Description
Insights on designing a sustainable 6G system as a multi-functional platform that delivers services beyond communication
6G to Build a Sustainable Future provides a summary of the research conducted in the European 6G Flagship project Hexa-X-II towards the sixth generation (6G) mobile networks, with additional input from other smart networks and services joint undertaking (SNS-JU) projects, such as 6G-DISAC, 6G-MUSICAL, 6G-NTN, 6G-SHINE, Deterministic 6G, RIGOROUS, ROBUST-6G, TERRAMETA and TERA6G. The book explores the motivation, values, and needs of 6G, with a strong emphasis on environmental, economic, and social sustainability.
To address these needs, the 6G system will be designed as a platform, providing services including and beyond communication; the book provides an end-to-end (E2E) blueprint of this system. The book also outlines the potential paths from the project results towards standardization and further towards introduction to the markets.
Topics discussed include:
- Design principles, requirements, value, validation and blueprints for inclusive, trustworthy, and environmentally sustainable 6G platforms
- 6G transceiver and radio design, covering architecture and deployment, radio link modeling, transmission schemes, and signal processing hardware
- 6G intelligence through AI-native architecture, smart network management, and intent-based management
- Architectural enablers including flexible networks, dependable networking, beyond communication services architecture, and radio protocols
- E2E security concepts, covering security enablers
- All this from Hexa-X-II as well as other SNS-JU projects
6G to Build a Sustainable Future is an essential, up-to-date reference for wireless researchers, network planners, technology analysts, technology marketers, R&D engineers, application developers, spectrum regulators, and students.
Table of Contents
List of Contributors xiii
Preface xxiii
1 Introduction 1
Patrik Rugeland, Mikko A. Uusitalo, Sylvaine Kerboeuf, Jeroen Famaey, Stefan Wendt, Henk Wymeersch, Sokratis Barmpounakis, Hamed Farhadi, and Mauro R. Boldi
1.1 Why Do We Need 6G? 2
1.2 Global View on Development Towards 6G 3
1.3 Structure of the Rest of the Book 5
Disclaimer 6
Acronyms and Abbreviations 6
References 6
2 Value of 6G 9
Stefan Wendt, Hanne-Stine Hallingby, Cristóbal Vinagre Zúñiga, Marja Matinmikko-Blue, Arturo Basaure, Maurizio Cecchi, Ishita Mishra, Ana Pereira, and Anastasia Yagafarova
2.1 Sustainability and Values 10
2.2 Stakeholders in the 6G System 16
2.2.1 6G Use-Case Business Ecosystem Stakeholders 17
2.2.1.1 Business Ecosystems’ Expansion with 6G 18
2.2.1.2 Sustainability Risk Assessment of the 6G Use Cases 19
2.2.1.3 The Envisioned 6G User 19
2.2.1.4 Indirect 6G User Impact 20
2.2.1.5 Customers and Innovators as Stakeholders 20
2.2.1.6 Risk Mitigation 20
2.2.1.7 Building a Resilient 6G 21
2.2.2 Spectrum Ecosystem Stakeholders 21
2.2.3 Public Ecosystem Stakeholders 23
2.3 6G Use-Case Families and Use Cases 25
2.3.1 Immersive Experience 25
2.3.2 Physical Awareness 26
2.3.3 Digital Twins 26
2.3.4 Fully Connected World 27
2.3.5 Trusted Environments 27
2.3.6 Collaborative Robots 27
2.4 6G Use Case and Value Design | Cooperating Mobile Robots 28
2.4.1 Human and Planetary Goals 28
2.4.2 Problems to Be Solved and Challenges 29
2.4.3 Why 6G Is Needed 29
2.4.4 Example Scenarios 30
2.4.4.1 Cooperative Carrying with Mobile Robots 30
2.4.4.2 Lot-Size-1 Production 31
2.4.4.3 Automated Industrial Tasks 31
2.4.4.4 Autonomous Farming 32
2.4.4.5 Autonomous Construction Site 32
2.4.4.6 Smart Workshop 33
2.4.5 Deployment Aspects 34
2.4.5.1 Environment 34
2.4.5.2 Type of Deployment 34
2.4.5.3 Users and Devices 34
2.4.5.4 Constraints and Challenges 34
2.4.6 Requirements 35
2.4.7 Key Performance Indicators 35
2.4.8 Key Values and Key Value Indicators 37
2.4.9 Feedback into Technical Design 43
2.5 Business Models 44
2.5.1 Business Modelling for 6G Ecosystem 44
2.5.2 Business Modelling for Cooperating Mobile Robots Use Case 51
2.6 Conclusions 52
Acknowledgement 52
Acronyms and Abbreviations 53
References 53
3 Sustainable 6G Platform 55
Sylvaine Kerboeuf, Akshay Jain, Diego Lopez, Raul Munoz, Pol Alemany, Behnam Ojaghi, Luís Pedro Santos, José María Jorquera Valero, Manuel Gil Pérez, Gregorio Martínez Pérez, Pietro G. Giardina, Huy Q. Tran, Gunes Kesik, Noelia Perez Palma, Antonio Skarmeta, Pawani Porambage, Josué Castañeda Cisneros, Elham Dehghan Biyar, Ioannis Tzanettis, Grigorios Kakkavas, Anastasios Zafeiropoulos, Xosé R. Sousa, and Patrik Rugeland
3.1 Sustainable 6G System: Principles and Requirements 56
3.1.1 Design Principles 57
3.1.2 Requirements 59
3.1.2.1 Functional Requirements 59
3.1.2.2 Non-functional Requirements 61
3.2 Blueprint of the Sustainable 6G Platform 64
3.2.1 E2E System Architecture 64
3.2.1.1 Infrastructure Layer 65
3.2.1.2 Network Functions Layer 66
3.2.1.3 Application Enablement Platform Layer 67
3.2.1.4 Application Layer 69
3.2.1.5 Pervasive Functionalities 69
3.2.1.6 Multistakeholder Support 71
3.2.2 Design Process of 6G E2E System 71
3.2.2.1 Top-Down Versus Bottom-Up System Design 71
3.2.2.2 Enablers Integration in 6G System: A Knowledge Graph-Based Approach 74
3.3 Multi-Stakeholder Intent-Based Service Management 76
3.3.1 End-to-End Multi-DSP Service Management 76
3.3.1.1 Multi-DSP Aggregation Service Provisioning 76
3.3.1.2 Multi-DSP Federation Service Provisioning 77
3.3.2 Intent-Based Digital Service Manager 78
3.3.2.1 Intent-Based Interfaces 79
3.3.3 Intent-Based-Specific Enablers for a Sustainable E2E Service Management 80
3.3.3.1 E2E Intent-Driven Service Fulfilment Management 80
3.3.3.2 E2E Intent-Driven Service Evaluation Management 80
3.3.3.3 E2E Intent-Driven Closed Loop Coordination 81
3.3.3.4 E2E Intent-Based Trust Management 82
3.4 E2E Security Concepts 82
3.4.1 Security Controls and Security Enablers 84
3.4.1.1 Physical Context Awareness 86
3.4.1.2 Physical Anomaly Detection 87
3.4.1.3 Physical Layer Deception 88
3.4.1.4 Transparency Services and Level of Trust Assessment 89
3.4.1.5 Data-Intensive E2E Security Management 91
3.4.1.6 DevSecOps 91
3.4.2 E2E 6G Security 92
3.4.2.1 Infrastructure Layer 92
3.4.2.2 Network Functions Layer 92
3.4.2.3 Application Enablement Platform Layer 93
3.4.2.4 Management and Orchestration 93
3.4.2.5 AI Framework 93
3.4.2.6 Data Framework 93
3.4.2.7 Multistakeholder 6G Ecosystem 93
3.4.2.8 Service Exposure and New 6G Services 93
3.5 Conclusion 94
Acronyms and Abbreviations 95
References 97
4 6G Transceiver and Radio Design 101
Ahmad Nimr, Luis González, Tommy Svensson, Italo Atzeni, Jeroen Famaey, Nurul Huda Mahmood, Enrico Maria Vitucci, Gilberto Berardinelli, Claude Desset, Nuutti Tervo, George-Roberto Hotopan, Philippe Ratajczak, Davide Dardari, Sotiris Droulias, Angeliki Alexiou, Bikshapathi Gouda, Venkatesh Tentu, Charitha Madapatha, Akshay Vayal Parambath, Hao Guo, Sebastian Haas, Emil Matus, Onel L. A. López, Bikramjit Singh, Nafiseh Mazloum, Samer Nasser, Ritesh Kumar Singh, Priyesh Pappinisseri Puluckul, Riku Jäntti, Dinh-Thuy Phan-Huy, Efstathios Katranaras, Usman Virk, Pekka Kyosti, Katsuyuki Haneda, Yigit Ertugrul, Meng Li, Bilal Khan, Christos Tsokos, Osmel Martínez Rosabal, Amirhossein Azarbahram, Ling Jie, Peize Zhang, Jingyi Liao, Kalle Koskinen, Xie Boxuan, Simon Nellen, Tianwen Qian, Ahmad Mohammad, Chris Roeloffzen, Muhsin Ali, Juha-Matti Runtti, and Fengchun Zhang
4.1 6G Radio Design Overview 103
4.1.1 6G Radio Scenarios 104
4.1.2 Radio Design Framework 106
4.1.3 Flexible Radio Architecture and Deployment 109
4.2 Transceivers and Antennas 110
4.2.1 Novel Architectures for Transistor-Based Sub-THz Systems 111
4.2.1.1 Dimensioning 111
4.2.1.2 Phase Noise Mitigation Utilizing Asymmetrical LO Routing 111
4.2.1.3 Antenna Integration 113
4.2.2 Novel Sub-THz Transceiver Technologies 115
4.2.2.1 Resonant Tunnelling Diodes 115
4.2.2.2 Photonic Sub-THz Transceivers 116
4.2.3 RIS Hardware Prototyping and Verification 119
4.3 Channel and Hardware Modelling 120
4.3.1 Short-Range Measurements and Channel Models in Industrial Scenarios 121
4.3.1.1 Delay Spread Analysis 122
4.3.1.2 Path-Loss Analysis 122
4.3.1.3 Analysis of the Rician K-Factor 124
4.3.2 Macroscopic Channel Modelling for RIS 124
4.3.2.1 Fully Ray-Based Macroscopic Modelling 125
4.3.3 Modelling of Sub-THz Channel Dispersion in the Presence of Beamforming 127
4.3.4 Modelling of Hardware Non-Idealities 128
4.3.4.1 Sub-THz Non-Idealities Modelling 128
4.3.4.2 FR3 Power Amplifier Modelling 130
4.4 MIMO Architectures and Transmission Schemes 130
4.4.1 Hybrid Architectures Exploiting ‘Over-the-Air’ EM Signal Processing 130
4.4.2 Near-Field Wavefront Engineering for Integrated Sensing and Communication 134
4.4.2.1 RIS-Aided Wavefront Engineering 134
4.4.2.2 Near-Field Angle-Range Localization for ISAC 136
4.4.3 Massive MIMO with Low-Resolution Data Converters 137
4.4.4 D-MIMO and RIS 139
4.4.4.1 Centralized Versus Distributed Beamforming Design in D-MIMO 139
4.4.4.2 ISAC D-MIMO, Scalable D-MIMO 140
4.4.4.3 RIS-Assisted D-MIMO, RIS-Assisted IAB 142
4.5 6G Devices and Infrastructure 144
4.5.1 Future Directions for IoT Devices 145
4.5.1.1 Energy Neutral Devices 145
4.5.1.2 Enhanced LPWA 145
4.5.1.3 Intelligence with TinyML 145
4.5.1.4 Security and Privacy Enhancements 145
4.5.2 Secure Integration of SoC Accelerators 146
4.5.2.1 Secure SoC Architecture with Accelerator Integration Support 146
4.5.2.2 AI and DSP Accelerator Capabilities 147
4.5.3 Energy Neutral Device Design 148
4.5.3.1 Energy Harvesting 148
4.5.3.2 Protocols for Active Energy Neutral Devices 150
4.5.3.3 Passive Energy Neutral Devices 152
4.6 Conclusions 154
Acronyms and Abbreviations 155
References 157
5 Architecture Enablers for 6G 167
Mårten Ericson, Ozgur Umut Akgul, Panagiotis Botsinis, Sameh Eldessoki, Nicolas Chuberre, Dorin Panaitopol, Joachim Sachs, Hasanin Harkous, Iman Hmedoush, Luis G. Uzeda Garcia, Pere Garau Burguera, Antonio de la Oliva, János Harmatos, Halina Tarasiuk, Marcin Ziółkowski, Karol Kuczyński, Alperen Gundogan, Milan Zivkovic, Diamanti Maria, Pilar Andres Maldonado, Stefan Wänstedt, Vignesh Raman, Bassem Arar, Riccardo Bassoli, Frank H.P. Fitzek, Vasileios Tsekenis, Sokratis Barmpounakis, and Antonio Varvara
5.1 Novel Services 168
5.1.1 Sensing Functional Architecture 170
5.1.2 Compute Offloading 171
5.1.3 AI as a Service 173
5.1.4 Consumer Application Function Placement Optimization 174
5.2 6G Cloud-Native Architecture 176
5.2.1 Modular Network Architecture for 6G 176
5.2.2 Inter-module Interactions and Interfaces 178
5.2.3 Integration of Extreme Edge 179
5.3 Flexible Networks 180
5.3.1 Subnetworks 181
5.3.2 Multi-connectivity 182
5.3.3 5G–6G Spectrum Co-existence: Multi-RAT Spectrum Sharing 185
5.4 Non-terrestrial Networks 186
5.4.1 Rationale for NTN in 6G 186
5.4.2 NTN Deployment Scenarios 187
5.4.2.1 Frequency Band of the Service Link 189
5.4.2.2 Radio Cells 190
5.4.3 Impact on 6G System Architecture 191
5.4.4 Support of NTN-TN Integration 191
5.4.4.1 Ubiquitous Connectivity 191
5.4.4.2 Resiliency 192
5.4.4.3 Network Energy Efficiency/Sustainability 192
5.4.4.4 Spectrum Usage Efficiency 192
5.4.5 On-Board Edge Capabilities 192
5.5 Dependable Networking 193
5.5.1 Enablers for Dependable Networking 194
5.5.1.1 Performance Observability and Predictability 194
5.5.1.2 Dependable Edge Cloud Integration 195
5.5.1.3 Packet Delay Correction for Deterministic Delay Performance 196
5.5.1.4 Network Programmability and Communication–Control–Compute Co-design 196
5.5.1.5 Bringing Dependability to the Multi-domain Multi-technology Data Plane 197
5.5.2 Architecture Support for Dependable End-to-End Communication with 6G 198
5.6 Radio Protocols 200
5.6.1 Radio Control Plane 201
5.6.2 Radio User Plane 202
5.6.3 Mobility Procedures 204
5.6.4 App-Network Interactions for Service Differentiation and QoS/QoE Management 204
5.7 Quantum-Enhanced Network Functionalities 205
5.8 Conclusions 207
Acronyms and Abbreviations 209
References 212
6 6G Intelligence 217
Hamed Farhadi, Dani Korpi, Nabeel Nisar Bhat, Pawani Porambage, Halina Tarasiuk, Marcin Ziółkowski, Karol Kuczyński, José Miguel Mateos Ramos, Christian Häger, Henk Wymeersch, Ricard Vilalta, Merve Saimler, Leyli Karacay, and Milan Zivkovic
6.1 The Motivations for AI/ML in 6G 217
6.1.1 The Needs for Data-Driven Architecture 217
6.1.2 The Needs for AI/ML for Physical Layer Signal Processing 219
6.1.3 The Needs for AI-Driven Management and Orchestration 221
6.1.4 The Needs for Trustworthy AI/ML and AI/ML for 6G Trustworthiness 222
6.2 6G System Blueprint: AI/ML-Specific View 222
6.3 AI-Native Architecture 225
6.3.1 DataOps 225
6.3.2 MLOps 227
6.3.3 AI as a Service 229
6.4 AI-Driven Radio Air Interface 232
6.4.1 AI-Driven Methods for Hardware Impairment Compensation for Communication 232
6.4.2 End-to-End Optimized Physical Layer Using AI/ML Algorithms 233
6.4.3 Model-Based Learning for Hardware Impairment Compensation in ISAC 234
6.4.4 Data-Driven Sensing with Wireless Signals 235
6.5 Smart Network Management 235
6.5.1 AI-Based Solutions for Resource Allocation 235
6.5.2 Network Digital Twins 236
6.5.3 Multi-agent-Based Solutions for Distributed Services Orchestration 237
6.5.4 AI-Enabled Network Management 238
6.5.5 Causal AI for Intent-Based Management 239
6.6 AI/ML and Trustworthiness for 6G 240
6.6.1 AI/ML for Trustworthiness 240
6.6.2 Trustworthy AI/ML for 6G 242
6.7 An Overview of AI/ML Standardizations 244
6.7.1 AI/ML Standardization in 3GPP SA 2 244
6.7.2 AI/ML Standardization in 3GPP SA 5 245
6.7.3 AI/ML Standardization in 3GPP SA 6 245
6.7.4 AI/ML Standardization for Air Interface in 3GPP RAN1/RAN 2 246
6.7.5 AI/ML Standardization for Air Interface in O-RAN 246
6.8 Conclusion 246
Acknowledgment 247
Acronyms and Abbreviations 247
References 249
7 Integrated Sensing and Communication 253
Henk Wymeersch, Sami Mekki, Stefan Wänstedt, Athanasios Stavridis, Kawon Han, George C. Alexandropoulos, Benoît Denis, Sharief Saleh, Hui Chen, Yu Ge, Sokratis Barmpounakis, Vasileios Tsekenis, Rreze Halili, Rafael Berkvens, Pablo Picazo-Martínez, Giyyarpuram Madhusudan, Henry Blue, Nhan Thanh Nguyen, Markku Juntti, Musa Furkan Keskin, Francesca Costanzo, and Christos Masouros
7.1 The Role of ISAC in 6G 254
7.1.1 ISAC Use Cases 254
7.1.2 ISAC Requirements and Metrics 256
7.1.3 Global View on ISAC 257
7.1.4 Foundations of ISAC 258
7.1.4.1 Sensing Configurations 258
7.1.4.2 Integrating Sensing into Communication 259
7.2 The ISAC Architecture 260
7.2.1 Sensing Network Functions and Procedures 261
7.2.2 Centralized and Distributed Processing 262
7.2.2.1 Data Representation and Sharing 263
7.2.2.2 Tracking and Handover of Passive Targets 264
7.2.3 Role of AI/ML and Semantics in ISAC 265
7.2.3.1 AI/ML in ISAC 265
7.2.3.2 Semantic Communication in ISAC 266
7.3 The ISAC Physical Layer 268
7.3.1 Waveforms for ISAC 268
7.3.1.1 MIMO-OFDM for ISAC 268
7.3.1.2 Beamforming for ISAC 269
7.3.1.3 Emerging Waveforms for ISAC: OTFS and Beyond 270
7.3.2 Signal Processing for Sensing 271
7.3.2.1 Generic ISAC Signal Processing 271
7.3.2.2 Examples Deployment Scenarios 273
7.4 ISAC Hardware Considerations 275
7.4.1 Hardware Impairments and Calibration 275
7.4.1.1 Hardware Impairments 275
7.4.1.2 Impact of Hardware Impairments 276
7.4.1.3 Mitigation of Hardware Impairments 277
7.4.2 Self-Interference Suppression 278
7.4.2.1 SI Mitigation Mechanisms 279
7.4.2.2 Simultaneous DL Data Communication and Monostatic Sensing 280
7.4.3 Synchronization Requirements for ISAC 281
7.4.3.1 Impact of Synchronization on Monostatic ISAC 281
7.4.3.2 Impact of Synchronization on Bistatic ISAC 282
7.4.3.3 Impact of Synchronization on Distributed ISAC 283
7.5 Conclusion 284
Acknowledgement 284
Acronyms and Abbreviations 285
References 286
8 Early Validation of 6G Concepts 293
Sokratis Barmpounakis, Vasileios Tsekenis, Vasiliki Lamprousi, Pietro G. Giardina, Ioannis Tzanettis, Grigorios Kakkavas, Anastasios Zafeiropoulos, Panagiotis Demestichas, Ricard Vilalta, Daniel Adanza, Raul Muñoz, Pol Alemany, and Rafael Pires
8.1 PoC Components in the E2E 6G System Blueprint 295
8.2 KPIs Related to the Validation Activities 297
8.3 Social, Environmental, and Economic Sustainability Aspects 298
8.4 Validation Use Cases 299
8.4.1 The Cobot-Powered Warehouse Inventory Management Use Case 299
8.4.2 Zero-Touch Cobot-Based Video Surveillance Use Case 301
8.4.2.1 Edge Computing and Orchestration Layer 302
8.4.2.2 Cobot Surveillance System (Robot Layer) 305
8.4.2.3 VR Control and Monitoring Layer 306
8.5 System PoC Enablers 307
8.5.1 Advanced Management and Orchestration Mechanisms: Trust- and Energy-Driven Functionality Allocation 307
8.5.1.1 Implementation (Energy-Driven Optimization) 307
8.5.1.2 Implementation (Trust-Driven Optimization) 309
8.5.2 Advanced Management and Orchestration Mechanisms: Zero-Touch Automation 311
8.5.3 Trustworthy Flexible Topologies and Beyond Communication Aspects 314
8.5.4 AI-Assisted E2E Lifecycle Management of a 6G Latency-Sensitive Service 317
8.6 Evaluation Results 320
8.6.1 Trust- and Energy-Driven Functionality Allocation Evaluation Results 320
8.6.2 Trustworthy Flexible Topologies and Beyond Communication Results 324
8.6.3 AI-Assisted E2E Lifecycle Management of a 6G Latency-Sensitive Service Evaluation Results 324
8.6.4 Service Migration-Related Evaluation Results 326
8.6.5 Intent-Based Networking Evaluation Results 327
8.7 Conclusion 330
Acronyms and Abbreviations 331
References 332
9 Path Towards 6G 335
Ishita Mishra, Toon Norp, Per Hjalmar Lehne, Bahare M. Khorsandi, Ricard Vilalta, Alexandros Kaloxilos, Patrik Rugeland, and Mauro R. Boldi
9.1 Migration from 5G to 6G and Gaps 335
9.2 Global 6G Initiatives 337
9.2.1 European Priorities for 6G Development 337
9.2.2 European National Platforms View 340
9.2.3 North America: Strengthening 6G Innovation Through Strategic Alliances 342
9.2.4 South America: Advancing 6G for Emerging Markets 343
9.2.5 Asia-Pacific: Key Contributions to 6G Development 343
9.2.6 Initiatives Towards Openness 344
9.3 6G Industrial Exploitation and Market Aspects 345
9.3.1 Industry’s Main Interests in 6G 345
9.3.2 Anticipated Impact from European R&I on 6G 346
9.3.3 Investigating the Exploitation Potential 346
9.3.4 6G Market Prospects 348
9.4 Next Steps for 6G Standardization 348
9.4.1 Standardization and Industrial Fora 349
9.4.2 Roadmap and Next Steps 349
9.5 Key Challenges and Future Directions 351
Acronyms and Abbreviations 351
References 352
10 Conclusion 355
Patrik Rugeland, Mikko A. Uusitalo, and Mauro R. Boldi
Index 357
