless Networks
	1 Introduction
	2 Intelligence
		2.1 Environment AI
		2.2 Data Market
		2.3 Low-Level Algorithmic Development
		2.4 Semantic Communications
	3 Automation
		3.1 DevOps
		3.2 Autonomous Operations (AO)
	4 Open Issues
		4.1 Security and Privacy
		4.2 Support and Operation Complexity
		4.3 Business Model
	5 Concluding Remarks
	References
18 The Intersection of Blockchain and 6G Technologies
	1 Introduction
	2 Blockchain
		2.1 Architecture
		2.2 Data Models
		2.3 Consensus Mechanism
		2.4 Access
		2.5 Vulnerabilities
			2.5.1 Protocol Vulnerabilities
			2.5.2 Smart Contract Vulnerabilities
	3 Applications
		3.1 IoT
		3.2 Security
	4 Blockchain and 6G
		4.1 Enabling Technologies
		4.2 6G Services
	5 Challenges
	6 Conclusion
	References
19 Role of Quantum Technology in 6G
	1 Introduction
		1.1 Superposition
		1.2 State Measurements
		1.3 Entanglement
	2 Deutsch-Jozsa Algorithm
	3 Superdense Coding
	4 Error Correction
		4.1 Detecting and Correcting Bit-Flip Errors
		4.2 Detecting and Correcting Phase-Flip Errors
		4.3 Shor's 9 Qubit Code
		4.4 Other Quantum Error Correcting Codes
	5 Practical Considerations and Future
		5.1 Costly but Accurate Qubits (Coolbits)
		5.2 Quick but Dirty Qubits (Hotbits)
		5.3 Concluding Remarks
	References
20 Post-quantum Cryptography in 6G
	1 Introduction
	2 Cryptography and Quantum Computing
		2.1 Cryptography
		2.2 Quantum Computing
			2.2.1 Grover's Algorithm
		2.3 Shor's Algorithm
	3 Development of Quantum Computing
	4 Cryptography and the Development Towards 6G
	5 Post-quantum Secure Asymmetric Cryptography for 6G
		5.1 Key Establishment and Public-Key Encryption
			5.1.1 Classic McEliece
			5.1.2 CRYSTALS-Kyber
			5.1.3 NTRU
			5.1.4 Saber
			5.1.5 Alternate Candidates
		5.2 Digital Signatures
			5.2.1 CRYSTALS-Dilithium
			5.2.2 Falcon
			5.2.3 Rainbow
		5.3 Alternate Candidates
	6 Discussion
	7 Conclusion
	References
21 6G: Open Issues and Concluding Remarks
	1 Tera-Hertz Communication
	2 High-Precision Network Configuration
	3 Machine-Type Communication
	4 Augmented Intelligence
	5 Edge Computing with Computational Split
	6 Security, Privacy and Trustworthiness
	7 Rich-Media Services
	References
Index