Intelligent Surfaces Empowered 6G Wireless Network / / edited by Qingqing Wu [and four others]

• Pubblicazione: Hoboken, New Jersey : , : John Wiley & Sons, Inc., , [2024]; ©2024
• Edizione: First edition.
• Descrizione fisica: 1 online resource (365 pages)
• Disciplina: 621.38456
• Soggetto topico: 6G mobile communication systems; Smart materials; Surfaces (Technology)
• Persona (resp. second.): WuQingqing (Professor)
• Nota di bibliografia: Includes bibliographical references and index.
• 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.
• Titolo autorizzato: Intelligent Surfaces Empowered 6G Wireless Network
• ISBN: 1-119-91310-1; 1-119-91312-8
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910830726203321
• Lo trovi qui: Univ. Federico II