Info
6G-Enabled Technologies for Next Generation : Fundamentals, Applications, Analysis and Challenges
| 6G-Enabled Technologies for Next Generation : Fundamentals, Applications, Analysis and Challenges |
| Autore | Tyagi Amit Kumar |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Newark : , : John Wiley & Sons, Incorporated, , 2025 |
| Descrizione fisica | 1 online resource (459 pages) |
| Disciplina | 621.3845/6 |
| Altri autori (Persone) |
TiwariShrikant
GuptaShivani MishraAnand Kumar |
| Soggetto topico | 6G mobile communication systems |
| ISBN |
9781394258369
1394258364 9781394258345 1394258348 9781394258352 1394258356 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9911019979603321 |
Tyagi Amit Kumar
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| Newark : , : John Wiley & Sons, Incorporated, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Advanced Metaverse Wireless Communication Systems
| Advanced Metaverse Wireless Communication Systems |
| Autore | Imoize Agbotiname Lucky |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Stevenage : , : Institution of Engineering & Technology, , 2025 |
| Descrizione fisica | 1 online resource (581 pages) |
| Disciplina | 621.384 |
| Altri autori (Persone) |
MontlouisWebert
SongHoubing Herbert |
| Collana | Telecommunications Series |
| Soggetto topico |
Wireless communication systems
6G mobile communication systems |
| ISBN |
1-83724-388-3
1-83953-908-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Contents -- Preface -- About the editors -- 1. Advanced wireless communication techniques and the metaverse | Webert Montlouis, Ashish Goswami and Agbotiname Lucky Imoize -- 2. Key enablers of metaverse wireless communication | Webert Montlouis, Ashish Goswami and Agbotiname Lucky Imoize -- 3. Enhancing machine learning accuracy in the metaverse: overcoming noise and error in object counting systems | Yuichi Sei, Keiichiro Oishi, Yasuyuki Tahara, Akihiko Ohsuga and Agbotiname Lucky Imoize -- 4. Communication-control co-design for closed-loop metaverse | Qinqin Xiong, Jiaying Zhou, Jie Cao, Xu Zhu and Zeping Sui -- 5. Location-based real-time utilization of reconfigurable intelligent surfaces for mmWave integrated communication and sensing in full-immersive multiuser Metaverse scenarios | Filip Lemic, Jalal Jalali, Gerard Calvo Bartra, Alejandro Amat, Jakob Struye, Jeroen Famaey and Xavier Costa Perez -- 6. Preamble parallelization-based random access management for heterogeneous IoT system in metaverse | Ziming Guo, Xu Zhu, Jie Cao, Dazhuo Wang and Agbotiname Lucky Imoize -- 7. Scalable metaverse-based wireless ecosystem: networked economic valuations | Roberto Moro-Visconti -- 8. Toward a secure metaverse: crafting cutting-edge algorithm for protected data analysis | Keiichiro Oishi, Yasuyuki Tahara, Akihiko Ohsuga, J. Andrew, Agbotiname Lucky Imoize and Yuichi Sei -- 9. Exploring zero-knowledge proofs in the metaverse: applications and challenges | Oleksandr Kuznetsov, Alex Rusnak, Anton Yezhov, Kateryna Kuznetsova, Dzianis Kanonik and Oleksandr Domin -- 10. Blockchain applications in metaverse environments: new horizons | Oleksandr Kuznetsov, Emanuele Frontoni, Kateryna Kuznetsova, Oleksii Smirnov and Victoria Kostenko -- 11. Blockchain-based security and privacy solutions for metaverseassisted wireless communication systems | Elsir Ali Saad Mohamed and Agbotiname Lucky Imoize -- 12. Federated learning for the metaverse: leveraging artificial intelligence for enhanced data privacy and efficiency | Zhihao Dong, Jie Cao, Xu Zhu, HaiYong Zeng and Agbotiname Lucky Imoize -- 13. Advancing metaverse security with cryptographic innovations | Oleksandr Kuznetsov, Emanuele Frontoni, Vladyslav Chevardin, Oleksii Smirnov and Agbotiname Lucky Imoize -- 14. Cryptography in the metaverse: advanced protocols for secure communication | Oleksandr Kuznetsov, Emanuele Frontoni, Volodymyr Zvieriev, Olha Bulhakova and Vladyslav Riabovolenko -- 15. Differentially private human interactions for the real world and the metaverse | Yuichi Sei, Keiichiro Oishi, Yasuyuki Tahara, Akihiko Ohsuga and Agbotiname Lucky Imoize -- 16. Transforming ageing in the metaverse: embracing virtual communities for enhanced well-being and empowerment | Andreas Andreou, Constandinos X. Mavromoustakis, Houbing Herbert Song, German Peinado Gomez and Jordi Mongay Batalla -- 17. Wireless tools for neuromarketing and neuromanagement in the metaverse | Antonio Gonzalez-Morales, Ma Milagro Martin Lopez and Alejandro Talaminos-Barroso -- 18. Legal perspectives of the International Scientific Sandbox Metaverse: technologies and foresights for digital transformation | V. Kostenko Oleksii, A. Volkova Yuliia, P. Ustynova Iryna, O. Shapenko Liudmyla and V. Usenko Yana -- 19. Societal impacts of advanced metaverse wireless communication systems | Mikail Batu, Onur Tos and Agbotiname Lucky Imoize -- 20. Advanced metaverse wireless communications: future perspectives and research directions | Agbotiname Lucky Imoize, Emmanuel Alozie, Nasir Faruk, Webert Montlouis and Houbing Herbert Song -- Index |
| Record Nr. | UNINA-9911006730203321 |
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Imoize Agbotiname Lucky
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| Stevenage : , : Institution of Engineering & Technology, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Deep Reinforcement Learning for Reconfigurable Intelligent Surfaces and UAV Empowered Smart 6G Communications
| Deep Reinforcement Learning for Reconfigurable Intelligent Surfaces and UAV Empowered Smart 6G Communications |
| Autore | Masaracchia Antonino |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Stevenage : , : Institution of Engineering & Technology, , 2024 |
| Descrizione fisica | 1 online resource (270 pages) |
| Disciplina | 621.38456 |
| Altri autori (Persone) |
NguyenKhoi Khac
DuongTrung Q SharmaVishal |
| Collana | Telecommunications Series |
| Soggetto topico |
6G mobile communication systems
Artificial intelligence |
| ISBN |
1-83724-384-0
1-83953-642-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Contents -- Preface -- About the authors -- Part I. Introduction to machine learning and neural networks -- 1. Artificial intelligence, machine learning, and deep learning -- 2. Deep neural networks -- Part II. Deep reinforcement learning -- 3. Markov decision process -- 4. Value function approximation for continuous state-action space -- 5. Policy search methods for reinforcement learning -- 6. Actor-critic learning -- Part III. Deep reinforcement learning in UAV-assisted 6G communication -- 7. UAV-assisted 6G communications -- 8. Distributed deep deterministic policy gradient for power allocation control in UAV-to-UAV-based communications -- 9. Non-cooperative energy-efficient power allocation game in UAV-to-UAV communication: a multi-agent deep reinforcement learning approach -- 10. Real-time energy harvesting-aided scheduling in UAV-assisted D2D networks -- 11. 3D trajectory design and data collection in UAV-assisted networks -- Part IV. Deep reinforcement learning in reconfigurable intelligent surface-empowered 6G communications -- 12. RIS-assisted 6G communications -- 13. Real-time optimisation in RIS-assisted D2D communications -- 14. RIS-assisted UAV communications for IoT with wireless power transfer using deep reinforcement learning -- 15. Multi-agent learning in networks supported by RIS and multi-UAVs -- Index |
| Record Nr. | UNINA-9911006720403321 |
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Masaracchia Antonino
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| Stevenage : , : Institution of Engineering & Technology, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Development of 6G Networks and Technology
| Development of 6G Networks and Technology |
| Autore | Tripathi Suman Lata |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Newark : , : John Wiley & Sons, Incorporated, , 2024 |
| Descrizione fisica | 1 online resource (476 pages) |
| Disciplina | 621.3845/6 |
| Altri autori (Persone) |
MahmudMufti
NarmadhaC AlexanderS. Albert |
| Collana | Next Generation Computing and Communication Engineering Series |
| Soggetto topico | 6G mobile communication systems |
| ISBN |
9781394230662
1394230664 9781394230686 1394230680 9781394230679 1394230672 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Cover -- Series Page -- Title Page -- Copyright Page -- Contents -- Preface -- Acknowledgements -- Chapter 1 Introduction to AI Techniques for 6G Application -- 1.1 Introduction -- 1.2 Different Generation of Communication: From 1G to 6G -- 1.2.1 First Generation (1G) -- 1.2.2 Second Generation (2G) -- 1.2.3 Third Generation (3G) -- 1.2.4 Fourth Generation (4G) -- 1.2.5 Fifth Generation (5G) -- 1.2.6 Sixth Generation (6G) -- 1.3 Key Features and Requirements of 6G Networks -- 1.3.1 Faster Data Speeds -- 1.3.2 Ultra-Low Latency -- 1.3.3 Massive Capacity -- 1.3.4 Energy Efficiency -- 1.3.5 Seamless Connectivity -- 1.3.6 Advanced Spectrum Management -- 1.3.7 Enhanced Security and Privacy -- 1.3.8 Artificial Intelligence Integration -- 1.3.9 Heterogeneous Network Architecture -- 1.4 Role of Artificial Intelligence in 6G -- 1.4.1 Intelligent Radio Resource Management -- 1.4.2 Beamforming and MIMO -- 1.4.3 Intelligent Network Slicing |
| Record Nr. | UNINA-9911019597103321 |
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Tripathi Suman Lata
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| Newark : , : John Wiley & Sons, Incorporated, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Digital Twins For 6G : Fundamental Theory, Technology and Applications
| Digital Twins For 6G : Fundamental Theory, Technology and Applications |
| Autore | Ahmadi Hamed |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Stevenage : , : Institution of Engineering & Technology, , 2024 |
| Descrizione fisica | 1 online resource (321 pages) |
| Disciplina | 621.38456 |
| Altri autori (Persone) |
DuongTrung Q
NagAvishek SharmaVishal CanberkBerk DobreOctavia A |
| Collana | Telecommunications Series |
| Soggetto topico |
Digital twins (Computer simulation)
6G mobile communication systems |
| ISBN |
9781523163120
1523163127 9781839537462 1839537469 9781839537455 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Contents -- About the editors -- Preface -- 1. Digital twins for resilient and reliable 6G networks | Fahad Alaklabi, Ahmed Al-Tahmeesschi, Avishek Nag and Hamed Ahmadi -- 2. Digital twin-enabled aerial edge networks with ultra-reliable low-latency communications | Dang Van Huynh, Yijiu Li, Tan Do-Duy, Emi Garcia-Palacios and Trung Q. Duong -- 3. AI-enabled data management for digital twin networks | Elif Ak, Gökhan Yurdakul, Ahmed Al-Dubai and Berk Canberk -- 4. AI-based traffic analysis in digital twin networks | Sarah Al-Shareeda, Khayal Huseynov, Lal Verda Cakir, Craig Thomson, Mehmet Ozdem and Berk Canberk -- 5. Digital twin empowered Open RAN of 6G networks | Antonino Masaracchia, Vishal Sharma, Muhammad Fahim, Octavia A. Dobre and Trung Q. Duong -- 6. Potentials of the digital twin in 6G communication systems | Bin Han, Mohammad Asif Habibi, Nandish Kuruvatti, Sanket Partani, Amina Fellan and Hans D. Schotten -- 7. Digital twins for optical networks | Agastya Raj, Dan Kilper and Marco Ruffini -- 8. Dynamic decomposition of service function chain using a deep reinforcement learning approach | Swarna B. Chetty, Hamed Ahmadi, Massimo Tornatore and Avishek Nag -- 9. An Optimization-as-a-Service platform for 6G exploiting network digital twins | Oriol Sallent, José-Manuel Martínez-Caro, Javier Baliosian, Luis Diez, Luis M. Contreras, Jordi Pérez-Romero, Juan Luis Gorricho, Matías Richart, Ramón Agüero, Joan Serrat, Pablo Pavón-Mariño and Irene Vilà -- 10. Robotics digital twin for 6G | Milan Groshev, Carlos Guimarães and Antonio de la Oliva -- Index |
| Record Nr. | UNINA-9911006666903321 |
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Ahmadi Hamed
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| Stevenage : , : Institution of Engineering & Technology, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Edge Computing Acceleration : From 5G to 6G and Beyond
| Edge Computing Acceleration : From 5G to 6G and Beyond |
| Autore | Hung Patrick |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Newark : , : John Wiley & Sons, Incorporated, , 2024 |
| Descrizione fisica | 1 online resource (273 pages) |
| Disciplina | 004.6/5 |
| Altri autori (Persone) |
KanHongwei
KnopfGreg |
| Collana | The ComSoc Guides to Communications Technologies Series |
| Soggetto topico |
Computer architecture
5G mobile communication systems 6G mobile communication systems |
| ISBN |
9781119813859
1119813859 9781119813866 1119813867 9781119813873 1119813875 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Title Page -- Copyright -- Contents -- About the Authors -- Foreword (Professor Ray Cheung) -- Foreword (Raghu Nambiar) -- Preface -- Acknowledgment (Patrick Hung) -- Acknowledgment (Greg Knopf) -- Part I Introduction -- Chapter 1 Introduction -- 1.1 Introducing 5G and Internet of Everything -- 1.2 Edge Computing Architecture -- 1.2.1 Edge Versus Cloud Computing -- 1.2.2 Edge Design Options -- 1.2.3 Key Benefits of Edge Computing -- 1.3 Custom Computing -- 1.3.1 Introduction to Custom Computing -- 1.3.2 5G/6G Security Concerns -- 1.3.3 Custom Edge Computing Cards -- 1.4 Deployment Considerations -- 1.4.1 5G/6G Cell Architecture -- 1.4.2 5G/6G Private Network -- 1.4.3 Infrastructure Sharing -- References -- Chapter 2 Overview of 5G and 6G -- 2.1 5G Timeline -- 2.2 5G Spectrum -- 2.3 Characteristics of 5G -- 2.4 5G New Radio -- 2.4.1 Orthogonal Frequency‐Division Multiplexing -- 2.4.2 Massive MIMO -- 2.4.3 Beamforming -- 2.4.4 Multiuser MIMO -- 2.5 Data Plane and Control Plane Separation -- 2.6 5G Applications -- 2.7 Smooth Transition to 6G -- 2.8 6G Expected Timeline, Spectrum, and Characteristics -- 2.9 6G Potential Applications -- 2.10 Edge, Fog, and Cloud Computing in Relation to 5G and 6G -- 2.10.1 Edge Computing in Relation to 5G and 6G -- 2.10.2 Fog Computing in Relation to 5G and 6G -- 2.10.3 Cloud Computing in Relation to 5G and 6G -- References -- Part II Theory -- Chapter 3 High‐Level Synthesis (HLS) -- 3.1 Why Use High‐Level Synthesis? -- 3.1.1 Hardware Acceleration with High‐Level Synthesis -- 3.2 Common HLS Languages and Platforms -- 3.2.1 Compute Unified Device Architecture (CUDA) -- 3.2.1.1 CUDA and HLS for Hardware Acceleration -- 3.2.1.2 Advantage of Using CUDA and HLS for Hardware Acceleration -- 3.2.2 OpenCL -- 3.2.2.1 OpenCL and HLS for Hardware Acceleration.
3.2.2.2 Advantages of Using OpenCL with HLS Tools for Hardware Acceleration -- 3.2.3 Maxeler MaxJ -- 3.2.3.1 Using Maxeler MaxJ with HLS for Hardware Acceleration -- 3.2.3.2 Advantages of Using Maxeler MaxJ with HLS for Hardware Acceleration -- 3.3 Limitations and Challenges of HLS -- 3.4 Using HLS in 5G Edge Computing -- 3.4.1 User (Data) Plane Acceleration -- 3.4.2 Control Plane Acceleration -- 3.4.3 Advantages of Using HLS for User Plane and Control Plane Acceleration -- References -- Chapter 4 Coding Design -- 4.1 Overview -- 4.2 Error Correction Codes (ECCs) -- 4.2.1 Turbo, Low‐Density Parity‐Check, and Polar Codes -- 4.2.1.1 Turbo Codes -- 4.2.1.2 LDPC Codes -- 4.2.1.3 Polar Codes -- 4.3 Security Codes -- 4.3.1 Public Key Infrastructure -- 4.3.2 Symmetric and Asymmetric Cryptography Concepts -- 4.3.2.1 Symmetric Key Cryptography -- 4.3.2.2 Asymmetric Key Cryptography -- 4.3.3 Existing Algorithms and Standards -- 4.3.3.1 Advanced Encryption Standard -- 4.3.3.2 RSA Algorithm -- 4.3.3.3 Elliptic Curve Cryptography -- 4.4 Emerging 5G Security Design Acceleration -- 4.4.1 Blockchain -- 4.4.2 Lightweight Encryption Algorithms -- 4.4.2.1 SIMON and SPECK Algorithms -- 4.4.2.2 PRESENT Algorithm -- 4.4.2.3 GIFT Algorithm -- 4.4.3 Network Codes -- 4.4.4 Post‐Quantum Cryptography -- 4.4.5 Homomorphic Encryption -- 4.4.6 Zero‐Knowledge Proof -- References -- Part III Architecture -- Chapter 5 Hardware Architecture -- 5.1 Development Timeline -- 5.2 Operating Spectrum -- 5.3 Core Requirements -- 5.4 New Radio Access Technology -- 5.4.1 Orthogonal Frequency‐Division Multiplexing -- 5.4.2 Massive MIMO (Multiple‐Input Multiple‐Output) -- 5.4.3 Beamforming -- 5.4.4 Multiuser MIMO -- 5.5 Network Architecture -- 5.5.1 Next Generation Radio Access Network -- 5.5.2 5G Core -- 5.5.2.1 Control and User Plane Separation (CUPS). 5.5.2.2 Service‐Based Architecture (SBA) -- 5.6 Performance Improvement -- 5.6.1 Computing and Network Convergence -- 5.6.2 Related Works -- 5.6.3 Smart& -- uscore -- xPU Design Methodology -- 5.6.3.1 Data Flow Optimization -- 5.6.3.2 Distributed System Optimization -- 5.6.3.3 Core Microarchitecture Optimization -- 5.6.3.4 Software/Hardware Interface Optimization -- 5.6.3.5 Analyzing the Smart& -- uscore -- xPU Architecture -- 5.6.4 Summary of the Smart& -- uscore -- xPU Architecture -- References -- Chapter 6 Software Architecture -- 6.1 End‐to‐End Example of 5G System -- 6.1.1 High‐Level Description -- 6.1.1.1 5G Radio Access Network -- 6.1.1.2 Edge -- 6.1.1.3 5G Core -- 6.1.1.4 Application and Services -- 6.1.2 Interfaces -- 6.1.2.1 N1: Between 5G Core and User Equipment -- 6.1.2.2 N2: Between 5G Core and Base Station -- 6.1.2.3 N3: Between RAN and User Plane Function -- 6.1.2.4 Other Interfaces Include the Following -- 6.2 Network Slicing Architecture, Software‐Defined Network, and Network Function Virtualization -- 6.2.1 Network Slicing Architecture -- 6.2.1.1 Software‐Defined Network (SDN) -- 6.2.1.2 Network Function Virtualization (NFV) -- 6.3 Software Acceleration -- 6.3.1 User Space Approach -- 6.3.1.1 Data Plane Development Kit (DPDK) -- 6.3.2 Other Approaches -- 6.3.2.1 Remote Direct Memory Access (RDMA) -- 6.3.2.2 Compute Express Link (CXL) -- 6.3.2.3 Data Processing Unit (DPU) -- References -- Part IV Applications -- Chapter 7 Killer Applications -- 7.1 Metaverse and Its Trends -- 7.2 Technologies Behind Metaverse -- 7.2.1 Artificial Intelligence -- 7.2.1.1 AI‐Based Non‐player Character -- 7.2.1.2 Sensory Capabilities with AI -- 7.2.2 Blockchain -- 7.2.2.1 Power Consumption -- 7.2.3 AR and VR -- 7.2.4 Internet of Things -- 7.3 Applications of Metaverse -- 7.3.1 Gaming -- 7.3.2 Education -- 7.3.3 Commerce. 7.3.4 Social Networking -- 7.3.5 Healthcare -- 7.3.6 Industrial Use -- 7.3.7 Entertainment -- 7.4 Accelerating Killer Apps -- 7.4.1 Edge Computing -- 7.4.2 Acceleration by Specialized Hardware -- References -- Chapter 8 From Concept to Production -- 8.1 System Design Process -- 8.2 Some Examples -- 8.3 Standards Compliance -- 8.4 Other Design Metrics -- 8.5 Summary -- References -- Part V Future Roadmap -- Chapter 9 The Road Ahead -- 9.1 Spatial Computing and Networking -- 9.2 Supporting 5G/6G Spatial Computing and Networking -- 9.3 Migrating to 6G -- 9.3.1 Cutting Edge 6G Research -- 9.4 Enabling Technologies for 5G and Beyond -- 9.4.1 Processing‐in‐Memory Architecture -- 9.4.2 New Packaging Architecture -- 9.4.3 New Memory Architecture -- 9.4.4 Artificial Intelligence‐Driven Architectures -- 9.5 Some Final Thoughts -- References -- Index -- The ComSoc Guides to Communications Technologies -- EULA. |
| Record Nr. | UNINA-9911019503203321 |
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Hung Patrick
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| Newark : , : John Wiley & Sons, Incorporated, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Hybrid Communication Systems for Future 6G and Beyond : Visible Light Communication and Radio over Fiber Technology
| Hybrid Communication Systems for Future 6G and Beyond : Visible Light Communication and Radio over Fiber Technology |
| Autore | Kashif Rao |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Newark : , : John Wiley & Sons, Incorporated, , 2024 |
| Descrizione fisica | 1 online resource (160 pages) |
| Disciplina | 621.382/7 |
| Soggetto topico |
Optical communications
FiWi access networks 6G mobile communication systems |
| ISBN |
9781394230310
1394230311 9781394230303 1394230303 9781394230297 139423029X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Title Page -- Copyright -- Contents -- About the Author -- Acknowledgments -- Introduction -- Chapter 1 Introduction -- 1.1 Overview -- 1.2 Radio Frequency Communication -- 1.2.1 Limitations for Future RF Communication -- 1.2.1.1 Spectrum Congestion -- 1.2.1.2 Limited Bandwidth -- 1.2.1.3 Line‐of‐Sight Requirements -- 1.2.1.4 Signal Attenuation and Interference -- 1.2.1.5 Security Concerns -- 1.2.1.6 Energy Efficiency -- 1.3 Optical Communication -- 1.3.1 Future Opportunities for Optical Communication -- 1.3.1.1 High Data Rates -- 1.3.1.2 Low Latency -- 1.3.1.3 Large Bandwidth -- 1.3.1.4 Immunity to Electromagnetic Interference -- 1.3.1.5 Secure Communication -- 1.3.1.6 Energy Efficiency -- 1.4 Hybrid System -- 1.4.1 Scope of Hybrid Communication -- 1.4.1.1 Seamless Connectivity -- 1.4.1.2 Enhanced Reliability -- 1.4.1.3 Improved Performance -- 1.4.1.4 Flexibility and Scalability -- 1.4.1.5 Multimodal Communication -- 1.4.1.6 Advanced Applications -- 1.5 History of Visible Light Communication -- 1.5.1 Ancient Signaling Methods -- 1.5.2 Optical Telegraphs -- 1.5.3 Alexander Graham Bell's Photophone (1880) -- 1.5.4 Invention of Light Emitting Diodes (LEDs) -- 1.5.5 Early Research into VLC (1990s-2000s) -- 1.5.6 Harald Haas and Li‐Fi (2011) -- 1.5.7 Technological Advancements -- 1.5.8 Standardization Efforts -- 1.5.9 Integration with Modern Communication Systems -- 1.5.10 Current Trends and Future Prospects -- 1.6 Visible Light Communication -- 1.6.1 Problem 1 -- 1.6.1.1 Current Industry Trend -- 1.6.1.2 Possible Solution -- 1.6.2 Problem 2 -- 1.6.2.1 Current Industry Trend -- 1.6.2.2 Possible Solution -- 1.6.3 Opti Wave System Tool -- References -- Chapter 2 Visible Light Communication -- 2.1 Overview -- 2.2 Background -- 2.3 VLC for Indoor Communication -- 2.4 Opportunities and Limitations -- 2.4.1 Applications.
2.5 Modulation Techniques -- 2.5.1 On-Off Keying -- 2.5.2 Pulse Width Modulation -- 2.5.3 Pulse Position Modulation (PPM) -- 2.5.4 Orthogonal Frequency Division Multiplexing -- 2.5.5 Color Shift Keying -- 2.5.6 Optical Asymmetric Modulation -- 2.5.7 Discrete Multi‐Tone (DMT) -- 2.6 Light Fidelity and Wireless Fidelity Comparison -- 2.7 VLC Transmitter and Receiver -- 2.7.1 VLC Transmitter -- 2.7.2 VLC Receiver -- References -- Chapter 3 Radio over Fiber System -- 3.1 Overview -- 3.1.1 Direct Modulation -- 3.1.2 External Modulation -- 3.2 Radio over Fiber Link Configuration -- 3.2.1 Radio Frequency over Fiber -- 3.2.2 Intermediate Frequency over Fiber -- 3.2.3 Baseband over Fiber -- 3.2.4 Millimeter‐Wave Signal Generation -- 3.2.5 Applications -- 3.2.5.1 Satellite Communication -- 3.2.5.2 Cellular Networks -- 3.2.5.3 Transportation and Vehicles -- 3.2.5.4 Visible Light Communication -- 3.3 Radio over Fiber System‐Level Analysis -- 3.3.1 Encoding Formats -- 3.3.2 PIN and APD Photodiodes -- 3.4 Simulation -- 3.4.1 Result -- 3.5 Future Multifunctional RoF Home Network -- 3.5.1 Fiber to the Home (FTTH) -- 3.5.2 Multifrequency RoF System Design -- References -- Chapter 4 Digital Coherent Integration with Radio over Fiber -- 4.1 Digital Coherent System Analysis -- 4.1.1 DP‐QPSK Transmitter -- 4.1.2 Digital Coherent Optical Receiver -- 4.1.3 Optical Integration Technology -- 4.1.3.1 PLC Technology -- 4.1.3.2 Optical Semiconductor -- 4.1.3.3 High‐Speed Electronic Devices -- 4.1.4 Digital Signal Processing in a Coherent Receiver -- 4.2 Software Implementation -- 4.3 Digital Coherent RoF System Analysis -- 4.3.1 Proposed System Design and Analysis -- 4.3.2 Simulation -- References -- Chapter 5 Proposed Hybrid System for Indoor VLC -- 5.1 Overview -- 5.1.1 Backhaul Connection -- 5.1.2 Uplink Connectivity -- 5.2 Proposed System Design -- 5.2.1 OFDM Coherent RoF. 5.2.1.1 Architecture Design -- 5.2.2 Modeling in OptiSystem 15 -- 5.3 Proposed Auto Channel Switching Unit (ACSU) -- 5.3.1 Modeling of the Auto Channel Switching Unit (ACSU) -- 5.4 Feasibility Analysis -- 5.4.1 Technical Feasibility -- 5.4.2 Cost‐Benefits Analysis -- References -- Chapter 6 Proposed Indoor Hybrid System Modeling -- 6.1 Modeling of Indoor Hybrid System for VLC -- 6.2 VLC and RoF Indoor Downloading -- 6.3 Wi‐Fi and RoF for Indoor Purposes -- Chapter 7 Conclusion and Future Work -- 7.1 Conclusion -- 7.2 Future Work -- 7.3 Applications of VLC in 6G and Above Communication -- 7.3.1 High‐Speed Data Transfer -- 7.3.1.1 High Bandwidth -- 7.3.1.2 Spectral Efficiency -- 7.3.1.3 Short‐Range Communication -- 7.3.1.4 Low Latency -- 7.3.1.5 Integration with Existing Infrastructure -- 7.3.1.6 Security and Privacy -- 7.3.1.7 Complementary to RF Technologies -- 7.3.2 Indoor Localization and Navigation -- 7.3.2.1 Precise Positioning -- 7.3.2.2 Multilayered Positioning -- 7.3.2.3 Low Latency -- 7.3.2.4 High‐Density Deployment -- 7.3.2.5 Complementary to GPS -- 7.3.2.6 Integration with Smart Lighting -- 7.3.2.7 Privacy and Security -- 7.3.3 Augmented Reality (AR) and Virtual Reality (VR) -- 7.3.3.1 Low Latency Communication -- 7.3.3.2 High Bandwidth -- 7.3.3.3 Indoor Localization and Positioning -- 7.3.3.4 Interactive Projection Mapping -- 7.3.3.5 Gesture Recognition -- 7.3.3.6 Privacy and Security -- 7.3.3.7 Multiuser Collaboration -- 7.3.4 Smart Infrastructure and Internet of Things (IoT) -- 7.3.4.1 Smart Lighting Systems -- 7.3.4.2 Indoor Positioning and Navigation -- 7.3.4.3 Environmental Monitoring -- 7.3.4.4 Smart Retail and Hospitality -- 7.3.4.5 Smart Transportation -- 7.3.4.6 Industrial Automation -- 7.3.4.7 Energy Harvesting -- 7.3.5 Telecommunication/Wireless -- 7.3.5.1 Indoor Wireless Networking -- 7.3.5.2 Li‐Fi. 7.3.5.3 Last‐Mile Connectivity -- 7.3.5.4 Secure Communications -- 7.3.5.5 Smart Cities -- 7.3.5.6 Augmented Reality (AR) and Location‐Based Services -- 7.3.5.7 Vehicle‐to‐Infrastructure (V2I) Communication -- Chapter 8 The Role of AI and Machine Learning in 6G -- 8.1 Overview of AI and ML Concepts -- 8.1.1 Key AI and ML Concepts -- 8.2 Evolution of AI in Telecommunications -- 8.2.1 Early Adoption (1980s-1990s) -- 8.2.2 Growth Phase (2000s) -- 8.2.3 Modern Era (2010s) -- 8.2.4 Current Trends (2020s) -- 8.2.5 Future Directions (2030s and beyond) -- 8.3 Why AI and ML are Critical for 6G -- 8.4 Applications of AI and ML in Wireless Networks -- 8.4.1 Network Management and Optimization -- 8.4.2 Enhanced User Experience -- 8.4.3 Security and Fraud Detection -- 8.4.4 Predictive Maintenance and Fault Management -- 8.4.5 Advanced Communication Techniques -- 8.4.6 Edge Computing and IoT -- 8.5 6G and Visible Light Communication (VLC) -- 8.5.1 Ultrahigh‐Speed Data Transmission -- 8.5.2 Enhanced Indoor Localization and Positioning -- 8.5.3 Secure and Resilient Communication -- 8.5.4 Energy‐Efficient Networking -- 8.5.5 Overcoming RF Limitations and Interference -- Chapter 9 Future Research Directions for Visible Light Communication (VLC) in 6G Networks -- 9.1 VLC with Terahertz -- 9.1.1 Research Focus: Investigate Seamless Integration of VLC with Terahertz (THz) Communication Technologies -- 9.1.1.1 Complementary Strengths -- 9.1.1.2 Applications -- 9.1.1.3 Research Directions -- 9.2 Enhanced Modulation and Coding Schemes -- 9.2.1 Research Focus: Develop Advanced Modulation and Coding Techniques Tailored for VLC in 6G Networks -- 9.2.1.1 Key Areas of Research -- 9.3 Hybrid VLC‐RF Networks -- 9.3.1 Research Focus: Explore Hybrid Visible Light Communication (VLC) and Radio Frequency (RF) Network Architectures to Enhance Both Coverage and Reliability. 9.3.1.1 Key Points -- 9.3.1.2 Challenges -- 9.3.1.3 Potential Solutions and Approaches -- 9.3.1.4 Collaborative Communication Strategies -- 9.4 Massive MIMO and Beamforming Techniques -- 9.4.1 Research Focus: Investigate the Integration of Massive Multiple‐Input Multiple‐Output (MIMO) and Beamforming Techniques Within Visible Light Communication (VLC)‐Enabled 6G Networks -- 9.4.1.1 Key Points -- 9.4.1.2 Challenges -- 9.4.1.3 Potential Solutions and Approaches -- 9.5 Network Slicing and Service Differentiation -- 9.5.1 Research Focus: Explore Network Slicing and Service Differentiation Mechanisms Tailored for Visible Light Communication (VLC) Networks Within the Context of 6G -- 9.5.1.1 Key Points -- 9.5.1.2 Challenges -- 9.5.1.3 Potential Solutions and Approaches -- 9.5.1.4 Application Scenarios -- 9.6 Energy‐Efficient VLC Systems -- 9.6.1 Research Focus: Develop Energy‐Efficient Visible Light Communication (VLC) Systems Tailored for Sustainable 6G Networks -- 9.6.1.1 Key Points -- 9.6.1.2 Challenges -- 9.6.1.3 Potential Solutions and Approaches -- 9.6.1.4 Application Scenarios -- 9.7 Security and Privacy Enhancements -- 9.7.1 Research Focus: Investigate Advanced Security and Privacy Mechanisms Specifically Designed for Visible Light Communication (VLC) in 6G Networks -- 9.7.1.1 Key Points -- 9.7.1.2 Challenges -- 9.7.1.3 Potential Solutions and Approaches -- 9.7.1.4 Application Scenarios -- Index -- EULA. |
| Record Nr. | UNINA-9911020332703321 |
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Kashif Rao
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| Newark : , : John Wiley & Sons, Incorporated, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Intelligent Spectrum Management : Towards 6G
| Intelligent Spectrum Management : Towards 6G |
| Autore | Iyer Sridhar |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Newark : , : John Wiley & Sons, Incorporated, , 2025 |
| Descrizione fisica | 1 online resource (307 pages) |
| Disciplina | 621.3845/6 |
| Altri autori (Persone) |
KallaAnshuman
LopezOnel Alcaraz De AlwisChamitha |
| Soggetto topico |
Radio frequency allocation - Management
6G mobile communication systems Mobile communication systems Artificial intelligence |
| ISBN |
9781394201228
1394201222 9781394201211 1394201214 9781394201235 1394201230 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9911018942203321 |
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Iyer Sridhar
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| Newark : , : John Wiley & Sons, Incorporated, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Intelligent Surfaces Empowered 6G Wireless Network / / edited by Qingqing Wu [and four others]
| Intelligent Surfaces Empowered 6G Wireless Network / / edited by Qingqing Wu [and four others] |
| Edizione | [First edition.] |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : John Wiley & Sons, Inc., , [2024] |
| Descrizione fisica | 1 online resource (365 pages) |
| Disciplina | 621.38456 |
| Soggetto topico |
6G mobile communication systems
Smart materials Surfaces (Technology) |
| ISBN |
1-119-91310-1
1-119-91312-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Title Page -- Copyright -- Contents -- About the Editors -- List of Contributors -- Preface -- Acknowledgement -- Part I Fundamentals of IRS -- Chapter 1 Introduction to Intelligent Surfaces -- 1.1 Background -- 1.2 Concept of Intelligent Surfaces -- 1.3 Advantages of Intelligence Surface -- 1.4 Potential Applications -- 1.5 Conclusion -- Bibliography -- Chapter 2 IRS Architecture and Hardware Design -- 2.1 Metamaterials: Basics of IRS -- 2.2 Programmable Metasurfaces -- 2.3 IRS Hardware Design -- 2.3.1 IRS System Architecture -- 2.3.2 IRS Element Design -- 2.3.3 IRS Array Design -- 2.3.4 IRS Controller Design -- 2.3.5 Full‐Wave Simulation and Field Test -- 2.4 State‐of‐the‐Art IRS Prototype -- 2.4.1 Passive IRS Prototype by Tsinghua -- 2.4.2 Active IRS Prototype by Tsinghua -- 2.4.3 IRS Modulation Prototype by SEU -- 2.4.3.1 Transmitter Design -- 2.4.3.2 Frame Structure Design -- 2.4.3.3 Receiver Design -- 2.4.3.4 System Design -- 2.4.4 Transmissive IRS Prototype by MIT -- 2.4.5 IRS Prototype by China Mobile -- 2.4.6 IRS Prototype by DOCOMO -- Bibliography -- Chapter 3 On Path Loss and Channel Reciprocity of RIS‐Assisted Wireless Communications -- 3.1 Introduction -- 3.2 Path Loss Modeling and Channel Reciprocity Analysis -- 3.2.1 System Description -- 3.2.2 General Path Loss Model -- 3.2.3 Path Loss Models for Typical Scenarios -- 3.2.4 Discussion on RIS Path Loss and Channel Reciprocity -- 3.3 Path Loss Measurement and Channel Reciprocity Validation -- 3.3.1 Two Fabricated RISs -- 3.3.2 Two Measurement Systems -- 3.3.3 Validation of RIS Path Loss Models -- 3.3.4 Validation of RIS Channel Reciprocity -- 3.4 Conclusion -- 3.A Appendix -- 3.A.1 Proof of Theorem 3.1 -- Bibliography -- Chapter 4 Intelligent Surface Communication Design: Main Challenges and Solutions -- 4.1 Introduction -- 4.2 Channel Estimation.
4.2.1 Problem Description and Challenges -- 4.2.2 Semi‐Passive IRS Channel Estimation -- 4.2.3 Fully‐Passive IRS Channel Estimation -- 4.3 Passive Beamforming Optimization -- 4.3.1 IRS‐aided SISO System: Passive Beamforming Basics and Power Scaling Order -- 4.3.2 IRS‐aided MISO System: Joint Active and Passive Beamforming -- 4.3.3 IRS‐Aided MIMO System -- 4.3.4 IRS‐Aided OFDM System -- 4.3.5 Passive Beamforming with Discrete Reflection Amplitude and Phase Shift -- 4.3.6 Other Related Works and Future Directions -- 4.4 IRS Deployment -- 4.4.1 IRS Deployment Optimization at the Link Level -- 4.4.1.1 Optimal Deployment of Single IRS -- 4.4.1.2 Single IRS versus Multiple Cooperative IRSs -- 4.4.1.3 LoS versus Non‐LoS (NLoS) -- 4.4.2 IRS Deployment at the Network Level: Distributed or Centralized? -- 4.4.3 Other Related Work and Future Direction -- 4.5 Conclusion -- Bibliography -- Part II IRS for 6G Wireless Systems -- Chapter 5 Overview of IRS for 6G and Industry Advance -- 5.1 IRS for 6G -- 5.1.1 Potential Use Cases -- 5.1.1.1 Indoor Use Cases -- 5.1.1.2 Outdoor Use Cases -- 5.1.2 Deployment Scenarios -- 5.2 Industrial Progresses -- 5.2.1 Funded Projects -- 5.2.2 White Papers -- 5.2.3 Prototyping and Testing -- 5.2.4 Standardization Progress -- Bibliography -- Chapter 6 RIS‐Aided Massive MIMO Antennas* -- 6.1 Introduction -- 6.1.0 Notation -- 6.2 System Model -- 6.2.1 Channel Model -- 6.2.2 Active Antenna Configuration -- 6.3 Uplink/Downlink Signal Processing -- 6.3.1 Uplink Channel Estimation -- 6.3.2 Downlink Data Transmission -- 6.4 Performance Measures -- 6.4.1 SINR and Spectral Efficiency under Perfect Channel State Information (CSI) -- 6.4.2 SINR and Spectral Efficiency under Imperfect Channel State Information (CSI) -- 6.4.2.1 The Upper‐Bound (UB) to the System Performance -- 6.4.2.2 The Hardening Lower‐Bound (LB) to System Performance. 6.5 Optimization of the RIS Phase Shifts -- 6.6 Numerical Results -- 6.7 Conclusions -- 6.A Appendix -- Bibliography -- Chapter 7 Localization, Sensing, and Their Integration with RISs -- 7.1 Introduction -- 7.1.1 Localization in 5G -- 7.1.2 RIS Key Advantages -- 7.1.2.1 Localization -- 7.1.2.2 Sensing -- 7.2 RIS Types and Channel Modeling -- 7.2.1 RIS Hardware Architectures -- 7.2.2 RIS‐Parameterized Channel Models -- 7.2.2.1 Geometric Channel Model -- 7.2.2.2 Stochastic Channel Modeling -- 7.3 Localization with RISs -- 7.3.1 Fundamentals on Localization -- 7.3.2 Localization with Reflective RISs -- 7.3.3 Localization with a Single STAR‐RIS -- 7.3.4 Localization with Multiple Receiving RISs -- 7.4 Sensing with RISs -- 7.4.1 Link Budget Analysis -- 7.4.1.1 Monostatic Radar Sensing -- 7.4.1.2 Bistatic Radar Sensing -- 7.4.2 Joint Sensing and Localization with a Single RIS -- 7.4.2.0 UE and Landmark Estimates -- 7.5 Conclusion and Open Challenges -- Bibliography -- Chapter 8 IRS‐Aided THz Communications -- 8.1 IRS‐Aided THz MIMO System Model -- 8.2 Beam Training Protocol -- 8.3 IRS Prototyping -- 8.3.1 Active Beam Steering at THz transceivers -- 8.3.2 Passive Beam Steering on THz IRS -- 8.3.3 Codebook Design for Beam Scanning -- 8.3.4 Beam‐Scanning Reflectarray -- 8.4 IRS‐THz Communication Applications -- 8.4.1 High Speed Fronthaul/Backhaul -- 8.4.2 Cellular Connected Drones -- 8.4.3 Wireless Data Center -- 8.4.4 Enhanced Indoor Coverage -- 8.4.5 Vehicular Communications -- 8.4.6 Physical‐Layer Security -- Bibliography -- Chapter 9 Joint Design of Beamforming, Phase Shifting, and Power Allocation in a Multi‐cluster IRS‐NOMA Network -- 9.1 Introduction -- 9.1.1 Previous Works -- 9.1.2 Motivation and Challenge -- 9.2 System Model and Problem Formulation -- 9.2.1 System Model -- 9.2.2 Problem Formulation -- 9.3 Alternating Algorithm. 9.3.1 Beamforming Optimization -- 9.3.2 Phase‐Shift Feasibility -- 9.3.3 Algorithm Design -- 9.4 Simulation Result -- 9.5 Conclusion -- Bibliography -- Chapter 10 IRS‐Aided Mobile Edge Computing: From Optimization to Learning -- 10.1 Introduction -- 10.2 System Model and Objective -- 10.3 Optimization‐Based Approaches to IRS‐Aided MEC -- 10.3.1 IRS Reflecting Coefficients Design -- 10.3.2 Receive Beamforming Design -- 10.3.3 Energy Partition Optimization -- 10.3.4 Convergence and Complexity -- 10.4 Deep Learning Approaches to IRS‐Aided MEC -- 10.4.1 CSI‐Based Learning Architecture -- 10.4.2 Location‐Only Learning Architecture -- 10.4.3 Input Feature Uncertainty -- 10.4.4 Comparison Between the CSI‐Based and CSI‐Free Learning Architectures -- 10.4.5 Complexity Reduction via Learning -- 10.5 Comparative Evaluation Results -- 10.5.1 Scenario Without LoS Direct Links -- 10.5.2 Scenario with Strong LoS Direct Links -- 10.6 Conclusions -- Bibliography -- Chapter 11 Interference Nulling Using Reconfigurable Intelligent Surface -- 11.1 Introduction -- 11.2 System Model -- 11.3 Interference Nulling via RIS -- 11.3.1 Feasibility of Interference Nulling -- 11.3.2 Alternating Projection Algorithm -- 11.3.3 Simulation Results -- 11.4 Learning to Minimize Interference -- 11.4.1 Learning to Initialize -- 11.4.2 Simulation Results -- 11.5 Conclusions -- Bibliography -- Chapter 12 Blind Beamforming for IRS Without Channel Estimation -- 12.1 Introduction -- 12.2 System Model -- 12.3 Random‐Max Sampling (RMS) -- 12.4 Conditional Sample Mean (CSM) -- 12.5 Some Comments on CSM -- 12.5.1 Connection to Closest Point Projection -- 12.5.2 Connection to Phase Retrieval -- 12.5.3 CSM for General Utility Functions -- 12.6 Field Tests -- 12.7 Conclusion -- Bibliography -- Chapter 13 RIS in Wireless Information and Power Transfer -- 13.1 Introduction -- 13.1.1 WPT and WIPT. 13.1.2 RIS -- 13.1.3 RIS in WPT and WIPT -- 13.2 RIS‐Aided WPT -- 13.2.1 WPT Architecture -- 13.2.2 Waveform and Beamforming -- 13.2.3 Channel Acquisition -- 13.2.3.1 Direct Channel -- 13.2.3.2 RIS‐Related Channels -- 13.2.4 Prototype and Experiments -- 13.3 RIS‐Aided WIPT -- 13.3.1 WIPT Categories -- 13.3.2 RIS‐Aided SWIPT -- 13.3.2.1 SWIPT Architecture -- 13.3.2.2 Waveform and Beamforming -- 13.3.2.3 Channel Acquisition -- 13.3.3 RIS‐Aided WPCN and WPBC -- 13.4 Conclusion -- Bibliography -- Chapter 14 Beamforming Design for Self‐Sustainable IRS‐Assisted MISO Downlink Systems -- 14.1 Introduction -- 14.2 System Model -- 14.2.1 Self‐Sustainable IRS Model -- 14.2.2 Channel and Signal Models -- 14.2.3 Power Harvesting Model at the IRS -- 14.3 Problem Formulation -- 14.4 Solution -- 14.4.1 Problem Transformation -- 14.4.2 Address the Coupling Variables and Binary Variables -- 14.4.3 Successive Convex Approximation -- 14.5 Numerical Results -- 14.6 Summary -- 14.7 Further Extension -- Bibliography -- Chapter 15 Optical Intelligent Reflecting Surfaces -- 15.1 Introduction -- 15.2 System and Channel Model -- 15.2.1 IRS Model -- 15.2.2 Transmitter and Receiver Model -- 15.2.3 Channel Model -- 15.3 Communication Theoretical Modeling of Optical IRSs -- 15.3.1 Scattering Theory -- 15.3.1.1 Incident Beam on the IRS -- 15.3.1.2 Huygens-Fresnel Principle -- 15.3.1.3 Intermediate‐Field Versus Far‐Field -- 15.3.1.4 Received Power Density -- 15.3.2 Geometric Optics -- 15.3.2.1 Equivalent Mirror‐Assisted Analysis -- 15.3.2.2 Received Power Density -- 15.4 Design of Optical IRSs for FSO Systems -- 15.4.1 IRS‐Assisted Point‐to‐Point System -- 15.4.1.1 IRS Phase‐Shift Profile Φ(r,rt) -- 15.4.1.2 IRS Efficiency ζ -- 15.4.2 IRS‐Assisted Multi‐Link System -- 15.4.2.1 Time Division Protocol -- 15.4.2.2 IRS Division Protocol -- 15.4.2.3 IRS Homogenization Protocol. 15.5 Simulation Results. |
| Record Nr. | UNINA-9910830726203321 |
| Hoboken, New Jersey : , : John Wiley & Sons, Inc., , [2024] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Next Generation Multiple Access
| Next Generation Multiple Access |
| Autore | Liu Yuanwei |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Newark : , : John Wiley & Sons, Incorporated, , 2024 |
| Descrizione fisica | 1 online resource (624 pages) |
| Disciplina | 004.62 |
| Altri autori (Persone) |
LiuLiang
DingZhiguo ShenXuemin |
| Soggetto topico |
6G mobile communication systems
Multiple access protocols (Computer network protocols) |
| ISBN |
9781394180523
1394180527 9781394180509 1394180500 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Title Page -- Copyright -- Contents -- About the Editors -- List of Contributors -- Preface -- Acknowledgments -- Chapter 1 Next Generation Multiple Access Toward 6G -- 1.1 The Road to NGMA -- 1.2 Non‐Orthogonal Multiple Access -- 1.3 Massive Access -- 1.4 Book Outline -- Part I Evolution of NOMA Towards NGMA -- Chapter 2 Modulation Techniques for NGMA/NOMA -- 2.1 Introduction -- 2.2 Space‐Domain IM for NGMA -- 2.2.1 SM‐Based NOMA -- 2.2.1.1 Multi‐RF Schemes -- 2.2.1.2 Single‐RF Schemes -- 2.2.1.3 Recent Developments in SM‐NOMA -- 2.2.2 RSM‐Based NOMA -- 2.2.3 SM‐Aided SCMA -- 2.3 Frequency‐Domain IM for NGMA -- 2.3.1 NOMA with Frequency‐Domain IM -- 2.3.1.1 OFDM‐IM NOMA -- 2.3.1.2 DM‐OFDM NOMA -- 2.3.2 C‐NOMA with Frequency‐Domain IM -- 2.3.2.1 Broadcast Phase -- 2.3.2.2 Cooperative Phase -- 2.4 Code‐Domain IM for NGMA -- 2.4.1 CIM‐SCMA -- 2.4.2 CIM‐MC‐CDMA -- 2.5 Power‐Domain IM for NGMA -- 2.5.1 Transmission Model -- 2.5.1.1 Two‐User Case -- 2.5.1.2 Multiuser Case -- 2.5.2 Signal Decoding -- 2.5.3 Performance Analysis -- 2.6 Summary -- References -- Chapter 3 NOMA Transmission Design with Practical Modulations -- 3.1 Introduction -- 3.2 Fundamentals -- 3.2.1 Multichannel Downlink NOMA -- 3.2.2 Practical Modulations in NOMA -- 3.3 Effective Throughput Analysis -- 3.3.1 Effective Throughput of the Single‐User Channels -- 3.3.2 Effective Throughput of the Two‐User Channels -- 3.4 NOMA Transmission Design -- 3.4.1 Problem Formulation -- 3.4.2 Power Allocation -- 3.4.2.1 Power Allocation within Channels -- 3.4.2.2 Power Budget Allocation Among Channels -- 3.4.3 Joint Resource Allocation -- 3.5 Numerical Results -- 3.6 Conclusion -- References -- Chapter 4 Optimal Resource Allocation for NGMA -- 4.1 Introduction -- 4.2 Single‐Cell Single‐Carrier NOMA -- 4.2.1 Total Power Minimization Problem -- 4.2.2 Sum‐Rate Maximization Problem.
4.2.3 Energy‐Efficiency Maximization Problem -- 4.2.4 Key Features and Implementation Issues -- 4.2.4.1 CSI Insensitivity -- 4.2.4.2 Rate Fairness -- 4.3 Single‐Cell Multicarrier NOMA -- 4.3.1 Total Power Minimization Problem -- 4.3.2 Sum‐Rate Maximization Problem -- 4.3.3 Energy‐Efficiency Maximization Problem -- 4.3.4 Key Features and Implementation Issues -- 4.4 Multi‐cell NOMA with Single‐Cell Processing -- 4.4.1 Dynamic Decoding Order -- 4.4.1.1 Optimal JSPA for Total Power Minimization Problem -- 4.4.1.2 Optimal JSPA for Sum‐Rate Maximization Problem -- 4.4.1.3 Optimal JSPA for EE Maximization Problem -- 4.4.2 Static Decoding Order -- 4.4.2.1 Optimal FRPA for Total Power Minimization Problem -- 4.4.2.2 Optimal FRPA for Sum‐Rate Maximization Problem -- 4.4.2.3 Optimal FRPA for EE Maximization Problem -- 4.4.2.4 Optimal JRPA for Total Power Minimization Problem -- 4.4.2.5 Suboptimal JRPA for Sum‐Rate Maximization Problem -- 4.4.2.6 Suboptimal JRPA for EE Maximization Problem -- 4.5 Numerical Results -- 4.5.1 Approximated Optimal Powers -- 4.5.2 SC‐NOMA versus FDMA-NOMA versus FDMA -- 4.5.3 Multi‐cell NOMA: JSPA versus JRPA versus FRPA -- 4.6 Conclusions -- Acknowledgments -- References -- Chapter 5 Cooperative NOMA -- 5.1 Introduction -- 5.2 System Model for D2MD‐CNOMA -- 5.2.1 System Configuration -- 5.2.2 Channel Model -- 5.3 Adaptive Aggregate Transmission -- 5.3.1 First Phase -- 5.3.2 Second Phase -- 5.4 Performance Analysis -- 5.4.1 Outage Probability -- 5.4.2 Ergodic Sum Capacity -- 5.5 Numerical Results and Discussion -- 5.5.1 Outage Probability -- 5.5.2 Ergodic Sum Capacity -- 5.A.1 Proof of Theorem 5.1 -- References -- Chapter 6 Multi‐scale‐NOMA: An Effective Support to Future Communication-Positioning Integration System -- 6.1 Introduction -- 6.2 Positioning in Cellular Networks -- 6.3 MS‐NOMA Architecture -- 6.4 Interference Analysis. 6.4.1 Single‐Cell Network -- 6.4.1.1 Interference of Positioning to Communication -- 6.4.1.2 Interference of Communication to Positioning -- 6.4.2 Multicell Networks -- 6.4.2.1 Interference of Positioning to Communication -- 6.4.2.2 Interference of Communication to Positioning -- 6.5 Resource Allocation -- 6.5.1 The Constraints -- 6.5.1.1 The BER Threshold Under QoS Constraint -- 6.5.1.2 The Total Power Limitation -- 6.5.1.3 The Elimination of Near‐Far Effect -- 6.5.2 The Proposed Joint Power Allocation Model -- 6.5.3 The Positioning-Communication Joint Power Allocation Scheme -- 6.5.4 Remarks -- 6.6 Performance Evaluation -- 6.6.1 Communication Performance -- 6.6.2 Ranging Performance -- 6.6.3 Resource Consumption of Positioning -- 6.6.3.1 Achievable Positioning Measurement Frequency -- 6.6.3.2 The Resource Element Consumption -- 6.6.3.3 The Power Consumption -- 6.6.4 Positioning Performance -- 6.6.4.1 Comparison by Using CP4A and the Traditional Method -- 6.6.4.2 Comparision Between MS‐NOMA and PRS -- References -- Chapter 7 NOMA‐Aware Wireless Content Caching Networks -- 7.1 Introduction -- 7.2 System Model -- 7.2.1 System Description -- 7.2.2 Content Request Model -- 7.2.3 Random System State -- 7.2.4 System Latency Under Each Random State -- 7.2.5 System's Average Latency -- 7.3 Algorithm Design -- 7.3.1 User Pairing and Power Control Optimization -- 7.3.2 Cache Placement -- 7.3.3 Recommendation Algorithm -- 7.3.4 Joint Optimization Algorithm and Property Analysis -- 7.4 Numerical Simulation -- 7.4.1 Convergence Performance -- 7.4.2 System's Average Latency -- 7.4.3 Cache Hit Ratio -- 7.5 Conclusion -- References -- Chapter 8 NOMA Empowered Multi‐Access Edge Computing and Edge Intelligence -- 8.1 Introduction -- 8.2 Literature Review -- 8.3 System Model and Formulation -- 8.3.1 Modeling of Two‐Sided Dual Offloading. 8.3.2 Overall Latency Minimization -- 8.4 Algorithms for Optimal Offloading -- 8.5 Numerical Results -- 8.6 Conclusion -- Acknowledgments -- References -- Chapter 9 Exploiting Non‐orthogonal Multiple Access in Integrated Sensing and Communications -- 9.1 Introduction -- 9.2 Developing Trends and Fundamental Models of ISAC -- 9.2.1 ISAC: From Orthogonality to Non‐orthogonality -- 9.2.2 Downlink ISAC -- 9.2.3 Uplink ISAC -- 9.3 Novel NOMA Designs in Downlink and Uplink ISAC -- 9.3.1 NOMA‐Empowered Downlink ISAC Design -- 9.3.2 Semi‐NOMA‐Based Uplink ISAC Design -- 9.4 Case Study: System Model and Problem Formulation -- 9.4.1 System Model -- 9.4.1.1 Communication Model -- 9.4.1.2 Sensing Model -- 9.4.2 Problem Formulation -- 9.5 Case Study: Proposed Solutions -- 9.6 Case Study: Numerical Results -- 9.6.1 Convergence of Algorithm 9.1 -- 9.6.2 Baseline -- 9.6.3 Transmit Beampattern -- 9.7 Conclusions -- References -- Part II Massive Access for NGMA -- Chapter 10 Capacity of Many‐Access Channels -- 10.1 Introduction -- 10.2 The Many‐Access Channel Model -- 10.3 Capacity of the MnAC -- 10.3.1 The Equal‐Power Case -- 10.3.2 Heterogeneous Powers and Fading -- 10.4 Energy Efficiency of the MnAC -- 10.4.1 Minimum Energy per Bit for Given PUPE -- 10.4.2 Capacity per Unit‐Energy Under Different Error Criteria -- 10.5 Discussion and Open Problems -- 10.5.1 Scaling Regime -- 10.5.2 Some Practical Issues -- Acknowledgments -- References -- Chapter 11 Random Access Techniques for Machine‐Type Communication -- 11.1 Fundamentals of Random Access -- 11.1.1 Coordinated Versus Uncoordinated Transmissions -- 11.1.2 Random Access Techniques -- 11.1.2.1 ALOHA Protocols -- 11.1.2.2 CSMA -- 11.1.3 Re‐transmission Strategies -- 11.2 A Game Theoretic View -- 11.2.1 A Model -- 11.2.2 Fictitious Play -- 11.3 Random Access Protocols for MTC -- 11.3.1 4‐Step Random Access. 11.3.2 2‐Step Random Access -- 11.3.3 Analysis of 2‐Step Random Access -- 11.3.4 Fast Retrial -- 11.4 Variants of 2‐Step Random Access -- 11.4.1 2‐Step Random Access with MIMO -- 11.4.2 Sequential Transmission of Multiple Preambles -- 11.4.3 Simultaneous Transmission of Multiple Preambles -- 11.4.4 Preambles for Exploration -- 11.5 Application of NOMA to Random Access -- 11.5.1 Power‐Domain NOMA -- 11.5.2 S‐ALOHA with NOMA -- 11.5.3 A Generalization with Multiple Channels -- 11.5.4 NOMA‐ALOHA Game -- 11.6 Low‐Latency Access for MTC -- 11.6.1 Long Propagation Delay -- 11.6.2 Repetition Diversity -- 11.6.3 Channel Coding‐Based Random Access -- References -- Chapter 12 Grant‐Free Random Access via Compressed Sensing: Algorithm and Performance -- 12.1 Introduction -- 12.2 Joint Device Detection, Channel Estimation, and Data Decoding with Collision Resolution for MIMO Massive Unsourced Random Access -- 12.2.1 System Model and Encoding Scheme -- 12.2.1.1 System Model -- 12.2.1.2 Encoding Scheme -- 12.2.2 Collision Resolution Protocol -- 12.2.3 Decoding Scheme -- 12.2.3.1 Joint DAD‐CE Algorithm -- 12.2.3.2 MIMO‐LDPC‐SIC Decoder -- 12.2.4 Experimental Results -- 12.3 Exploiting Angular Domain Sparsity for Grant‐Free Random Access: A Hybrid AMP Approach -- 12.3.1 Sparse Modeling of Massive Access -- 12.3.2 Recovery Algorithm -- 12.3.2.1 Application to Unsourced Random Access -- 12.3.3 Experimental Results -- 12.4 LEO Satellite‐Enabled Grant‐Free Random Access -- 12.4.1 System Model -- 12.4.1.1 Channel Model -- 12.4.1.2 Signal Modulation -- 12.4.1.3 Problem Formulation -- 12.4.2 Pattern Coupled SBL Framework -- 12.4.2.1 The Pattern‐Coupled Hierarchical Prior -- 12.4.2.2 SBL Framework -- 12.4.3 Experimental Results -- 12.5 Concluding Remarks -- Acknowledgments -- References -- Chapter 13 Algorithm Unrolling for Massive Connectivity in IoT Networks. 13.1 Introduction. |
| Record Nr. | UNINA-9911020068103321 |
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Liu Yuanwei
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| Newark : , : John Wiley & Sons, Incorporated, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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