Intelligent Spectrum Management E-Book
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- Herausgeber: John Wiley & Sons
- Kategorie: Wissenschaft und neue Technologien
- Sprache: Englisch
Forward-thinking reference on spectrum sharing and resource management for 5G, B5G, and 6G wireless networks
Intelligent Spectrum Management: Towards 6G explores various aspects of spectrum sharing and resource management in 5G, beyond 5G, and the envisaged 6G networks. The book offers an in-depth exploration of intelligent and secure sharing of spectrum and resource management in existing and future mobile networks.
The book sets the stage by providing an insight to the evolution of mobile networks and highlights the importance of spectrum sharing and resource management in next-generation wireless networks. At the core, the book explores various promising technologies such as cognitive radio, reinforcement learning, deep learning, reconfigurable intelligent surfaces, and blockchain technology towards efficient, intelligent, and secure sharing of spectrum and resource management. Moreover, the book presents dynamic and decentralized resource management techniques, including network slicing, game theory, and blockchain-enabled approaches.
Topics covered include:
- Spectrum, and why it must be utilized optimally and transparently
- Future applications envisioned with 6G, such as digital twins, Industry 5.0, holographic telepresence, and Extended Reality (XR)
- Challenges when Dynamic Spectrum Management (DSM) is enabled through Machine Learning (ML) techniques, including the complexity of received signals and the difficulty in obtaining accurate network data such as channel state information
- Reinforcement learning and deep learning-assisted spectrum management
- Synergy between Artificial Intelligence (AI) and blockchain technology for spectrum management
- Private networks, including their prospects, architecture, enabling concepts, and techniques for efficient operation
In essence, various innovative technologies and approaches that can be leveraged to enhance spectrum utilization and efficiently manage network resources are discussed. The book is a potential reference for researchers, academics, and professionals in the wireless service provider industry, as well as regulators and officials.
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Veröffentlichungsjahr: 2024
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Table of Contents
Cover
Table of Contents
Title Page
Copyright
About the Editors
Foreword
Preface
Acknowledgments
Section I
1 Evolution of Mobile Networks
1.1 Introduction
1.2 Origins and Early Developments
1.3 Data-Centric Mobile Networks
1.4 5G Mobile Networks
1.5 Beyond 5G and Prospects
1.6 Conclusion
References
Note
2 Spectrum Access Options for Local 6G Networks
2.1 Introduction
2.2 Background/State of the art
2.3 Spectrum Valuation and Pricing
2.4 Analysis of Identified Spectrum Access Options for Local 6G Networks
2.5 Conclusion
Acknowledgment
References
Section II
3 Spectrum Management Technologies in Mobile Networks
3.1 Background
3.2 Cell Frequency Planning
3.3 Steps Toward Dynamic Spectrum Access
3.4 6G Spectrum Management Opportunities
3.5 Way Ahead Toward 6G Spectrum Management
3.6 Conclusion
References
4 Artificial Intelligence-Enabled Dynamic Spectrum Management
4.1 Introduction
4.2 Dynamic Spectrum Allocation
4.3 Machine Learning for Dynamic Spectrum Allocation
4.4 Large Language Models for Dynamic Spectrum Allocation
4.5 Challenges and Future Directions
4.6 Conclusion
References
5 Infrastructure for Spectrum Management Enabled by Virtualization and Network Slicing
5.1 Evolution of Network and Spectrum Management Infrastructure
5.2 Network Virtualization—Toward Software-Defined Networks
5.3 Network Slicing: A Pillar for Spectrum Management in Modern Networks
5.4 Network Virtualization and Network Slicing for Efficient Spectrum Management
5.5 Spectrum Virtualization and Network Slicing Enabled Infrastructure for Spectrum Management
5.6 Conclusion
References
Section III
6 Spectrum Management for 6G RIS-SWIPT Systems
6.1 Introduction
6.2 Energy Harvesting Models
6.3 Multiple RIS Scenario
6.4 Case Study
6.5 Spectrum Management
6.6 Recent Advancements
6.7 Conclusion
References
7 Reinforcement Learning and Deep Learning-Assisted Spectrum Management for RIS-SWIPT-Enabled 6G Systems
7.1 Introduction
7.2 RIS Design and Characteristics
7.3 SWIPT Protocols
7.4 DRL in RIS-Aided 6G Wireless Communication Systems
7.5 Open Issues and Challenges
7.6 Conclusion
References
8 RIS-Aided Low Complexity Waveform Design for Joint Sensing and Communications
8.1 Introduction
8.2 RIS and ISAC
8.3 Waveform Design for ISAC Systems
8.4 Optimal Waveform Design for RIS-Assisted Mimo JRC System: A Case Study
8.5 Conclusion
References
Section IV
9 Blockchain and Smart Contract for Decentralized and Secure Spectrum Management Toward 6G – Beyond Hype
9.1 Introduction
9.2 Dynamic Spectrum Sharing, Blockchain, and Smart Contract
9.3 Blockchain and Smart Contract for Spectrum Sharing in 5G
9.4 Blockchain and Smart Contract for Spectrum Management in B5G and 6G
9.5 Deployment Challenges and Possible Solutions
9.6 Conclusion
References
10 The Synergy of Artificial Intelligence and Blockchain in 6G Spectrum Management
10.1 Introduction
10.2 Understanding Spectrum Management in 6G
10.3 Foundations of AI with Respect to 6G
10.4 Fundamentals of Blockchain with Respect to 6G
10.5 AI-Driven Spectrum Prediction Techniques
10.6 Blockchain for Spectrum Access and Authentication
10.7 Synergy of AI and Blockchain in 6G
10.8 Conclusion
References
11 Conclusions
Index
End User License Agreement
List of Tables
Chapter 1
Table 1.1 Evolution of mobile networks.
Chapter 2
Table 2.1 The pricing examples of the locally licensed spectrum in the mid-b...
Chapter 3
Table 3.1 Mobile cellular system features.
Table 3.2 The 6G use cases based on International Telecommunication Union (I...
Chapter 6
Table 6.1 Recent study on RIS-SWIPT.
Table 6.2 Parameters used in simulations.
Table 6.3 Emulation environment for five scenarios.
a)
Chapter 7
Table 7.1 Summary of existing works that address various challenges in RIS-S...
Chapter 8
Table 8.1 Waveform designs for ISAC systems.
Chapter 9
Table 9.1 Summary of related works.
List of Illustrations
Chapter 1
Figure 1.1 Evolution of mobile networks and emerging KPIs.
Figure 1.2 Capabilities of a 5G wireless network.
Figure 1.3 Spectrum utilization of different generations of cellular network...
Chapter 2
Figure 2.1 Unlicensed 5 GHz spectrum availability.
Figure 2.2 New 6 GHz unlicensed spectrum for RLAN and 5G NR-U networks.
Figure 2.3 Spectrum trading and leasing availability.
Figure 2.4 Spectrum trading and leasing availability.
Figure 2.5 Valuation methods (a) and factors influencing resource prices (b)...
Chapter 3
Figure 3.1 An illustration of frequency planning including frequency reuse i...
Figure 3.2 The block diagram of the proposed DSM architecture.
Chapter 4
Figure 4.1 The United States radio-frequency allocation chart between 40 and...
Figure 4.2 Dynamic spectrum access categories.
Figure 4.3 Spectrum refarming as a smooth transition method from LTE to NR....
Figure 4.4 Dynamic spectrum allocation as a more efficient smooth transition...
Figure 4.5 Cognitive radio cycle.
Chapter 5
Figure 5.1 Basic components of network virtualization.
Figure 5.2 SDN architecture.
Figure 5.3 Network slicing layers.
Figure 5.4 An architecture facilitating virtualized spectrum sharing.
Chapter 6
Figure 6.1 Linear and nonlinear EH with energy conversion efficiency.
Figure 6.2 System model for multi-RIS assisted IoT system employing PS-SWIPT...
Figure 6.3 Comparative study of ERA and ORA for (a) five scenarios.
Figure 6.4 Comparative frequency analysis of various protocols (spectrum man...
Chapter 7
Figure 7.1 RIS architecture.
Figure 7.2 RIS-assisted SWIPT V2I communication.
Figure 7.3 Rate (bits/channel use) versus maximum power (W).
Figure 7.4 Harvested energy (Joules) versus maximum power (W).
Figure 7.5 An illustration of DRL framework for solving research challenges ...
Chapter 8
Figure 8.1 RIS assisting ISAC.
Figure 8.2 A MIMO JRC system with low complexity analog architecture.
Figure 8.3 Sum rate w.r.t. SNR communication performance comparison for diff...
Figure 8.4 Radar beampattern performance for different methods with , .
Figure 8.5 An RIS-assisted MIMO JRC system with low complexity analog archit...
Figure 8.6 Sum rate w.r.t. SNR communication performance comparison for the ...
Figure 8.7 Radar beampattern performance for the proposed approach without R...
Chapter 9
Figure 9.1 The evolution of mobile networks from 4G to beyond 5G (B5G).
Figure 9.2 6G architecture.
Figure 9.3 6G spectrum.
Figure 9.4 Outline of the sections.
Figure 9.5 DSS architecture.
Chapter 10
Figure 10.1 Critical challenges of 6G spectrum management and usage.
Figure 10.2 AI and blockchain for 6G spectrum management.
Guide
Cover
Table of Contents
Title Page
Copyright
About the Editors
Foreword
Preface
Acknowledgments
Begin Reading
Index
End User License Agreement
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IEEE Press445 Hoes LanePiscataway, NJ 08854
IEEE Press Editorial BoardSarah Spurgeon, Editor-in-Chief
Moeness Amin
Jón Atli Benediktsson
Adam Drobot
James Duncan
Joydeep Mitra
Ekram Hossain
Brian Johnson
Hai Li
James Lyke
Diomidis Spinellis
Desineni Subbaram Naidu
Tony Q. S. Quek
Behzad Razavi
Thomas Robertazzi
Intelligent Spectrum Management
Towards 6G
Edited by
Sridhar Iyer
KLE Technological University, Dr MSSCET, Belagavi, Karnataka, India
Anshuman Kalla
Department of Computer Engineering, CGPIT, Uka Tarsadia University (UTU),
India
Onel Alcaraz López
Centre for Wireless Communications (CWC), Oulu, Finland
Chamitha De Alwis
School of Computer Science and Technology, University of Bedfordshire,
United Kingdom
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About the Editors
Sridhar Iyer (Senior Member IEEE) received the MS degree in electrical engineering from NMSU, USA, in 2008, and PhD degree from Delhi University, India, in 2017. He received the young scientist award from the DST/SERB, Govt. of India, in 2013, and Young Researcher Award from the Institute of Scholars in 2021. He is the recipient of the “Protsahan Award” from IEEE ComSoc, Bangalore Chapter, as a recognition to his contributions toward paper published/tutorial offered in recognized conferences/journals during 2021, 2022, and 2023. He has completed two funded research projects as the principal investigator and is currently involved in an ongoing funded research project as the principal investigator. He is currently an Editorial Board Member of Scientific Reports, Nature. His current research focus includes semantic communications and spectrum enhancement techniques for intelligent wireless networks. Currently, he serves as professor at KLE Technological University, Dr MSSCET, Belagavi, Karnataka, India. For more info visit https://scholar.google.co.in/citations?hl=en&user=2hbORHEAAAAJ&view_op=list_works&sortby=pubdate.
Anshuman Kalla (Senior Member IEEE) is working as professor at the Department of Computer Engineering, CGPIT, Uka Tarsadia University (UTU), India. Dr. Kalla has more than 15 years of teaching and research experience. He has worked as a postdoctoral visiting researcher at the Center for Wireless Communications (CWC), University of Oulu, Finland. He graduated as an engineer from Govt. Engineering College Bikaner in 2004. He did Master of Science in telecommunications and wireless networking from ISEP, Paris, France, in 2008 and another master’s from University of Nice Sophia Antipolis, France, in 2011. He obtained a PhD degree in 2017. Dr. Kalla was recipient of master’s scholarships for pursuing both his master’s programs. Dr. Kalla has delivered invited sessions and talks during various short-term courses, faculty development programs, workshops, and conferences. In particular, he has delivered tutorials at IEEE 5G World Forum in 2021, IEEE ANTS 2020, and IEEE 5G World Forum in 2020. He has published papers in reputed international journals such as Elsevier (JII, IPM, JNCA, COMNET, and ICT Express), IEEE Consumer Electronics Magazine, IEEE ComSoc, IEEE Computer, IEEE Potentials, and IEEE EMR. His areas of interest are blockchain, 5G, 6G, IoT, information centric networking, software-defined networking, and next-generation networks. For more info visit https://sites.google.com/site/kallanshuman.
Onel Alcaraz López (Senior Member IEEE) is an associate professor (tenure track) in sustainable wireless communications engineering at the Centre for Wireless Communications (CWC), Oulu, Finland. He received the BSc (1st class honors, 2013), MSc (2017), and DSc (with distinction, 2020) degrees in electrical engineering from the Central University of Las Villas (Cuba), the Federal University of Paraná (Brazil), and the University of Oulu (Finland), respectively. From 2013 to 2015, he served as a specialist in telematics at the Cuban telecommunications company (ETECSA). He is a collaborator to the 2016 Research Award given by the Cuban Academy of Sciences, a co-recipient of the 2019 and 2023 IEEE European Conference on Networks and Communications (EuCNC) Best Student Paper Award, the recipient of both the 2020 best doctoral thesis award granted by Academic Engineers and Architects in Finland TEK and Tekniska Föreningen i Finland TFiF in 2021, and the 2022 Young Researcher Award in the field of technology in Finland. He is co-author of the books entitled Wireless RF Energy Transfer in the Massive IoT Era: Towards Sustainable Zero-Energy Networks, Wiley, December 2021, and Ultra-Reliable Low-Latency Communications: Foundations, Enablers, System Design, and Evolution Towards 6G. He is currently an associate editor of the IEEE Transactions on Communications. For more info visit https://sites.google.com/view/onellopez.
Chamitha De Alwis (Senior Member IEEE) is a lecturer at the School of Computer Science and Technology, University of Bedfordshire, United Kingdom. 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 secured several competitive research grants, actively contributed to many research projects, delivered guest talks and tutorials, and provided professional consultancy services to the industry. He actively pursues research in areas including AI security, cybersecurity, network security, 5G/6G, and blockchain.
For more info visit https://sites.google.com/view/chamitha.
Foreword
The vision for a fully digitized, data-driven, and autonomous society in the next decade demands future communication networks to provide ubiquitous, high-performance connectivity and thus facilitate advanced applications and services. Recently, the basic 5G standardization was completed, marking a significant milestone and paving the way for potential enhancements Beyond 5G (B5G) networks and technologies, which are currently under study. Indeed, the research community has already envisioned that by 2030, a reinvented mobile communication will be required to support the next generation of bandwidth-hungry, ubiquitous, and intelligent services and applications. Therefore, both the industry and the research community have already begun conceptualizing 6G to sustain the competitive edge of wireless technology and meet the communication requirements of the next decade. Further, effectively utilizing the broad spectrum bands in the next-generation mobile networks, including mitigating existing and future spectrum crunch issues, will require devising new intelligent and dynamic spectrum management techniques. Various techniques such as cognitive radio, blockchain, deep learning, and reinforcement learning can be used to enable intelligence within the wireless networks. In turn, this will result in an increased utilization of the spectrum, allowing networks to meet the heterogeneous demands of the users, thereby fostering the technological and market growth of the wireless communication industry.
This book aims to delve into efficient spectrum management for the next-generation intelligent mobile networks. For this, key technologies, the convergence of AI with advanced techniques, and physical and virtual infrastructure management are comprehensively discussed. Initially, the book introduces the reader to the topic through detailed information on the evolution of mobile networks, including the evolution of spectrum management toward 6G. Then, specific technologies for spectrum management, such as deep learning, blockchain, and reinforcement learning, are thoroughly discussed. Further, aspects related to the convergence of artificial intelligence (AI) and blockchain for spectrum management are presented, followed by a discussion on multiple techniques, such as network slicing and virtualization for implementing dynamic and decentralized spectrum management in the 5G/B5G/6G networks.
The book is arranged in the following four sections:
Section I
introduces the readers to the various generations of wireless networks followed by the aspects related to spectrum management and presents various options to access the spectrum in 6G networks. The section includes contributions titled “Evolution of Mobile Networks” and “Spectrum Access Options for Local 6G Networks.”
Section II
details the various techniques that can be implemented for spectrum management in the wireless networks. The section includes contributions titled “Spectrum Management Technologies in Mobile Networks,” “Artificial Intelligence Enabled Dynamic Spectrum Management,” and “Infrastructure for Spectrum Management Enabled by Virtualization and Network Slicing.”
Section III
details the implementation of reflective intelligent surfaces (RIS) for spectrum management in 6G networks. The content presented also includes specific case studies for validating the implementations. The section includes contributions titled “Spectrum Management for 6G RIS-SWIPT Systems,” “Reinforcement Learning and Deep Learning Assisted Spectrum Management for RIS-SWIPT Enabled 6G Systems,” and “RIS-Aided Low Complexity Waveform Design for Joint Sensing and Communications.”
Section IV
includes the implementation of blockchain for spectrum management followed by the joint implementation of blockchain with AI for spectrum management. The section includes contributions titled “Blockchain and Smart Contracts for Decentralized and Secure Spectrum Management Toward 6G—Beyond Hype” and “The Synergy of Artificial Intelligence and Blockchain in 6G Spectrum Management.”
Through the aforementioned sections of the book, the readers will find comprehensive discussion on:
identification of the key technologies and techniques to enable efficient spectrum management in the 5G/B5G/6G intelligent wireless networks.
aspects related to physical and virtual infrastructure for spectrum management.
mutual benefits, challenges, and prospective research on AI and blockchain for spectrum management.
blockchain and smart contracts for decentralized and secure spectrum management toward 6G.
The book may be of key interest to:
Researchers
: This book sheds light on the technologies for spectrum management in future wireless networks. To those initiating research in this area, the book can help in identifying the innovative methods that can be adopted to ensure increased spectrum utilization and management. The book also provides a comprehensive treatment of the principles and architectures for spectrum management. Overall, for the researchers, this book can provide them with a clear understanding of spectrum management in intelligent mobile networks and can help them develop future related frameworks.
Academicians
: The book may be valuable for the academicians who engage in teaching and conducting research in the area related to intelligent wireless networks.
Network Service Providers
: This book can help the service providers gather key information regarding spectrum management. This can help them plan future frameworks and algorithms.
Industry Professionals
: Industry professionals may use this book as a reference to envision, plan, and implement future applications and use cases considering appropriate business models.
Regulators and Standardization Bodies
: For regulators and Standards institutions, this book can help to inform them about forthcoming technologies and applications.
Preface
Fifth-generation (5G) mobile networks are expanding, underpinning applications ranging from smart cities and smart industries to autonomous vehicles. However, as researchers are exploring emerging applications, including augmented reality (AR), virtual reality (VR), mixed reality (XR), holographic telepresence, connected autonomous vehicles (CAVs), Industry 5.0, and Metaverse technologies, it is evident that the world demands better connectivity that can be realized through Beyond 5G (B5G) technologies, developing toward the sixth generation (6G) of mobile networks. The 6G networks will exploit a plethora of new technologies and harness the capabilities of artificial intelligence (AI) to power the next-generation applications.
The B5G and 6G networks are expected to manage heterogeneous communication technologies utilizing a broad range of frequency spectrum up to terahertz (THz) frequencies. This demands efficient and intelligent spectrum management. In this direction, the book provides a comprehensive understanding of the advances in the research and development work related to B5G and 6G spectrum management in wireless networks. The book explores the evolution of mobile networks focusing on spectrum management technologies in mobile networks (principles, technical aspects, applications, and challenges). Furthermore, the book provides a detailed understanding of the evolution of spectrum management toward 6G, together with various technologies such as deep learning, reinforcement learning, and blockchain, which enable efficient spectrum management. The book also elaborates on the convergence of AI and blockchain to facilitate intelligent and secure spectrum management in the B5G and 6G networks. In addition, the book highlights the infrastructure requirements for realizing dynamic spectrum management in the B5G and 6G wireless networks. Therefore, it is envisaged that the book will be a valuable resource for the communication researchers, academics, industry experts, and standardization bodies working toward realizing intelligent spectrum management solutions for the B5G and 6G networks.
15 October 2024
Sridhar Iyer
KA, India
Anshuman Kalla
GJ, India
Onel Alcaraz López
Oulu, Finland
Chamitha De Alwis
Luton, UK
Acknowledgments
In compiling this book, we have been fortunate to receive state-of-the-art technical contributions from renowned researchers. This book could not have been completed without their contributions. We are deeply indebted to the following researchers who took the time to frame and revise their contributions:
Deepak Kumar, Marja Matinmikko-Blue, Seppo Yrjola, Petri Ahokangas, Harri Saarnisaari, Qiyang Zhao, Hang Zou, Yu Tian, Lina Bariah, Belkacem Mouhouche, Faouzi Bader, Ebtesam Almazrouei, Merouane Debbah, Uditha Wijewardhana, Nishan Dharmaweera, Bhathiya Pilanawithana, Neha Sharma, Sumit Gautam, Prabhat Kumar Upadhyay, Symeon Chatzinotas, Bjorn Ottersten, Manojkumar B. Kokare, Purva Sharma, Swaminathan R., Vimal Bhatia, Christos Tsinos, Soumya P. Dash, Aryan Kaushik, Aakash Arora, Marco Di Renzo, Bikramjit Choudhury, Pranav Kumar Singh, Panchanan Nath, Ujjal Roy, Ramalingam M., Gokul Yenduri, Pyingkodi M., and Thippa Reddy Gadekallu.
We would like to thank Kavipriya, Becky, and Sandra from Wiley for their constant support and timely inputs regarding the completion of various phases of this book. We also thank Wiley for their assistance in creating the index for the book. We are thankful to our respective institutions for providing us the opportunity to carry out this work and for providing us with an intellectually stimulating environment.
As always, the greatest debt one owes is to one’s colleagues, friends, and family. In our case, this debt is especially large. So, we would like to acknowledge the unwavering support by our family members who are responsible for this book in more ways than even they know. We dedicate this book to them.
Sridhar Iyer
Anshuman Kalla
Onel Alcaraz López
Chamitha De Alwis
Section I
1Evolution of Mobile Networks
Deepak Kumar1, Sridhar Iyer2, and Onel Alcaraz López1
1Centre for Wireless Communications (CWC), University of Oulu, Oulu, Finland
2Department of ECE, KLE Technological University, Dr. MSSCET, Belagavi, Karnataka, India
1.1 Introduction
The advent of mobile networks has ushered in a new era of communication. This in turn is playing a pivotal role in our interconnected world and has transformed the way we connect, work, and live. By enabling people to seamlessly communicate, access information, and utilize digital services anytime and anywhere, mobile networks increasingly bridge the digital divide and support businesses, e-commerce, and digital entrepreneurship, thus fueling economic growth and societal advances. Indeed, mobile communications can significantly contribute to achieving the sustainable development goals of the United Nations.1 This is possible by offering infrastructure and access to digital services supporting growth, efficiency, and sustainability, especially for economies where existing services are limited or the related infrastructure is poor [1].
Digitalization of services delivered through mobile communications networks has shown immense benefit in developing economies in particular driving the uptake of micro-banking and micro-finance, micro-energy grids, and market creation [2]. Productivity enhancement may arise from remote work support and access to critical information and digital services, a capability that has become crucial in the face of global challenges such as the COVID-19 pandemic. In times of crisis, mobile networks even serve as vital lifelines, facilitating emergency communication and coordination.
There have been phenomenal advancements in mobile communications for more than a century and consistently since the first-generation (1G) networks in the 1980s. A new generation has been introduced nearly every 10 years since then, with each iteration bringing significant improvements in terms of key performance indicators (KPIs). From the initial 1G networks that allowed only voice calls, mobile communication networks have progressed through the second generation (2G), third generation (3G), fourth generation (4G), and fifth generation (5G), enabling not only voice communication but also high-speed Internet access, mobile gaming, location tracking, online education, augmented reality applications, and foundation for the Internet of Things (IoT) [3]. A graphical representation of the evolution of mobile networks, including some distinctive KPIs that emerged during the evolution, is shown in Figure 1.1.
Figure 1.1 Evolution of mobile networks and emerging KPIs.
Understanding the evolution of mobile networks is of paramount importance for researchers, engineers, and academics, and constitutes the scope of this chapter. Such an understanding/knowledge drives innovation, informs policy, opens business avenues, and ensures the education of future generations. As mobile networks continue to evolve, staying informed and engaged in their development is vital for the betterment of society and the advancement of human, human-to-machine, and machine-to-machine connectivity.
1.2 Origins and Early Developments
Telecommunications have been critical to human society since ancient times. The discovery of the relationship between electricity and magnetism by Hans Christian Oersted in 1820 was a milestone. Further, Michael Faraday showed that a fluctuating magnetic field could induce electric current on a conductor in 1831, marking a turning point in the history of telecommunications by laying the foundation for subsequent advancements. This discovery laid the groundwork for wireless communication at non-line-of-sight distances.
Later on, two major telecommunication developments were the invention of the telephone by Alexander Graham Bell in 1876, allowing the transmission of analog live signals, and Marconi’s wireless telegraphy in 1896. The first amplitude-modulation radio broadcasting was demonstrated by Reginald A. Fessenden in 1906. Meanwhile, in 1935, Major Edwin H. Armstrong demonstrated high-quality music transmission using frequency-modulation radio broadcasts. The private telephone companies also started providing landline telephones and services. During the 1940s, the general public was offered a public mobile telephone, which was a wireless device that connected with the public switched telephone network [4]. The United States’ Federal Communication Commission (FCC) started two-way radio service over a 460 MHz band in 1945, where millions of users used the same channel across the country. In 1947, radiotelephone systems, comprising small geographical areas called cells, were proposed by the Bell laboratories [5]. A base station (BS) transmitter setup was placed in each cell, and cell traffic was controlled by a central switch. A few decades later, in 1971, the first wireless computer network, called AlohaNet, was introduced [6]. AlohaNet could connect multiple low-data rate stations via a single radio channel to a central host without considering any access rule or synchronization [7]. In 1972, S-Aloha was proposed using a time-slotted channel, which could double the channel capacity. The cellular radio networks assign radio channels to mobile stations by employing a demand-assigned multiple-access protocol, where the uplink request channel is based on S-Aloha.
The initial cellular systems are referred to as mobile radiotelephone or zeroth generation (0G), pointing to the pre-cellphone mobile telephony. Such systems were usually mounted in vehicles’ boot/trunk. Indeed, the transceiver was mounted in the vehicle boot and was usually placed on the head section and fixed close to the driver’s seat. In 1979, Nippon Telegraph and Telephone Corporation launched 1G to the citizens of Tokyo, which was available nationwide in Japan by 1984 [8]. The cellular standards used in 1G included mainly Advanced Mobile Phone Services (AMPS) and Nordic Mobile Telephones (NMT). The AMPS was invented at Bell Labs [9] and also used in the United Kingdom under the name of Total Access Communication System [10]. The NMT system was simultaneously introduced in Denmark, Finland, Norway, and Sweden in 1981, which was the first mobile phone network with worldwide roaming [11]. Motorola’s DynaTAC mobile phone was implemented by Chicago-based Ameritech in 1983 to build the first 1G network in the United States [12]. The world’s first cell phone, DynaTAC 8000X, created by Motorola in 1983, was essentially a two-way frequency-modulation radio designed only for voice calls [13]. Several nations, including the United Kingdom, Mexico, and Canada, followed in the early to mid-1980s.
1G was completely an analog cellular system. The fundamental concept underlying 1G cellular networks is the division of the region into cells, each of which is serviced by a BS and usually spans 10–25 km. The small size of cells allows for frequency reuse in nearby cells. In addition, smaller cells need smaller, less-expensive, and less-powerful equipment to send and receive data. However, these standards did not include any placement (i.e., coordinates of a certain object) instructions. The utilization of location data within the network garnered noteworthy interest from both, operators and application developers. Vehicle location (by using signal strength, time delay, or direction of arrival measurements) was targeted to improve the effectiveness of cellular calls through system control [14]. 1G cellular systems were additionally utilized for intelligent vehicle highway system (IVHS) applications [15]. Further, it supported emergency services based on proprietary location solutions. This included services such as those of Grayson Wireless with a joint time difference of arrival and angle of arrival solution or true position with an uplink time difference of arrival, both of which used AMPS signals [16]. 1G networks realized data rates up to 2.4 kbps, sufficient to support analog voice call services [10]. Meanwhile, these networks were concentrated in urban and densely populated areas with limited coverage and capacity, and faced network congestion, excessive call drop problems, reckless hand-off, and security threats.
The Groupe Spécial Mobile, established in 1982 by the European Conference of Postal and Telecommunications Administrations, started working on the harmonization of mobile communication systems in the 900 MHz band [9]. The primary service was telephony; however, it was also possible to use enticing nonvoice alternatives. The action plan included studies on market, tariff, technical, and regulatory needs. Further, in 1984, France and Germany contributed to the global system for mobile communications (GSM) [17]. A structure for the GSM specifications and an action plan for their completion was created. It was decided to employ smart cards as subscriber identity modules (SIMs), and support free circulation, mobile station licensing, international roaming, charging, and accounting. At a high-level meeting in Bonn in May 1987, the basic GSM specification was finally agreed upon.
The transition from 1G to 2G in the 1990s constituted the transition from analog to digital cellular systems, offering improved voice quality and paving the way for sophisticated mobile services and capabilities. The progression of mobile communications from several separate systems to standard systems across the nations was one of the primary factors that made this transition possible. The 2G system aimed to enhance spectrum efficiency while offering a fixed data rate of 64 kbps [18]. Additionally, 2G systems offered features like electronic mail (e-mail) and short message service (SMS). The first SMS message “Merry Christmas,” was sent by Neil Papworth, a test engineer for Sema Group, from a computer to his colleague Richard Jarvis’s Orbitel 901 phone on December 3, 1992 [19]. In 1993, Nokia’s mobile phones were the first to support consumer SMS texting.
The major 2G cellular system standards were GSM, interim standard 95 (IS-95), and interim standard 136 (IS-136). The physical layer of GSM is based on time-division multiple access (TDMA) and frequency-division multiple access (FDMA). The TDMA of GSM was followed by digital standards such as digital AMPS or IS-54 (later on substituted by IS-136), integrated dispatch enhanced network (iDEN), and personal digital cellular [8]. The code-division multiple access (CDMA) was added to the IS-95 standard to improve the capacity of mobile cellular networks. CDMA also provided support for multiple data rate sets. The GSM’s standard was split into two phases, enabling first, rapid implementation of common services such as telephone or SMS, and then, the introduction of technical advancements and additional services [20].
Notably, there were no positioning/location mechanisms within the standard. The positioning capability of GSM was limited to the use of training or synchronization signals to compute ranging requirements, and similar procedures were employed for the CDMA system. In 1996, the FCC approved the provision of enhanced 911 (also known as E-911 or E911, which was a system that gives 911 dispatchers the caller’s location automatically in North America) for location requirements on the existing TDMA and CDMA cellular systems. Later on, global positioning system (GPS) receivers were incorporated to assist the cellular networks. Meanwhile, digital cellular networks were evolving toward GSM phase 2+ (i.e., 2.5G and 2.75G) and universal mobile telecommunications systems (UMTS). The 2.5G comprises a general packet radio system (GPRS) with a data rate of 50 kbps, and 2.75G comprises an enhanced data rate for GSM evolution (EDGE) with a data rate of 200 kbps, including packet-switched services like transport control protocol (TCP)/internet protocol (IP). The third generation partnership project (3GPP) was created in 1998 as a partnership of international members to standardize the evaluation of GSM and UMTS, with the European Telecommunications Standards Institute (ETSI) being one of the contributors and the main sponsor. In parallel, the Telecommunications Industry Association (TIA) and the Electronic Industries Alliance (EIA) established the 3GPP2 collaboration to carry out the standardization of IS-95 and CDMA2000 technologies.
Cellular networks were originally designed for circuit-switched speech communication and later offered data as an add-on. Data transfer via analog cellular telephone connections utilizing modems was a basic method of mobile data communication. For instance, analog and digital cellular networks such as EIA-553, AMPS, and ETSI GSM, provided modem-based circuit-switched transparent data service [7]. In this communication method, the network merely provides a voice link over which the mobile data modem can interact with a corresponding data modem in an office or computer center. The circuit-mode connection was largely underutilized, and the service was expensive if only brief messages were sent back and forth over the network during a (long) interactive session. This was the driving force for the creation of mobile data networks that use end-to-end packet switching. The packet switch was an evolution of the GPRS with a more optimized functional split between the UMTS terrestrial radio access (UTRA) network and the core network.
1G and 2G network evolution was driven by the need to support analog and then digital voice communications. Spectrum allocation was relatively static, with fixed frequency bands designated for specific services. 1G networks, e.g., AMPS and NMT, operated primarily in the 800–900 MHz range, utilizing analog signals and simple frequency division. This period saw significant regulatory involvement to allocate and license the spectrum to the operators, ensuring minimal interference and promoting initial market growth. With the advent of 2G networks, like GSM, there was a shift to digital transmission, significantly improving the spectral efficiency by exploiting TDMA and FDMA technologies. Spectrum efficiency became crucial as 2G introduced SMS, basic data services, and even digital encryption for improved security. This period laid the foundation for more dynamic and competitive spectrum management practices as mobile communication started to scale globally.
1.3 Data-Centric Mobile Networks
The previous generations of cellular communication systems were based on circuit and packet switching modes while supporting poor data rates, capacity, and limited services. The explosive growth of the Internet (entailing worldwide access to information) and multimedia applications would become the driving force for the evolution into data-centric mobile networks. A mobile Internet, i.e., using a mobile device to access the Internet over a wireless connection, represented realizing ubiquitous access to data communications. With this technology, users could finally access various online services and content without a traditional wired connection to the Internet.
The International Telecommunication Union established the International Mobile Telecommunications 2000 (IMT-2000) framework as an international standard for 3G cellular networks in 1998 [21]. 3GPP aimed to develop globally applicable specifications for 3G mobile systems. 3GPP standards were designed for mobile systems based on evolved GSM core networks, as well as the supported radio access technologies, service capabilities, and security. 3GPP was the standards organization behind UMTS/wideband CDMA (W-CDMA), and 3GPP2 developed separate standards for 3G technologies, known as CDMA2000 [22]. The emerging 3G systems enabled universal access to a variety of services tailored to mobile users as well as a wide range of basic and supplementary services supported by networks. The 3G architecture was evolved from 2G GSM, GPRS, and UMTS. Specifically, a set of extensions to GSM data services were designed and standardized, resulting in 2.5G systems viz., high speed circuit switched data (HSCSD), GPRS, and EDGE. The main 3G technologies were UMTS and CDMA2000, and are discussed below.
The UMTS was a wideband CDMA (WCDMA) technology, also called UTRA. The frequency-division duplex (FDD) and time-division duplex (TDD) modes of the UTRA network were set up to produce data speeds of up to 2 Mbps. UMTS R99 allowed mobile networks to directly profit from the vast impetus behind the Internet’s expansion and launch of new services. This evolution also enabled telecom providers to roll out a standard backbone (like IP) for all access types, significantly lowering capital and operating costs. Meanwhile, UMTS R00 introduced a next-generation network architecture for circuit and packet-switched domains. Both, stationary and mobile customers, were able to access a variety of services using UMTS. The World Administrative Radio Conference in 1992 designated the 1885–2025 MHz and 2110–2200 MHz frequency bands as the target radio interfaces for UMTS, which was designed to be extremely flexible and efficient.
The CDMA2000 technology was based on the evolution of IS-95, which consists of multiple narrowband CDMA carriers of 1.25 MHz. To safeguard significant financial investment in the base of networks that have already been deployed, the design of the air interface was backward compatible with the deployed IS-95 networks and built on 2G. The cdma2000 supported an advanced medium access control feature to efficiently support several concurrent data (up to 2 Mbps) and voice services.
The progression of GSM, UMTS, and CDMA2000 toward 4G cellular systems aimed to support Internet browsing, interactive gaming, mobile TV, and streaming video and audio [23]. This was led by long-term evolution (LTE), which is regarded as a 3.9G technology since 3GPP Rel-8 [24] and Rel-9 [25] of the LTE standard do not completely comply with the International Mobile Telecommunications (IMT)-Advanced standards for 4G technology. The LTE technology was designated by 3GPP to support mobile data demand and multimedia applications. Its evolved-UTRA air interface uses single-carrier (SC) FDMA for uplink and orthogonal frequency-division multiple access (OFDMA) for downlink to achieve a data rate of up to 50 Mbps and 100 Mbps, respectively [26]. The multicarrier feature allows LTE to operate in different system bandwidths (between 1.4 and 20 MHz) by adjusting the number of subcarriers and their allocation to multiple users.
LTE operates in the FDD and the TDD modes. A time-frequency block is the fundamental LTE radio resource that can be addressed for data transfer. The resource block has a subframe duration of only 1 ms in the time domain. The inclusion of a short subframe allows for the exploitation of channel variations by scheduling users based on their channel quality. Further, it is feasible to achieve broadly scaled transport block sizes and a wide variety of user-data rates by assigning a variable number of resource blocks to a particular user and choosing a modulation and coding scheme to suit the present channel conditions. Furthermore, an LTE system was designed to operate as a packet-based system with fewer network components, which increases system capacity and coverage, and offers enhanced quality of service (QoS) in terms of high data rates, low access latency, flexible bandwidth operation, and seamless integration with other current wireless communication systems.
3GPP began establishing advanced LTE, aka LTE-A, standards in Rel-10 [27] and termed it 4G technology to fulfill the peak data rate of up to 1 Gbps and low data rate of up to 100 Mbps [28]. The heterogeneous networks (comprising of macro and small cells) were defined to fulfill new features, including carrier aggregation (CA), coordinated multipoint, and improved multiple-input multiple-output (MIMO) transmissions. With SC-FDMA for uplink and OFDMA for downlink, LTE-A’s physical layer was backward compatible with LTE. The maximum system bandwidth of the LTE-A technology was 100 MHz. As a result, the operators were able to combine fragmented spectrum from several bands into one bigger spectrum resource. The implementation of CA networks has advanced well, enabling operators to convert their investment in more LTE carriers into commercially viable high data rates. Moreover, CA is considered a vital enabler for harnessing unlicensed spectrum opportunities within the 5 GHz band, as specified in 3GPP Rel-13 [29].
The LTE-A system improved the previous LTE systems by supporting significantly more data usage, lower latency, and better spectral efficiency. In addition, it introduced a new type of data communication between entities called machine-type communication (MTC). With MTC, machines can share and exchange data without any human intervention. In the vision of smart city applications such as online education, smart utility, online surveillance, environment monitoring, e-health, and connected vehicles, a large number of autonomously operated low-cost devices (i.e., actuators and sensors) are required to be connected to physical objects. MTC is a term used to describe the communications that take place between these independently operating devices. Contention-based random access is used to support MTC in LTE.
The further enhancements of the LTE standard in 3GPP Rel-13 are known as LTE-Advanced Pro and termed 4.5G. A fundamental component of this evolution is indoor location, which plays a crucial role in improving mobile broadband and connectivity QoS while maintaining full LTE-A backward compatibility. Radiofrequency pattern matching (RFPM) was adopted to improve the existing positioning techniques dependent on radio access technologies such as observed time difference of arrival (TDoA), uplink TDoA, and enhanced cell-ID. Additionally, systems independent of radio access technologies, such as advanced global navigation satellite systems, terrestrial beacon systems, and WiFi/Bluetooth, were adopted to improve existing positioning techniques. The goal of LTE-A Pro’s evolution was to offer a fresh 5G candidate technology.
The transition to 3G and 4G networks greatly reshaped spectrum management due to increasing data demands. 3G networks, e.g., UMTS and CDMA2000, leveraged wider frequency bands around 2 GHz and introduced technologies like WCDMA and CDMA, enabling higher data rates and more efficient spectrum use. Spectrum auctions became common, promoting a more competitive environment and better resource allocation. With the advent of 4G, the focus shifted to high-speed data and low latency. Spectrum management strategies in this generation included dynamic spectrum access and CA, which allowed operators to combine multiple frequency bands to enhance bandwidth and improve user experience. Additionally, the introduction of OFDMA enabled a more efficient use of the spectrum through time/frequency-domain multiplexing. Regulatory bodies played a critical role in standardizing these practices and ensuring that the spectrum was used efficiently and fairly.
1.4 5G Mobile Networks
Cellular mobile radio’s communication and positioning functions are undergoing a revolution owing to the 5G technology. With the advent of 5G, connectivity provision has experienced significant improvements in wireless data rate, capacity, and coverage, together with a reduction of round-trip latency and energy usage. The 5G wireless standard envisions a network that is always available everywhere. Millions of 5G handsets and hundreds of operators have been involved in the commercial deployment of the 5G mobile networks globally. 5G-capable devices are not only limited to smartphones as they may also be found in a wide range of different forms, including head-mounted displays, laptops, drones, and fixed wireless access. 3GPP Rel-15 [30] in 2016 established the groundwork for 5G new radio (NR) by considering a variety of service needs, a broad spectrum (ranging from hundreds of megahertz to tens of gigahertz), and multiple deployment scenarios (indoor/outdoor, macro/small cells). Both, standalone and nonstandalone 5G mobile network architectures, such as those utilizing dual connection between LTE and NR, were defined to make it easier for operators to transition from 4G LTE to 5G NR.
Figure 1.2 Capabilities of a 5G wireless network.
5G mobile networks are aimed to fulfill the recommendation of IMT for 2020, providing three main capabilities as illustrated in Figure 1.2[31]:
Enhanced Mobile Broadband (eMBB)
: Hotspots and wide-area coverage for high throughput and a seamless user experience.
Ultrareliable and Low Latency Communications (URLLC)
: High availability and low latency.
Massive Machine Type Communications (mMTC)
: Very broad coverage and a large number of inexpensively linked devices with long battery life.
The 5G architecture offers better software services and network solutions for a variety of public and private sectors, including energy, agriculture, city administration, health care, manufacturing, and transportation. The device-centric feature of 5G is anticipated to make it possible for nearby devices to directly communicate while skipping cellular BS to share pertinent resources. Such MTC involves automated data generation, processing, transfer, and exchange amongst intelligent devices, with minimum human participation. This is a component of the IoT ecosystem, which envisions millions of simultaneous connections between various gadgets, connected homes, smart grids, and intelligent transportation systems. The 5G wireless technology’s high bandwidth, widespread availability, and low latency are ensuring smart and intelligent vehicular communications. Technology developments in sensing and communication have created new opportunities for health monitoring. A paradigm shift in real-time remote patient health monitoring is made possible by the emerging 5G mobile networks and body area networks.
The 5G spectrum is divided into multiple frequency ranges (FRs). Specifically, FR1 corresponds to the region of 0.410–7.125 GHz, while FR2 covers 24.25–52.6 GHz (FR2-1) and 52.6–71 GHz (FR2-2). 5G mobile networks aim to provide a data rate of 10 Gbps in uplink and 20 Gbps in downlink, a 10-fold increase from the highest data rate of 150 Mbps for LTE cellular networks. Also, a latency below 1 ms is targeted, which is also a 10-fold improvement over the 10 ms round-trip duration of 4G mobile networks. To support an enormous number of linked devices as well as ultrahigh bandwidths for extended periods in a specific space, 1000 times greater bandwidth per unit area is required [32]. Moreover, longer battery life (up to 10 years) is supported to accommodate these and other emerging applications.
5G uses beam division multiple access (BDMA) and non- and quasi-orthogonal or filter bank multicarrier (FBMC) multiple access [33]. Within the BDMA framework, an orthogonal beam is assigned to each mobile station based on its position such that the mobile stations can receive numerous accesses, thus increasing the system’s capacity [34]. Notably, the beamforming capabilities at the transmitter and receiver and the exploitation of spatial division multiple access allow greater frequency reuse.
Interestingly, the mobile industry’s rising demand is pushing the transition from traditional cellular coverage to cell-free device-centric deployments. This can be realized by exploiting large beamforming gains, high frequency/bandwidth, and interference-taming capabilities of distributed massive MIMO (M-MIMO) networks. Note that millimeter-wave (mm-wave) propagation’s small radio wavelengths make it possible to employ numerous small antennas. By utilizing array antennas to control the signal’s phase and amplitude, electromagnetic waves can be enhanced in the desired direction while being canceled out in all other directions. Further, smart antennas support interference mitigation while preserving the best coverage area and transmit power reduction for both, mobile devices and BS. Therefore, it is crucial for the development of 5G wireless communications to have smart antenna designs that are optimized for directional gains, cost, and complexity.
The ultimate evolution to cell-free setups (in future systems) may initially require small-cell deployments. Indeed, deploying a large number of tiny cells, giving rise to heterogeneous networks (HetNets [35]), can help cope with the explosive growth of wireless traffic anticipated in the coming years. HetNets often include small, low-transmission-power cells in addition to the traditional macrocells. In such a dense 5G deployment, configuring and maintaining several servers and routers are challenging tasks that can be resolved by software-defined networks. This allows a division between the control and the data planes, bringing speed and flexibility to 5G networks, and may rebuild networks for fully automated management by stepping over open system interconnection (OSI) layers. Furthermore, cloud RAN aims to address the high data rate demands and promises to lower the cost of network deployment and operation while simultaneously enhancing system architecture, mobility, coverage performance, and energy efficiency [36].
The 5G standard was expanded by 3GPP Rel-16 [37] to include new verticals like (i) NR sidelink, which focuses on public safety and vehicle-to-everything; (ii) 5G broadcast, which is an evolution of LTE-based enhanced TV; (iii) nonpublic networks; (iv) Industrial IoT applications; and (v) shared or unlicensed spectrum, which includes sub-6 GHz bands. Additional changes in Rel-17 include multicast and broadcast services, expansion into FR2-2, support for satellite communications for smartphones and IoT devices, and the introduction of reduced capability (RedCap) devices aimed at new device types (e.g., wearables, surveillance cameras, and industrial sensors).
Although 5G NR has many technical components, it is important to note salient features such as scalable OFDM-based air interface, advanced channel coding (via low-density parity check coding, which provides more efficient support of throughput per decoder chip area), M-MIMO, and mm-wave operation.
5G networks have revolutionized spectrum management by incorporating a wide range of frequencies, from sub-6 GHz to millimeter-wave bands (24–52 GHz). This is critical for supporting the varied requirements of 5G services, including eMBB, URLLC, and mMTC. Spectrum sharing and dynamic spectrum access have become more prevalent, allowing for more flexible and efficient use of available resources. Techniques like dynamic spectrum sharing (DSS) enable 5G to coexist with 4G, providing a smoother transition and better spectrum utilization. Beamforming and M-MIMO technologies enhance the efficiency and capacity of the network by directing signals precisely where needed. Meanwhile, regulatory frameworks and global spectrum harmonization efforts have evolved to support these advanced techniques and allow a seamless operation of the 5G services worldwide.
The spectrum use evolution from 1G to 5G and key features of each generation are respectively illustrated and summarized in Figure 1.3 and Table 1.1.
Figure 1.3 Spectrum utilization of different generations of cellular networks.
Table 1.1 Evolution of mobile networks.
Source: Adapted from [23, 38].
Features
1G
2G
3G
4G
5G
Speed
2 kbps
64 kbps
2 Mbps
1 Gbps
Gbps
Latency
—
629 ms
212 ms
60–98 ms
ms
Access technology
AMPS, FDMA
GSM, TDMA, GPRS, EDGE
CDMA, UMTS, WCDMA, high-speed uplink packet access (HSUPA)/high-speed downlink packet access (HSDPA), EVDO
OFDMA/SC-FDMA
BDMA, FBMC
Switching
Circuit
Circuit/Packet
Packet
Packet
Packet
Bandwidth
30 KHz
200 KHz
5 MHz
1.4–20 MHz
1–6 GHz
Forward error correction
NA
NA
Turbo codes
Turbo codes
Low density parity check codes
Application
Voice
Voice + data
Voice + data + video calling
Online gaming + high definition video
Ultra high definition video + virtual reality
1.5 Beyond 5G and Prospects
After almost a decade of intense academic and industrial research on 5G mobile networks and the subsequent commercial deployment, it has become clear that 5G networks will fall short in supporting the vision of the Internet of Everything (IoE), i.e., the intelligent connection of people, processes, data, and things. Moreover, future networks are anticipated to connect many nodes in various proximity ranges, such as small cells, microcells, picocells, and femtocells, while there is an increasing need to support advanced bandwidth-hungry applications such as mixed reality, telepresence, and Industry 5.0 requiring infimum delay, highly reliable connections, and/or accessing the Internet via mm-wave/THz frequencies [39]. Given this, the research community has commenced intensive research on the Beyond 5G (B5G) successor technology, i.e., 6G mobile networks [39–41].
B5G networks are envisioned to overcome critical shortcomings of 5G mobile networks by adopting cell-free architectures and operating in sub-6 GHz, mm-wave, and THz spectrum. However, transforming such speculative ideas into real-time commercial deployments is a big challenge. Specifically, limited coverage is a key issue when operating in the mm-wave/THz spectrum and dedicated research is needed since current spectrum allocation methods are ineffective for such setups [42]. In this regard, Open RAN (O-RAN) may provide flexibility for spectrum occupancy in B5G mobile networks and thus facilitate spectrum management. Emerging open interface standards can be explored for minimizing interference between heterogeneous systems in a very congested B5G radio environment. In addition, O-RAN may permit operations in different spectrum bands, involving varied spectrum sharing (SS) levels over the mm-wave/THz spectrum. However, advanced SS techniques are required to deal with dynamically changing and highly heterogeneous environments.
Concerning M-MIMO, novel low-cost/complex hybrid architectures, and accompanied precoding techniques, are needed to promote sustainability and highly dense deployments [43]. In addition, artificial intelligence (AI) techniques can be used to predict channel characteristics and create dataset frameworks for beam-forming in M-MIMO [44]. Moreover, holographic displays are considered the next evolution in multimedia experience delivering 3D images from one or multiple sources to one or multiple destinations, providing an immersive 3D experience for the end user [45]. Interactive holographic capability in 6G networks will require a combination of very high data rates and ultralow latency. The key requirements will also include perfect synchronization, extreme resilience, and large computations. These requirements will serve as the backbone for advanced use cases such as Industry 5.0, which will need the expansion of digital twins so that visual models of the products, processes, and generation will allow better understanding and testing [46]. For Industry 5.0, 6G networks are expected to meet the intelligent information society standards to deliver ultrahigh reliability [47].
Mobile edge computing has been identified as the technology that will transform the 5G communication networks into distributed cloud computing platforms [48] and will continue its evolution over the next generations [49]. Mixed reality, autonomous driving, and holographic communications are all candidates for edge cloud coordination. The key network requirements include computing awareness of constituent edge facilities, joint network and computing resource scheduling, flexible addressing, and fast routing and rerouting.
The research community has already foreseen multiple techniques and applications that will leverage AI mechanisms in modern and future mobile networks [43, 50, 51]. For 6G networks, new network architectures comprising holistic network virtualization and pervasive AI will be required. The holistic network virtualization will consist of network slicing and digital twin to provision services and demands thereby, incorporating service- and user-centric networking [52]
