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This book presents novel RIS-Based Smart Radio techniques, targeting at achieving high-quality channel links in cellular communications via design and optimization of the RIS construction. Unlike traditional antenna arrays, three unique characteristics of  the RIS will be revealed in this book. First, the built-in programmable configuration of the RIS enables analog beamforming inherently without extra hardware or signal processing. Second, the incident signals can be controlled to partly reflect and partly transmit through the RIS simultaneously, adding more flexibility to signal transmission. Third, the RIS has no digital processing capability to actively send signals nor any radio frequency (RF) components. As such, it is necessary to develop novel channel estimation and communication protocols, design joint digital and RIS-based analog beamforming schemes and perform interference control via mixed reflection and transmission. This book also investigates how to integrate the RIS to legacy communication systems. 
RIS techniques are further investigated in this book (benefited from its ability to actively shape the propagation environment) to achieve two types of wireless applications, i.e., RF sensing and localization. The influence of the sensing objectives on the wireless signal propagation can be potentially recognized by the receivers, which are then utilized to identify the objectives in RF sensing. Unlike traditional sensing techniques, RIS-aided sensing can actively customize the wireless channels and generate a favorable massive number of independent paths interacting with the sensing objectives. It is desirable to design RIS-based sensing algorithms, and optimize RIS configurations. For the second application, i.e., RIS aided localization, an RIS is deployed between the access point (AP) and users. The AP can then analyze reflected signals from users via different RIS configurations to obtain accurate locations of users. However, this is a challenging task due to the dynamic user topology, as well as the mutual influence between multiple users and the RIS. Therefore, the operations of the RIS, the AP, and multiple users need to be carefully coordinated. A new RIS-based localization protocol for device cooperation and an RIS configuration optimization algorithm are also required. 
This book targets researchers and graduate-level students focusing on communications and networks. Signal processing engineers, computer and information scientists, applied mathematicians and statisticians, who work in RIS research and development will also find this book useful.

Reconfigurable Intelligent Surface-Empowered 6G

1 Introductions and Basics1.1 Background and Requirements1.2 Overview of RISs1.2.1 History of Meta-materials1.2.2 Working Principles1.2.3 Applications of RISs1.3 Fundamentals of RIS-aided Wireless Communications1.3.1 Response Model1.3.2 Channel Model1.3.3 Comparisons with Existing TechniquesReferences2 RIS Aided MIMO Communications2.1 Limited Phase Shifts: How Many Phase Shifts Are Enough?2.1.1 Motivations2.1.2 System Model2.1.3 Achievable Data Rate Analysis2.1.4 Analysis on the Number of Phase Shifts2.1.5 Simulation Results2.1.6 Summary2.1.7 Appendix2.2 Size Effect: How Many Reflective Elements Do We Need?2.2.1 Motivation2.2.2 System Model2.2.3 Analysis on Asymptotic Capacity2.2.4 Analysis on the Number of Reflective Elements2.2.5 Simulation Results2.2.6 Summary2.3 Coverage Extension: RIS Orientation and Location Optimization2.3.1 Motivations2.3.2 System Model2.3.3 Cell Coverage Analysis2.3.4 RIS Placement Optimization2.3.5 Simulation Results2.3.6 Summary2.4 Hybrid Beamforming Design2.4.1 Motivations2.4.2 System Model2.4.3 RIS-based Hybrid Beamforming and Problem Formulation for Multi-user Communications 2.4.4 Sum Rate Maximization Algorithm Design2.4.5 Performance Analysis of RIS-based Multi-userCommunications2.4.6 Simulation Results2.4.7 Summary2.5 Full-dimensional Coverage Extension2.5.1 Motivations2.5.2 Intelligent Omni-Surface2.5.3 System model2.5.4 Problem Formulation and Decomposition2.5.5 Sum-rate Maximization: Algorithm Design2.5.6 Performance Analysis of the IOS-Assisted Communication System2.5.7 Simulation Results2.5.8 SummaryReferences3 Convergences of RISs with Existing Wireless Technologies3.1 RIS Aided Device-to-Device Communications3.1.1 Motivations 3.1.2 System Model3.1.3 Problem Formulation3.1.4 Sum Rate Maximization Algorithm3.1.5 Performance Evaluation3.1.6 Summary3.2 RIS Aided Cell-free MIMO3.2.1 Motivations3.2.2 System Model3.2.3 Hybrid Beamforming and Problem Formulation3.2.4 Energy Efficiency Maximization Algorithm Design3.2.5 Theoretical Analysis of RIS Aided Cell-free System3.2.6 Simulation Results3.2.7 Summary 3.2.8 Appendix 3.3 RIS Aided Spatial Equalization3.3.1 Motivations3.3.2 System Model3.3.3 Problem Formulation3.3.4 Algorithm Design3.3.5 Simulation Results3.3.6 Summary3.3.7 AppendixReferences4 RIS Aided RF Sensing and Localization4.1 2D Sensing4.1.1 Motivations4.1.2 System Design4.1.3 Problem Formulation of RIS-based Posture Recognition4.1.4 Algorithms for Configuration Matrix and Decision Function Optimizations4.1.5 Performance Analysis 4.1.6 System Implementation4.1.7 Simulation and Experimental Results4.1.8 Summary4.1.9 Appendix 4.2 3D Sensing4.2.1 Motivations4.2.2 System Model4.2.3 Problem Formulation4.2.4 Algorithm Design4.2.5 Algorithm Analysis4.2.6 Simulation and Evaluation4.2.7 Summary4.3 Indoor Localization4.3.1 Motivations4.3.2 Related Work4.3.3 System Overview4.3.4 Radio Map Preparation Phase4.3.5 Fine-grained Localization Phase4.3.6 Implementation4.3.7 Evaluation4.3.8 Discussion4.3.9 SummaryReferences