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- Herausgeber: John Wiley & Sons
- Kategorie: Wissenschaft und neue Technologien
- Sprache: Englisch
6G Frontiers Enables readers to understand the exciting new technologies, architectural directions, technical aspects, and applications of 6G, plus legal and standardization approaches 6G Frontiers offers intelligent insight into the ongoing research trends, use cases, and key developmental technologies powering the upcoming 6G framework. The authors cover a myriad of important topics that intersect with 6G, such as hyper-intelligent networking, security, privacy, and trust, harmonized mobile networks, legal views, and standards initiatives. The work also explores the more extreme and controversial predictions surrounding 6G, such as hyper-connected smart cities, space tourism, and deep-sea tourism. Sample thought-provoking topics covered in the comprehensive work include: * Evolution of mobile networks, from 0G to 6G, including the driving trends, requirements, and key enabling technologies of each generation * Logistics of 6G networks, which are expected to offer peak data rates over 1 Tbps, imperceptible end-to-end delays (beneath 0.1 ms), and network availability and reliability rates beyond 99.99999% * New technology requirements for 6G, such as Further enhanced Mobile Broadband (FeMBB), ultra-massive Machine-Type Communication (umMTC), Mobile BroadBand and Low-Latency (MBBLL), and massive Low-Latency Machine Type communication (mLLMT) * Potential architectural directions of 6G, including zero-touch network and service management, intent-based networking, edge AI, intelligent network softwarization, and radio access networks A complete and modern resource for understanding the potential development, logistics, and implications of 6G networks, 6G Frontiers is a must-read reference for researchers, academics, and technology architects who wish to understand the cutting-edge progress that is being made towards better and faster wireless mobile technology.
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Veröffentlichungsjahr: 2022
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Table of Contents
Cover
6G Frontiers
Title Page
Copyright
Dedication
About the Authors
Preface
Intended Audience
Book Organization
Acknowledgments
Acronyms
Part I: Introduction
1 Evolution of Mobile Networks
1.1 Introduction
1.2 6G Mobile Communication Networks
2 Key Driving Trends Toward 6G
2.1 Introduction
2.2 Expansion of IoT toward IoE
2.3 Massive Availability of Small Data
2.4 Availability of Self‐Sustaining Networks
2.5 Convergence of Communications, Computing, Control, Localization, and Sensing (3CLS)
2.6 Zero Energy IoT
2.7 Advancement of Communication Technologies
2.8 Gadget‐Free Communication
2.9 Increasing Elderly Population
3 6G Requirements
3.1 6G Requirements/Vision
3.2 Further‐Enhanced Mobile Broadband (FeMBB)
3.3 Ultramassive, Machine‐Type Communication
3.4 Extremely Reliable Low Latency Communication
3.5 Extremely Low Power Communication
3.6 Long Distance and High Mobility Communication
3.7 High Spectrum Efficiency
3.8 High Area Traffic Capacity
3.9 Mobile Broadband and Low Latency (MBBLL)
3.10 Massive Broadband Machine‐Type Communications
3.11 Massive Low Latency Machine‐type Communications (mLLMT)
3.12 AI‐Assistive Extreme Communications
4 Key 6G Technologies
4.1 Radio Network Technologies
4.2 AI/ML/FL
4.3 DLT/Blockchain
4.4 Edge Computing
4.5 Quantum Communication
4.6 Other New Technologies
Part II: Architectural Directions
5 6G Architectural Visions
5.1 Evolution of Network Architecture
5.2 Intelligent Network of Subnetworks
5.3 A Greener Intelligent Network
5.4 Cybertwin‐based Network Architecture
6 Zero‐Touch Network and Service Management
6.1 Introduction
6.2 Need of Zero‐Touch Network and Service Management
6.3 Overview of Zero Touch Network and Service Management
6.4 ZSM Reference Architecture
6.5 Importance of ZSM for 5G and Beyond
7 Edge AI
7.1 Introduction
7.2 Benefits of Edge AI
7.3 Why Edge AI Is Important?
7.4 Building Blocks for Edge AI
7.5 Architectures for Edge AI networks
7.6 Level of Edge AI
7.7 Future Cloud Computing Perspective
7.8 Role of Edge AI in 6G
Acknowledgment
Note
8 Intelligent Network Softwarization
8.1 Network Softwarization
8.2 Intelligent Network Softwarization
9 6G Radio Access Networks
9.1 Key Aspects and Requirements
9.2 Aerial Radio Access Networks
9.3 AI‐enabled RAN
9.4 Open RAN
Notes
Part III: Technical Aspects
10 Security and Privacy of 6G
10.1 Introduction
10.2 Evolution of Mobile Security
10.3 6G Security Requirements
10.4 Security Threat Landscape for 6G Architecture
10.5 Security Challenges with 6G Applications
10.6 Security Impact on New 6G Technologies
10.7 Privacy
11 Resource Efficient Networks
11.1 Energy‐Efficient 6G Network Management
11.2 Energy‐efficient Security
11.3 Efficient Resource Management
Acknowledgement
12 Harmonized Mobile Networks and Extreme Global Network Coverage
12.1 Harmonized Mobile Networks
12.2 Extreme Global Network Coverage
12.3 Limitations and Challenges
13 Legal Aspects and Standardization of 6G Networks
13.1 Legal Aspects
13.2 6G Standardization Efforts
Part IV: Applications
14 6G for Healthcare
14.1 Evolution of Telehealth
14.2 Toward Intelligent Healthcare with 6G
14.3 Personalized Body Area Networks
14.4 XR for Healthcare Applications
14.5 Role of Blockchain in Medical Applications
14.6 Security and Privacy Aspects of 6G Healthcare Applications
15 Smart Cities and Society 5.0
15.1 Preliminaries of Smart Cities
15.2 6G for Smart Citizen
15.3 6G for Smart Transportation
15.4 6G for Smart Grid
15.5 6G for Supply Chain Management
15.6 6G for Other Smart Scenarios
Acknowledgement
16 Industrial Automation
16.1 Introduction
16.2 Background of Industry 5.0
16.3 Applications in Industry 5.0
16.4 Role of 6G in Industry 5.0
17 Wild Applications
17.1 Introduction
17.2 Metaverse
17.3 Deep‐Sea Explorations
17.4 Space Tourism
Acknowledgement
Part V: Conclusion
18 Conclusion
Bibliography
Index
End User License Agreement
List of Tables
Chapter 10
Table 10.1 Security KPIs and 6G vision.
Table 10.2 Security challenges in intelligence network management and orches...
List of Illustrations
Chapter 1
Figure 1.1 Evolution of Mobile Networks from 0G to 6G. Source: vectorplus / ...
Figure 1.2 Expected Timeline of 6G Development, Standardization and Launch....
Figure 1.3 Global 6G Development Initiatives.
Chapter 2
Figure 2.1 6G Driving Trends.
Figure 2.2 IoT to IoE Transition.
Figure 2.3 Advancement of communication technologies toward 6G.
Figure 2.4 Gadget‐free Communication.
Figure 2.5 Increasing elderly population.
Chapter 3
Figure 3.1 6G Requirements.
Figure 3.2 An application example (IoT Healthcare,
Figure 3.3 Application examples (such as space tourism [91] (Studiostoks/Ado...
Chapter 4
Figure 4.1 Promising scenarios in 6G enabled by THz communication: (a) high ...
Figure 4.2 Three categories of FL: (a) horizontal FL, (b) vertical FL, and (...
Figure 4.3 Illustration of the general transaction process of blockchain: (1...
Figure 4.4 A general architecture of MEC.
Chapter 5
Figure 5.1 6G architectural changes.
Figure 5.2 Toward greener intelligent networks.
Figure 5.3 Toward a cloud‐centric network architecture.
Chapter 6
Figure 6.1 The ZSM framework reference architecture.
Chapter 7
Figure 7.1 Use‐cases of edge AI.
Figure 7.2 Architecture of edge of things.
Figure 7.3 Illustration of a learning round of blockchain‐enabled federated ...
Figure 7.4 End‐to‐end Edge‐AI architecture.
Figure 7.5 Decentralized Edge‐AI architecture.
Figure 7.6 Edge AI five‐level categorization.
Figure 7.7 Trust, security, and privacy of edge AI.
Chapter 8
Figure 8.1 Toward intelligent softwarized networks.
Figure 8.2 Service Function Chain (SFC) architecture.
Figure 8.3 In network computing – Application Services are executed in the n...
Chapter 9
Figure 9.1 Edge intelligence with federated learning for personalized health...
Figure 9.2 Three scenarios of energy refills in aerial access networks. (a) ...
Figure 9.3 ARANs in a comprehensive 6G access infrastructure.
Figure 9.4 System architecture of ARANs.
Figure 9.5 Illustration of a three‐tier computing infrastructure, including ...
Figure 9.6 A high‐level illustration of traditional RAN (a) and O‐RAN (b).
Figure 9.7 The high‐level architecture of O‐RAN proposed by the O‐RAN allian...
Chapter 10
Figure 10.1 Evolution of the security landscape in telecommunication network...
Figure 10.2 6G security vision.
Figure 10.3 6G security threat landscape.
Figure 10.4 Key security requirements of prominent 6G applications.
Figure 10.5 Key security vulnerabilities of blockchanized 6G services.
Figure 10.6 Role of quantum computing in 6G.
Figure 10.7 6G security and AI.
Figure 10.8 Illustrative PLS scenarios in 6G era: (a) THz communications in ...
Figure 10.9 Summary of 6G privacy.
Chapter 11
Figure 11.1 5G communication tower in cities.
Figure 11.2 NIB‐enabled mobility architecture.
Figure 11.3 Automation layer architecture.
Figure 11.4 6G RAN network cluster powered by distributed energy sources.
Figure 11.5 A RAN network operations: training and run‐time phases.
Figure 11.6 Under water wireless communication.
Figure 11.7 Network‐coded cooperative mobile edge computing in mobile small ...
Figure 11.8 Secure and energy‐efficient key management [6].
Figure 11.9 Resource management using blockchain.
Figure 11.10 Energy‐efficient self‐sustainability architecture in 6G.
Chapter 12
Figure 12.1 Network convergence of different frequency bands, including, Sub...
Figure 12.2 Network convergence of Sub‐6 GHz, FSO, VLC, and Wi‐Fi in 6G.
Figure 12.3 Illustration of 4C functions provided in edge computing systems....
Figure 12.4 An example of JCAS systems, where a JCAS node transmits a single...
Figure 12.5 A collaborative computation system, where HAP‐edge servers execu...
Figure 12.6 Illustration of HAP/LAP deployment for backhauling solutions in ...
Chapter 13
Figure 13.1 Global 6G Standards.
Chapter 14
Figure 14.1 Blockchain for 6G medical applications.
Chapter 15
Figure 15.1 6G for smart citizen.
Figure 15.2 Applications of 6G for smart transportation.
Figure 15.3 Illustration of 6G use‐cases for smart grid.
Figure 15.4 Applications of 6G for supply chain management.
Chapter 16
Figure 16.1 Illustration of industrial evolution.
Figure 16.2 The core elements of Industry 5.0.
Figure 16.3 The cloud manufacturing ecosystem.
Figure 16.4 Industry 5.0 Technologies.
Chapter 17
Figure 17.1 The Metaverse Concept.
Figure 17.2 6G Communication for Space Tourism.
Guide
Cover Page
Table of Contents
6G Frontiers
Title Page
Copyright
Dedication
About the Authors
Preface
Acknowledgments
Acronyms
Begin Reading
Bibliography
Index
End User License Agreement
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IEEE Press
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Editor in Chief
Jón Atli Benediktsson
Andreas Molisch
Diomidis Spinellis
Anjan Bose
Saeid Nahavandi
Ahmet Murat Tekalp
Adam Drobot
Jeffrey Reed
Peter (Yong) Lian
Thomas Robertazzi
6G Frontiers
Towards Future Wireless Systems
Chamitha de Alwis
University of Bedfordshire
Luton, United Kingdom
and
University of Sri Jayewardenepura
Nugegoda, Sri Lanka
Quoc‐Viet Pham
Pusan National University
Busan, Republic of Korea
Madhusanka Liyanage
University College Dublin
Dublin, Ireland
and
University of Oulu
Oulu, Finland
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To my parents
About the Authors
CHAMITHA DE ALWIS University of Sri Jayewardenepura
Chamitha de Alwis (Senior Member, IEEE) is a Lecturer, Researcher and Consultant in Cybersecurity. Presently he works as a Lecturer in Cybersecurity in the School of Computer Science and Technology, University of Bedfordshire, United Kingdom. He is the founder Head of the Department of Electrical and Electronic Engineering, University of Sri Jayewardenepura, Sri Lanka. He also provides consultancy services for telecommunication‐related projects and activities. He received the BSc degree (First Class Hons.) in Electronic and Telecommunication Engineering from the University of Moratuwa, Sri Lanka, in 2009, and the PhD degree in Electronic Engineering from the University of Surrey, United Kingdom, in 2014. He has published peer‐reviewed journal articles, conference papers, and book chapters, and delivered tutorials and presentations in international conferences. He also has contributed to various projects related to ICT, and served as a guest editor, reviewer, and TPC member in international journals and conferences. He has also worked as a Consultant to the Telecommunication Regulatory Commission of Sri Lanka, an Advisor in IT Services in the University of Surrey, United Kingdom, and a Radio Network Planning and Optimization Engineer in Mobitel, Sri Lanka. His research interests include network security, 5G/6G, blockchain, and IoT.
QUOC-VIET PHAM Pusan National University
Quoc‐Viet Pham (Member, IEEE) received the BS degree in Electronics and Telecommunications Engineering from the Hanoi University of Science and Technology, Vietnam, in 2013, and the MS and PhD degrees in Telecommunications Engineering from Inje University, South Korea, in 2015 and 2017, respectively. From September 2017 to December 2019, he was with Kyung Hee University, Changwon National University, and Inje University, in various academic positions. He is currently a Research Professor with Pusan National University, South Korea. He has been granted the Korea NRF Funding for outstanding young researchers for the term 2019–2023. His research interests include convex optimization, game theory, and machine learning to analyze and optimize edge/cloud computing systems and future wireless systems. He received the Best PhD Dissertation Award in Engineering from Inje University, in 2017. He received the top reviewer award from the IEEE Transactions on Vehicular Technology in 2020. He is an editor of the Journal of Network and Computer Applications (Elsevier), an associate editor of the Frontiers in Communications and Networks, and the lead guest editor of the IEEE Internet of Things Journal.
MADHUSANKA LIYANAGE is currently an Assistant Professor/Ad Astra Fellow and Director of Graduate Research at the School of Computer Science, University College Dublin, Ireland. He is also acting as a Docent/Adjunct Professor at the Center for Wireless Communications, University of Oulu, Finland, and Honorary Adjunct Professor of Network Security, The Department of Electrical and Information Engineering, University of Ruhuna, Sri Lanka. He received his Doctor of Technology degree from the University of Oulu, Finland, in 2016. He was also a recipient of the prestigious Marie Skłodowska‐Curie Actions Individual Fellowship during 2018–2020. During 2015–2018, he had been a Visiting Research Fellow at the CSIRO, Australia, the Infolabs21, Lancaster University, United Kingdom, Computer Science and Engineering, The University of New South Wales, Australia, School of IT, University of Sydney, Australia, LIP6, Sorbonne University, France and Computer Science and Engineering, The University of Oxford, United Kingdom. He is also a senior member of IEEE. In 2020, he received the “2020 IEEE ComSoc Outstanding Young Researcher” award by IEEE ComSoc EMEA. Dr. Liyanage is an expert consultant at the European Union Agency for Cybersecurity (ENISA). In 2021, Liyanage was elevated as Funded Investigator of Science Foundation Ireland CONNECT Research Centre, Ireland. He was ranked among the World's Top 2% Scientists (2020) in the List prepared by Elsevier BV, Stanford University, USA. Also, he was awarded an Irish Research Council (IRC) Research Ally Prize as part of the IRC Researcher of the Year 2021 awards for the positive impact he has made as a supervisor. Moreover, he is an expert reviewer at different funding agencies in France, Qatar, UAE, Sri Lanka, and Kazakhstan. More info: www.madhusanka.com
Preface
While the fifth‐generation (5G) mobile communication networks are deployed worldwide, multitude of new applications and use cases driven by current trends are already being conceived, which challenges the capabilities of 5G. This has motivated academic and industrial researchers to rethink and work toward the next generation of mobile communication networks called 6G hereafter. 6G networks are expected to mark a disruptive transformation to the mobile networking paradigm by reaching extreme network capabilities to cater to the demands of the future data‐driven society.
Recent developments in communications have introduced many new concepts such as edge intelligence, beyond sub 6, GHz to THz communication, nonorthogonal multiple access, large intelligent surfaces, and self‐sustaining networks. These concepts are evolving to become full‐fledged technologies that can power future generations of communication networks. On the other hand, applications such as holographic telepresence, extended reality, smart grid 2.0, and Industry 5.0 are expected to emerge as mainstream applications of future communication networks. However, requirements of these applications such as ultra‐high data rates, real‐time access to powerful computing resources, extremely low latency, precision localization and sensing, and extremely high reliability and availability surpass the network capabilities promised by 5G. IoT, which is enabled by 5G, is even growing to become Internet of Everything (IoE) that intends to connect massive numbers of sensors, devices, and cyber‐physical systems beyond the capabilities of 5G. This has inspired the research community to envision 6G mobile communication networks. 6G is expected to harness the developments of new communication technologies, fully support emerging applications, connect a massive number of devices, and provide real‐time access to powerful computational and storage resources.
6G mobile networks are expected to provide extreme peak data rates over 1, Tbps. The end‐to‐end delays will be imperceptible and lie even beneath 0.1, ms. 6G networks will provide access to powerful edge intelligence that has processing delays falling below 10, ns. Network availability and reliability are expected to go beyond 99.99999%. An extremely high connection density of over 107 devices/ per km2 is expected to be supported to facilitate IoE. The spectrum efficiency of 6G will be over 5× than 5G, while support for extreme mobility up to 1000, kmph is expected. It is also envisioned that the evolution of 6G will focus around a myriad of new requirements such as Further‐enhanced Mobile Broadband (FeMBB), ultra‐massive Machine‐Type Communication (umMTC), Mobile BroadBand and Low‐Latency (MBBLL), and massive Low‐Latency Machine Type communication (mLLMT). These requirements will be enabled through emerging technologies such as THz spectrum, federated learning, edge artificial intelligence (AI), compressive sensing, blockchain, and 3D networking. Moreover, 6G will facilitate emerging applications such as unmanned aerial vehices (UAVs), holographic telepresence, IoE, Industry 5.0, and collaborative autonomous driving. In light of this vision, many new research work and projects are themed toward developing the 6G vision, technologies, use cases, applications, and standards. The vision for 6G is envisaged to be framed by 2022–2023 to set forth the 6G requirements and evaluate the 6G development, technologies, standards, etc.
In order to further provide a full understanding of 6G frontiers and boost the research and development of 6G, we are motivated to provide an authored book on 6G, future wireless systems. To the best of our knowledge, this book covers all the aspects of 6G. In the first part of this book, we present the evolution of mobile networks, from 0G to 6G, which are followed by the introduction to driving trends, requirements, and key‐enabling technologies. In the second part, we present potential architectural directions of 6G, including zero‐touch network and service management, intent‐based networking, edge AI, intelligent network softwarization, and radio access networks. Then, the technical aspects of 6G are discussed in detail. In particular, we focus on (i) hyper‐intelligent networking, (ii) security and privacy, trust, (iii) energy management and resource allocation, (iv) harmonized mobile networks, and (v) legal aspects and standardization. In the final part of this work, we focus on vertical applications which are expected to emerge in future 6G network systems. More specifically, we focus on four main kinds of applications, including (i) healthcare/well‐being, (ii) smart cities, (iii) industrial automation (e.g. Industry 5.0. collaborative robots, and digital twin), and (iv) wild applications (e.g. space tourism and deep sea tourism).
Intended Audience
This books will be of key interest for
Researchers
: Developing 6G enabling technologies is already at the forefront of today's communications research. This book will provide a clear idea on how different technologies will mature toward developing the 6g framework.
Academics
: Academics who are teaching and performing research work in the area of emerging communication technologies are in need of a textbook on the envisaged 6G technologies and framework, which is provided through this book.
Technology Architects
: Technology architects need to envision 6G and develop and align technologies toward realizing 6G.
Mobile Network Operators
(
MNOs
): MNOs require knowledge on 6G in order to plan their future work considering 6G technologies, framework, applications, and use cases as discussed in this book.
Industry Experts
: Industry experts are expected to envision future applications and use cases and develop businesses and invest accordingly.
Regulators and Standards
: Regulators and Standards institutions are required to be aware of the forthcoming technologies and applications in order to set regulations and standards.
Book Organization
This book begins with introducing the concept of 6G mobile communication networks in Chapter 1. Subsequently, the key driving trends toward 6G mobile networks are explained in Chapter 2. Then 6G requirements, including the vision for 6G together with enabling 6G applications and technologies, are discussed in Chapter 3. Chapter 4 explains the key 6G technologies, while Chapter 5 introduces 6G architectural visions. Zero‐Touch Network and Service Management is explained in Chapter 6. Chapter 7 elaborates Edge AI, while Chapter 8 discusses intelligent network softwarization with 6G. Chapter 9 explains 6G radio access technologies. Security and privacy aspects of 6G are discussed in Chapter 10, while Chapter 11 discusses about resource efficient 6G networks. Chapter 12 elaborates how 6G will be deployed as harmonized mobile networks to provide extreme global coverage. Chapter 13 discusses 6G standardization efforts and legal aspects. Chapters 14, 15, and 16 explain emerging directions for 6G applications in healthcare, smart cities, and industrial automation. Chapter 17 provides insights on some wild 6G applications that are expected to emerge in the coming decade. Chapter 18 concludes this book.
Nugegoda, Sri Lanka Chamitha de Alwis
Dublin, Ireland Madhusanka Liyanage
South Korea Quoc‐ Viet Pham
Acknowledgments
This book would not have been possible without the great help and support of many. The concept of publishing this book to facilitate 6G‐related studies, research, development, and standardization came to light during our research work in projects such as STHRD R1/SJ/01 Project, University of Sri Jayewardenepura ASP/01/RE/ENG/2022/85 Research Project, Korea NRF‐2019R1C1C1006143, and Science Foundation Ireland under Connect Center (13/RC/2077_P2) Project, the Academy of Finland under 6Genesis Flagship (Grant 318927) project and European Commission under H2020 SPATIAL project (Grant 101021808). We would also like to acknowledge all the partners of those projects. Furthermore, we would like to thank our universities, University of Sri Jayewardenepura, Pusan National University, and University College Dublin, for all the support extended toward the successful completion of this book. We would also like to thank chapter contributors, including Dr. Pardeep Kumar, Dr. Thippa Reddy Gadekallu, Dr. Sweta Bhattacharya, Dr. Praveen Kumar Reddy Maddikunta for their invaluable contribution to complete this book. We also thank all the reviewers for helping us select suitable chapters for this book. We are also grateful to Sandra Grayson, Teresa Netzler, and the whole John Wiley & Sons team for their support toward getting this book published.
Last but not least, we would offer our heartiest gratitude to our families, who gladly allowed us to share our time with them toward the completion of this book.
Chamitha de Alwis
Quoc‐Viet Pham
Madhusanka Liyanage
C. V. M.
Acronyms
ASTA
Arrivals See Time Averages
BHCA
Busy Hour Call Attempts
BR
Bandwidth Reservation
b.u.
bandwidth unit(s)
CAC
Call / Connection Admission Control
CBP
Call Blocking Probability(‐ies)
CCS
Centum Call Seconds
CDTM
Connection Dependent Threshold Model
CS
Complete Sharing
DiffServ
Differentiated Services
EMLM
Erlang Multirate Loss Model
erl
The Erlang unit of traffic‐load
FIFO
First in ‐ First out
GB
Global balance
GoS
Grade of Service
ICT
Information and Communication Technology
IntServ
Integrated Services
IP
Internet Protocol
ITU‐T
International Telecommunication Unit–Standardization sector
LB
Local balance
LHS
Left hand side
LIFO
Last in ‐ First out
MMPP
Markov Modulated Poisson Process
MPLS
Multiple Protocol Labeling Switching
MRM
Multiretry Model
MTM
Multithreshold Model
PASTA
Poisson Arrivals See Time Averages
Probability Distribution Function
probability density function
PFS
Product Form Solution
QoS
Quality of Service
r.v.
random variable(s)
RED
random early detection
RHS
Right hand side
RLA
Reduced Load Approximation
SIRO
service in random order
SRM
Single‐Retry Model
STM
Single‐Threshold Model
TCP
Transport Control Protocol
TH
Threshold(s)
UDP
User Datagram Protocol
3GPP
3rd Generation Partnership Project
A2G
Air‐to‐Ground
AEC
AI‐assistive Extreme Communications
AI
Artificial Intelligence
AR
Augmented Reality
AV
Autonomous Vehicles
BAN
Body Area Network
BCI
Brain Computer Interface
CAV
Connected Autonomous Vehicles
CPS
Cyber‐Physical Systems
CS
Compressive Sensing
D2D
Device‐to‐Device
DLT
Distributed Ledger Technologies
DRL
Deep Reinforcement Learning
EI
Edge Intelligence
ELPC
Extremely Low‐Power Communication
ETSI
European Telecommunications Standards Institute
eMBB
enhanced‐Mobile Broadband
eMTC
enhanced Machine Type Communication
eRLLC
extremely Reliable Low‐Latency Communication
FeMBB
Further‐enhanced Mobile Broadband
FL
Federated Learning
H2H
Hospital‐to‐Home
HCS
Human‐Centric Services
HT
Holographic Telepresence
IoBNT
Internet of Bio‐NanoThings
IIoMT
Intelligent Internet of Medical Things
IIosT
Internet of Industrial smart Things
IIoT
Industrial Internet of Things
IoE
Internet of Everything
IoH
Internet of Healthcare
IoNT
Internet of Nano‐Things
IoT
Internet of Things
IoV
Internet of Vehicles
IP
Internet Protocol
ITU
International Telecommunication Union
IRS
Intelligent Reflecting Surface
ITS
Intelligent Transport System
IWD
Intelligent Wearable Devices
KPI
Key Performance Indicator
LDHMC
Long Distance and High Mobility Communications
LED
Light Emitting Diodes
LIS
Large Intelligent Surfaces
LSTM
Long Short Term Memory
LTE
Long‐Term Evolution
MBBLL
Mobile BroadBand and Low‐Latency
mBBMT
massive Broadband Machine Type
MEC
Multiaccess Edge Computing
mHealth
mobile Health
MIMO
Multiple‐Input and Multiple‐Output
ML
Machine Learning
mLLMT
massive Low‐Latency Machine Type
MMS
Multimedia Message Services
mMTC
massive Machine Type Communication
MR
Mixed Reality
MTC
Machine Type Communication
MTP
Motion‐To‐Photon
NB‐IoT
Narrowband Internet of Things
NOMA
Non‐Orthogonal Multiple Access
NTN
Nonterrestrial Networks
QoL
Quality of Life
QoPE
Quality‐of‐Physical‐Experience
RF
Radio Frequency
RIS
Reconfigurable Intelligent Surface
SAGINs
Snetworks, and space‐Air‐Ground Interconnected Networks
SDN
Software Defined Networking
SDO
Standards Developing Organizations
SMS
Short Message Services
SSN
Self‐Sustaining Networks
U2X
UAV‐to‐Everything
UAV
Unmanned Aerial Vehicles
UHD
Ultra High Definition
umMTC
ultra‐massive Machine‐Type Communication
uRLLC
ultra‐Reliable Low Latency Communication
VANET
Vehicular Ad Hoc Networks
VoIP
Voice Over IP
VR
Virtual Reality
VLC
Visible Light Communincaiton
XR
Extended Reality
RPL
Low‐Power and Lossy Networks
ZSM
Zero touch network and Service Management
Part IIntroduction
1Evolution of Mobile Networks
Mobile networks have been evolving since the 1980s, resulting in a new generation of mobile network every decade. Presently, fifth‐generation (5G) mobile networks are being deployed. However, mobile communication research and development work suggest that we can expect to see sixth‐generation (6G) mobile networks by 2030. After reading this chapter, you should be able to
Explain the evolution of mobile networks from 0G to 6G.
Understand the present context of 6G development.
1.1 Introduction
While fifth‐generation (5G) mobile communication networks are deployed worldwide, multitude of new applications and use‐cases driven by current trends are already being conceived, which challenges the capabilities of 5G. This has motivated researchers to rethink and work toward the next‐generation mobile communication networks “hereafter 6G” [1, 2]. The sixth‐generation (6G) mobile communication networks are expected to mark a disruptive transformation to the mobile networking paradigm by reaching extreme network capabilities to cater to the demands of the future data‐driven society.
So far mobile networks have evolved through five generations during the last four decades. A new generation of mobile networks emerges every ten years, packing more technologies and capabilities to empower humans to enhance their work and lifestyle. The precellphone era before the 1980s is marked as the zeroth‐generation (0G) of mobile communication networks that provided simple radio communication functionality with devices such as walkie‐talkies [3]. The first‐generation (1G) introduced publicly and commercially available cellular networks in the 1980s. These networks provided voice communication using analog mobile technology [4]. The second‐generation (2G) of mobile communication networks marked the transition of mobile networks from analog to digital. It supported basic data services such as short message services in addition to voice communication [5]. The third‐generation (3G) introduced improved mobile broadband services and enabled new applications such as multimedia message services, video calls, and mobile TV [6]. Further improved mobile broadband services, all‐IP communication, Voice Over IP (VoIP), ultrahigh definition video streaming, and online gaming were introduced in the fourth‐generation (4G) [7].
The 5G mobile communication networks are already being deployed worldwide. 5G supports enhanced Mobile Broadband (eMBB) to deliver peak data rates up to 10 Gbps. Furthermore, ultra‐Reliable Low Latency Communication (uRLLC) minimizes the delays up to 1 ms while massive Machine Type Communication (mMTC) supports over 100 more devices per unit area compared to 4G. The expected network reliability and availability is over 99.999% [8]. Network softwarization is a prominent 5G technology that enables dynamicity, programmability, and abstraction of networks [9]. Capabilities of 5G have enabled novel applications such as Virtual Reality (VR), Augmented Reality (AR), Mixed Reality (MR), autonomous vehicles, Internet of Things (IoT), and Industry 4.0 [10, 11].
Recent developments in communications have introduced many new concepts such as Edge Intelligence (EI), beyond sub 6 GHz to THz communication, Nonorthogonal Multiple Access (NOMA), Large Intelligent Surfaces (LIS), swarm networks, and Self‐Sustaining Networks (SSN) [12, 13]. These concepts are evolving to become fully fledged technologies that can power future generations of communication networks. On the other hand, applications such as Holographic Telepresence (HT), Unmanned Aerial Vehicles (UAV), Extended Reality (XR), smart grid 2.0, Industry 5.0, and space and deep‐sea tourism are expected to emerge as mainstream applications of future communication networks. However, requirements of these applications such as ultrahigh data rates, real‐time access to powerful computing resources, extremely low latency, precision localization and sensing, and extremely high reliability and availability surpass the network capabilities promised by 5G [14, 15]. IoT, which is enabled by 5G, is even growing to become Internet of Everything (IoE) that intends to connect massive numbers of sensors, devices, and Cyber‐Physical Systems (CPS) beyond the capabilities of 5G. This has inspired the research community to envision 6G mobile communication networks. The 6G is expected to harness the developments of new communication technologies, fully support emerging applications, connect a massive number of devices, and provide real‐time access to powerful computational and storage resources.
1.2 6G Mobile Communication Networks
The 6G networks are expected to be more capable, intelligent, reliable, scalable, and power‐efficient to satisfy all the expectations that cannot be realized with 5G. The 6G is also required to meet any new requirements, such as support for new technologies, applications, and regulations, raised in the coming decade. Figure 1.1 illustrates the evolution of mobile networks, elaborating key features of each mobile network generation. Envisaged 6G requirements, vision, enablers, and applications are also highlighted to formulate an overview of the present understanding of 6G.
1.2.1 6G as Envisioned Today
The 6G mobile communication networks, as envisioned today, are expected to provide extreme peak data rates over 1 Tbps. The end‐to‐end delays will be imperceptible and lie even beneath 0.1 ms. The 6G networks will provide access to powerful edge intelligence that has processing delays falling below 10 ns. Network availability and reliability are expected to go beyond 99.99999%. An extremely high connection density of over devices/ is expected to be supported to facilitate IoE. The spectrum efficiency of 6G will be over 5 than 5G, while support for extreme mobility up to 1000 kmph is expected [12].
It is envisioned that the evolution of 6G will focus around a myriad of new requirements such as further‐enhanced mobile broadband (FeMBB), ultramassive Machine‐Type Communication (umMTC), Mobile BroadBand and Low‐Latency (MBBLL), and massive Low‐Latency Machine Type communication (mLLMT). These requirements will be enabled through emerging technologies such as THz spectrum, Federated Learning (FL), edge Artificial Intelligence (AI), Compressive Sensing (CS), blockchain/Distributed Ledger Technologies (DLT), and 3D networking. Moreover, 6G will facilitate emerging applications such as UAVs, HT, IoE, Industry 5.0, and collaborative autonomous driving. In light of this vision, many new research work and projects are themed toward developing 6G vision, technologies, use‐cases, applications, and standards [1, 2].
Figure 1.1 Evolution of Mobile Networks from 0G to 6G. Source: vectorplus / Adobe Stock.
1.2.2 6G Development Timeline
The 6G developments are expected to progress along with the deployment and commercialization of 5G networks, and the final developments of 4G Long‐Term Evolution (LTE), being LTE‐C, which followed LTE‐Advanced and LTE‐B [16]. The vision for 6G is envisaged to be framed by 2022–2023 to set forth the 6G requirements and evaluate the 6G development, technologies, standards, etc. Standardization bodies such as the International Telecommunication Union (ITU) and Third‐Generation Partnership Project (3GPP) are expected to develop the specifications to develop 6G by 2026–2027 [16]. Network operators will start 6G research and development (R&D) work by this time to do 6G network trials by 2028–2029, to launch 6G communication networks by 2030 [14, 16–18]. Global 6G development initiatives are illustrated in Figure 1.3, while the expected timeline for 6G development, standardization, and launch is presented in Figure 1.2.
Figure 1.2 Expected Timeline of 6G Development, Standardization and Launch.
Source: Adapted from [14, 16–18]
.
Figure 1.3 Global 6G Development Initiatives.
2Key Driving Trends Toward 6G
Emerging applications and use‐cases of the future society demands mobile networks to be more dense and capable. After reading this chapter, you should be able to
Understand the future trends of 6G networks.
Importance of the driving trend toward the development and definition of the requirements of 6G network.
Identify components related to environmental and energy infrastructure.
2.1 Introduction
A new generation of mobile communication has emerged every 10 years over the last four decades to cater to society's growing technological and societal needs. This trend is expected to continue, and 6G is seen on the horizon to meet the requirements of the 2030 society [19, 20]. The technologies, trends, requirements, and expectations that force the shift from 5G toward the next generation of networks are identified as 6G driving trends. These driving trends will shape 6G into the key enabler of a more connected and capable 2030 society.
This chapter discusses the key 6G driving trends elaborating why and how each trend demands a new generation of communication networks. Figure 2.1 illustrates the 6G driving trends that are discussed in this section.
Expansion of IoTs
: It is expected that the number of IoT devices in the world will grow up to 24 billion by 2030. Moreover, the revenue related to IoT will hit the market capitalization of USD 1.5 trillion by 2030 [
23
].
Massive Availability of Small Data
: Due to the anticipated popularity of 6G‐based IoT devices and new 6G‐IoT services, 6G networks will trend to generate an increasingly high volume of data. Most of such data will be small, dynamic, and heterogeneous in nature [
12
,
24
].
Availability of Self‐Sustained Networks
: 6G mobile systems need to be energy self‐sustainable, both at the infrastructure side and at the device side, to provide uninterrupted connectivity in every corner of the world. The development of energy harvesting capabilities will extend the life cycle of both network infrastructure devices and end devices such as IoE devices [
25
,
26
].
Convergence of Communication, Sensing, Control, Localization, and Computing
: Development of sensor technologies and direct integration of them with mobile networks accompanied by low‐energy communication capabilities will lead to advanced 6G networks [
12
,
27
]. Such a network will be able to provide sensing and localization services in addition to the exciting communication and computing features [
12
,
27
,
28
].
Zero Energy IoT
: Generally, IoT devices will consume significantly more energy for communication than sensing and processing [
29
]. The development of ultralow‐power communication mechanisms and efficient energy harvesting mechanisms will lead to self‐energy sustainable or zero‐energy IoT devices [
29
].
More Bits, Spectrum, and Reliability
: The advancement of wireless communication technologies, including coding schemes and antenna technologies, will allow to utilize new spectrum as well as reliably send more information bits over existing wireless channels [
12
,
19
].
Gadget‐Free Communication
: The integration of an increasing number of smart and intelligent devices and digital interfaces in the environment will lead to a change from gadget‐centric to user‐centric or gadget‐free communication model. The hyperconnected digital surroundings will form an “omnipotential”atmosphere around the user, providing all the information, tools, and services that a user needs in his or her everyday life [
30
–
32
].
Increasing Elderly Population
: Due to factors such as advanced healthcare facilities and the development of new medicines, the world's older population continues to grow at an unprecedented rate. According to the “An Aging World: 2015” Report, nearly 17 percent (1.6 billion) of the world's population will be aged 65 and over by 2050 [
22
].
Emergence of New Technologies
: By 2030, the world will experience new technological advancements such as stand‐alone cars,
Artificial Intelligence
(
AI
)‐powered automated devices, smart clothes, printed bodies in 3D, humanoid robots, smart grid 2.0, industry 5.0, and space travel [
12
,
19
]. The 6G will be the main underline communication infrastructure to realize these technologies.
Figure 2.1 6G Driving Trends.
Source: [21, 22]/IEEE.
2.2 Expansion of IoT toward IoE
IoT envisions to weave a global network of machines and devices that are capable of interacting with each other [33]. The number of IoT devices is on the rise and is expected to grow up to 24 billion by 2030 due to the growth of applications such as the Industrial Internet of Things (IIoT). The total IoT market is also expected to rise to USD 1.5 trillion in 2030 [23]. IoE is expected to expand the scope of IoT to form a hyperconnected world connecting people, data, and things to streamline the processes of businesses and industries while enriching human lives [34]. IoE will connect many ecosystems involving heterogeneous sensors, actuators, user equipment, data types, services, and applications [35].
The importance of this driving trend is discussed, considering the challenges in overcoming the limitations of existing networks to facilitate IoT development toward IoE. One of the key challenges in this development is the integration of AI and Machine Learning (ML) technologies into mobile communication networks [36]. These technologies are essential to process massive amounts of data collected from heterogeneous IoE devices to obtain meaningful information and enable new applications and use‐cases envisioned with 6G [37]. Processing massive amounts of data using AI and ML requires future communication networks to provide real‐time access to powerful computational facilities (Figure 2.2). The communication between IoE devices and mobile networks should also be power‐efficient to minimize the carbon footprint. For instance, intelligent traffic control and transportation systems in future smart cities are expected to utilize future 6G communication networks to massively exploit data‐driven methods for real‐time optimization [38]. Such systems will require AI and ML to efficiently process large amounts of data collected from heterogeneous sensors in real‐time to provide insights that will minimize traffic.
Preserving data security and privacy in existing IoT networks is yet another important requirement. Since everything in IoE is connected to the Internet, distributed AI technologies will be required for training data sets spread unevenly across multiple edge devices. This exposes IoE networks to security vulnerabilities associated with distributed AI, such as poisoning attacks and authentication issues [39]. Solving these issues requires AI and DLT‐based adaptive security solutions that should be integrated with future communication networks [40]. DLTs and blockchain, in particular, are key enablers of IoE. The decentralized operation, immutability, and enhanced security of blockchain are instrumental in overcoming the challenges concerned with the exponential expansion of IoT [41].
Figure 2.2 IoT to IoE Transition.
Moreover, traditional Orthogonal Multiple Access (OMA)‐based schemes cannot provide access to a massive number of IoE devices due to limitations in the radio spectrum. This requires new technologies such as NOMA to be applied to cellular IoT to provide access to a massive number of IoT devices [13, 36]. In addition, providing seamless connectivity to IoE devices that lie beyond the coverage of terrestrial cellular networks requires unmanned aerial vehicle (UAV) and satellites to work in coordination to form a cognitive satellite‐UAV network [42]. Such technologies are expected to be integrated with the next generation of mobile communication networks to facilitate the smooth progression from IoT toward IoE.
2.3 Massive Availability of Small Data
The widespread heterogeneous IoT sensor nodes that continuously acquire massive amounts of diverse data are expected to generate over 30 exabytes of data per month by 2020 [43]. Collecting, storing, and processing this type of data through widespread communication networks will be one of the challenging requirements that should be met by future communication networks. The term “Small Data” refers to small data sets representing a limited pool of data in a niche area of interest [44]. Such data sets can provide meaningful insights to manage massive amounts of IoT devices. Unlike Big Data that are concerned with large sets of historical data, Small Data are concerned about either real‐time data or statistical data of a limited time. Small Data will be instrumental in many applications, including the real‐time equipment operation and the maintenance of massive numbers of machines connected in IIoT. IIoT is expected to grow connecting billions of CPS, devices, and sensors in the coming decade as discussed in Section 2.2.
Another example is the growing demand for Small Data‐based analytics in the retail industry that collects data from various sensors, personal wearables, and IoT devices [45]. Such analytics are helpful to provide real‐time personalized services for customers. These applications give rise to the generation of massive amounts of small data sets that should be efficiently collected and processed using AI and ML [12].
The importance of this driving trend is discussed, considering the processing and communication limitations of existing mobile communication networks. Processing massive amounts of Small Data sets is not efficient in existing cloud computing and edge computing infrastructure that is designed to process large data sets [46]. This requires new means of efficiently processing massive amounts of Small Data sets in the Edge AI infrastructure in future communication networks. This will also require new ML techniques beyond classical, big data analytics to enhance network functions and provide new services envisaged in future communication networks [12]. Furthermore, future networks should maximize the energy efficiency of offloading massive amounts of Small Data to edge computing facilities. This requires the optimization of joint radio and computation resources while satisfying the maximum tolerable delay constraints [47].
On the other hand, communication networks will need to support massive amounts of Small Data transmission from heterogeneous IoT devices. Overheads of this type of communication can be significant compared to the size of data that is being transmitted, making this type of data communication less efficient [24, 48]. This requires new methods to reduce transmission and contention overheads in future communication networks.
2.4 Availability of Self‐Sustaining Networks
Self‐Sustaining Networks (SSNs) can perform tasks such as self‐managing, self‐planning, self‐organizing, self‐optimizing, self‐healing, and self‐protecting network resources to continuously maintain its Key Performance Indicators (KPIs) [12]. This is performed by adapting network operation and functionalities considering various facts, including environmental status, network usage, and energy constraints [49]. These types of intelligent and real‐time network operations in SSNs are facilitated using machine learning/deep learning/quantum machine learning techniques that enable fast learning of rapid network changes and dynamic user requirements [50]. Using SSNs, future networks are expected to enable seamless access to emerging application domains under highly dynamic and complex environments [12].
The importance of this driving trend is discussed, considering the incapability of existing mobile networks to function as SSNs. SSNs require the ability to obtain network statistics in real time to automatically manage resources and adapt functionalities to maintain high KPIs [12]. Therefore, SSNs require a novel self‐sustaining network architecture that can adapt to rapid changes in the environment and user requirements. These operations should be facilitated through real‐time analysis of massive amounts of Small Data obtained by network nodes. Small Data analysis can be performed using edge intelligence capabilities envisaged in future networks, as explained in Section 2.3.
Furthermore, self‐optimization of radio resources needs to bank on software‐defined cognitive radios through operations such as radio scene analysis [50, 51]. In addition, SSNs should facilitate energy self‐sustainability at the infrastructure side as well as the device side to provide uninterrupted and seamless connectivity. Therefore, energy harvesting in network infrastructure should play a pivotal role to extend the range and stand‐by times [25, 26]. This also requires future communication networks to be designed in an energy‐aware fashion to enable devices to harvest energy, be self‐powered, share power, and last long [17, 52]. Furthermore, handling massive numbers of IoT devices in an energy‐efficient manner under various channel conditions and diverse applications requires self‐learning through context‐aware operation to minimize the energy per bit for a given communication requirement [43].
2.5 Convergence of Communications, Computing, Control, Localization, and Sensing (3CLS)
Future communication networks are expected to converge computing resources, controlling architecture, and other infrastructure used for precise localization and sensing [12]. This convergence is essential to facilitate highly personalized and time‐critical future applications. For instance, Human‐Centric Services (HCS) are expected to bank on 3CLS services to facilitate efficient communication and real‐time processing of a large number of data streams gathered through sensors that are centered around humans [53, 54].
The development of 3CLS services is an important driving trend toward the next generation of mobile communication networks as existing 5G technologies have not fully explored the interdependence between computing, communication, control, localization, and sensing in an end‐to‐end manner [55]. Realizing 3CLS services will require future mobile communication networks to possess collective network intelligence at the edge of the network to run AI and ML algorithms in real time [12, 56]. Moreover, the network architecture should also be open, scalable, and elastic to facilitate AI orchestrated end‐to‐end 3CLS design services [12, 57]. Precise localization and sensing should also coexist with communication networks by sharing network resources in time, frequency, and space to facilitate emerging applications such as extended reality, connected robotics, connected and automated vehicles (CAVs), sensing, and 3D mapping [12, 28].
2.6 Zero Energy IoT
Zero energy IoT devices can harvest energy from the environment to obtain infinite power [58]. For instance, radio frequency (RF) energy harvesting can harvest energy from RF waves to extend the network lifetime. Nodes that harvest more energy can share their energy with other nodes using energy cooperation. Presently, only about 0.6% of the 1.5 trillion objects in the real world is connected to the Internet [29]. The remaining devices are also expected to be connected in an energy‐efficient fashion together with the growth of future communication technologies and applications.
Zero energy IoT is an important driving trend toward future communication networks to enable maintenance‐free and battery‐less operation of a massive number of IoT devices. This requires mobile networks to be able to support ultralow‐power communication and efficient energy harvesting [29]. However, existing 5G network infrastructures do not support energy harvesting, especially as the electronic circuitry cannot efficiently convert the harvested energy into electric current [17]. Therefore, electronic circuitry in future communication networks should be designed and developed to support efficient energy harvesting. Furthermore, circuits that harvest energy should allow devices to be self‐powered to enable off‐grid operations, long‐lasting IoT devices, and longer stand‐by times [17]. Wireless power transfer is also expected to play a key role in the next generation of mobile communication networks considering the feasibility of doing so due to much shorter communication distances in denser communication networks [59]. Furthermore, data communication stacks can also be optimized in an energy‐aware fashion to minimize energy usage.
2.7 Advancement of Communication Technologies
Mobile communication has seen significant technological advances recently. For instance, electromagnetically active Large Intelligent Surfaces (LIS) made using meta‐materials placed in walls, roads, buildings, and other smart environments with integrated electronics will provide massive surfaces for wireless communication [60]. Furthermore, novel channel access schemes such as NOMA have offered many advantages, such as being more spectral efficient than prevailing schemes. Beyond‐millimeter Wave (mmWave) communication at THz frequency bands is also being exploited to provide uninterrupted connectivity in local and wide‐area networks [61]. Key advancements of communication technologies are illustrated in Figure 2.3.
The emergence of new communication technologies that cannot be integrated with existing 5G networks is discussed to highlight the importance of this driving trend. For instance, future communication networks will need to shift from existing small cells toward tiny cells to support high‐frequency bands in the THz spectrum. This requires a new architectural design supporting denser network deployments and mobility management at higher frequencies [61]. Furthermore, multimode base stations will be necessary to facilitate networks to operate in a wide range of spectra ranging from microwave to THz to provide uninterrupted connectivity. Furthermore, utilizing LISs as transceivers requires low‐complexity channel demodulation banking on techniques such as joint compressive sensing (CS) and deep learning, which is not feasible with 5G [63]. Also, none of the recent advancements in communication technologies such as providing AI‐powered network functionalities using collective network intelligence, Visible Light Communication (VLC), NOMA, cell‐free networks, and quantum computing and communications are realized in 5G [12, 62, 64]. Therefore, the integration of these advanced communication technologies demands a new paradigm of mobile communication networks.
Figure 2.3 Advancement of communication technologies toward 6G.
Source: Adapted from [12, 60–62]
2.8 Gadget‐Free Communication
Gadget‐free communication eliminates the requirement for a user to hold physical communication devices. It is envisaged that the digital services centered around smart and connected gadgets will move toward a user‐centric, gadget‐free communication model as more and more digital interfaces, intelligent devices, and sensors get integrated to the environment [30, 32, 65]. Since most of our data and services are already based on cloud platforms, the move toward a ubiquitous gadget‐free environment seems to be the natural progression. The hyperconnected smart digital surroundings will provide an omnipotential environment around the user to provide all the digital services needed in their everyday life. Hence, in the future, any user can live naked, i.e. users can access Internet‐based services without any personal devices, gadgets, or wearables [31].
The limitations of present 5G network technologies to facilitate gadget‐free communication also highlights it as an essential driving trend toward the next generation of networks. Gadget‐free communication requires users to stay connected seamlessly with high availability, high‐network performance, increased energy efficiency, and lower costs (Figure 2.4). Future communication networks need to be highly automated, context‐aware, adaptable, flexible, secure, and self‐configurable to provide users with a satisfactory service [31]. Facilitating such requirements demands future communication networks be equipped with powerful distributed computing with edge intelligence, which is lacking in present 5G implementation [56]. Future networks are also required to facilitate extreme data rates, negligible latencies, and extreme reliability to facilitate holographic communication that will enable users to fully utilize the potential of gadget‐free communication [66]. Furthermore, existing network security measures and privacy also need to be improved. For instance efficient, secure, and privacy, ensuring authentication mechanisms using lightweight operations are required to be integrated with future communication networks to facilitate gadget‐free communication [67].
Figure 2.4 Gadget‐free Communication.
2.9 Increasing Elderly Population
The world's older population continues to grow exponentially due to advance healthcare facilities, life prospects, and access to new medicine and healthcare facilities. Presently, there are more 60‐year‐olds than children under the age of five, and this trend is expected to grow [21]. The World Health Organization (WHO) in 2015 has also predicted that the elderly populations will double from 12% to 22% by 2050 [22]. The elderly population is prone to old‐age diseases. Thus, they need continuous health monitoring to ensure well‐being. However, frequent hospital visits might not be feasible due to costs, transportation difficulties, and body movement restrictions. This requires technologies to aid physicians to manage their patients in real time while measuring parameters such as heart rate, body and skin temperature, blood pressure, respiration rate, and physical activity using multiple wearable devices and environmental sensors [68]. Concepts such as Human Bond Communication (HBC) are developed to detect and transmit information using all five human senses (sight, smell, sound, touch, and taste) [21]. Ambient‐Assisted Living (AAL) is another developing concept that will allow remote monitoring of health as well as other hazards such as smoke or fire [69].
The importance of increasing the elderly population as an emerging trend is identified considering the limitations of existing network infrastructure to provide smart healthcare and other related facilities to the increasing elderly population. It is observed that the requirements of future healthcare applications can extend up to very high data rates, extremely high reliability (99.99999%), and extremely low end‐to‐end delays (1 ms) [17, 70]. Furthermore, emerging applications such as the Intelligent Internet of Medical Things (IIoMT) require powerful edge intelligence to process massive amounts of data in real time for the early detection of adverse medical conditions such as cancers (Figure 2.5). Similarly, Hospital‐to‐Home (H2H) services that can provide urgent treatments for patients will also require seamless connectivity with extreme reliability [70]. In addition, VLC is expected to be integrated with mobile networks to facilitate in‐body sensors to provide vital information for patient monitoring [21]. Moreover, the massive amounts of health information that will be gathered should be protected by future networks with powerful and intelligent measures to ensure data security and user privacy [70, 71]. These requirements are beyond 5G capabilities and demand a new generation of mobile communication networks.
Figure 2.5 Increasing elderly population.
36G Requirements
The 6G networks are required to develop over existing 5G networks to support emerging technologies and applications. After reading this chapter, you should be able to
Understand how the 6G requirements develop over existing networks capabilities.
