Название: Intelligent Reconfigurable Surfaces (IRS) for Prospective 6G Wireless NetworksАвтор: Muhammad Ali Imran, Lina Mohjazi, Tie Jun Cui
Издательство: Wiley-IEEE Press
Год: 2023
Страниц: 296
Язык: английский
Формат: pdf (true), epub
Размер: 36.5 MB
Authoritative resource covering preliminary concepts and advanced concerns in the field of IRS and its role in 6G wireless systems.
Intelligent Reconfigurable Surfaces (IRS) for Prospective 6G Wireless Networks provides an in-depth treatment of the fundamental physics behind reconfigurable metasurfaces, also known as intelligent reflecting surfaces (IRS), and outlines the research roadmap towards their development as a low-complexity and energy-efficient solution aimed at turning the wireless environment into a software-defined entity.
The text demonstrates IRS from different angles, including the underlying physics, hardware architecture, operating principles, and prototype designs. It enables readers to grasp the knowledge of the interplay of IRS and state-of-the-art technologies, examining the advantages, key principles, challenges, and potential use-cases. Practically, it equips readers with the fundamental knowledge of the operational principles of reconfigurable metasurfaces, resulting in its potential applications in various intelligent, autonomous future wireless communication technologies.
To aid in reader comprehension, around 50 figures, tables, illustrations, and photographs to comprehensively present the material are also included.
Edited by a team of highly qualified professionals in the field, sample topics covered are as follows
Evolution of antenna arrays design, introducing the fundamental principles of antenna theory and reviewing the stages of development of the field;
Beamforming design for IRS-assisted communications, discussing optimal IRS configuration in conjunction with overviewing novel beamforming designs;
Reconfigurable metasurfaces from physics to applications, discussing the working principles of tunable/reconfigurable metasurfaces and their capabilities and functionalities;
IRS hardware architectures, detailing the general hardware architecture of IRS and features related to the IRS’s main operational principle;
Wireless communication systems assisted by IRS, discussing channel characterization, system integration, and aspects related to the performance analysis and network optimization of state-of-the-art wireless applications.
This book is aimed to be a solid foundation for the theoretical investigation and practical implementation of IRS‐enabled wireless networks. The book is envisioned to be a concrete reference for students, researchers, university professors, and industrial people working in the field of intelligent surfaces, in which they can exploit it to identify open research problems, and hence steer their research and industrial activities in those directions. With the diverse aspects studied in our book, we look forward to facilitating a smooth comprehension of the preliminary concepts, as well as providing solid answers to more advanced critical concerns raised in the field of IRS.
Chapter 2 discusses the fundamental principles of IRS‐aided communications and provides an analysis on the near‐field region, wherein the channel modelling and phase shift design problems differ from those in the far‐field. Specifically, the chapter highlights the impact of beamfocusing in manipulating the emitted EM waves to achieve desired signal propagation. This chapter also investigates IRS‐aided MIMO communications and the relationship between the number of reflecting elements and the achieved energy efficiency gains.
In Chapter 3, the potential of deploying IRSs in merging non‐terrestrial networks (NTNs) is explored. This is linked with discussions related to 3GPP standardization guidelines in the context of the various operational aspects, architecture types, and connectivity mechanisms in NTN. Additionally, this chapter highlights how IRSs can be integrated in NTN to enable a typical mobile handset to directly communicate with satellites.
Chapter 4 introduces a new concept called the Internet of MetaMaterial Things (IoMMT), where artificial materials with real‐time tunable physical properties can be interconnected to form a network to realize communication through software‐controlled EM, acoustic, and mechanical energy waves. After exploring the means for abstracting the complex physics behind these materials, their integration into the IoT world is discussed. The chapter presents two novel software categories for the material things, namely the meta‐material Application Programming Interface and Meta‐material Middleware, which will be in charge of the application and physical domain.
Chapter 5 overviews the general hardware architecture of IRS that opened a new platform to dynamically manipulate EM waves. This includes describing the design of an IRS structure based on different categorizations. The available IRS modes of operation will be discussed in deployments relevant to wireless communication systems. The chapter also discusses the hardware aspects and features related to the IRS's main operational principles: reconfigurability, interconnection, computing, networking, programmability, and sensing. This chapter reviews the state‐of‐the‐art on advancements in IRS prototype designs for wavefront manipulation and information modulation.
In Chapter 6, the authors discusses practical design considerations for IRS. Specifically, the tunability of the IRS unit‐cell elements will be explained. Also, the biasing network of an IRS, which provides a means of control over the individual unit cell reflection characteristics, will be detailed. The chapter will provide a comprehensive treatment on the physical limitations of the IRSs including the trade‐off between the bandwidth and phase resolution, the incidence angle response, and the quantization effects.
Chapter 7 explores channel modelling frameworks for facilitating a thorough and accurate evaluation of the system performance of IRS‐aided communications operating in the mmWave and sub‐6 GHz bands. Specifically, the chapter discusses the channel side limitations of the IRS and sheds light on the important role the channel plays in the IRS implementation. The chapter focuses on discussing small‐scale fading and path loss model of IRS‐enabled wireless networks, for different scenarios, including far‐field and near‐field scenarios. Finally, the chapter introduces the open‐source, user‐friendly, and widely applicable SimRIS Channel Simulator v2.0.
Chapter 8 develops an iterative optimization framework to maximize the data rate of a given user by jointly optimizing the user service mode selection along with phase shifts of the nearest IRS of IRS‐assisted users in a large‐scale multi‐user, multi‐base station, multi‐IRS network. This chapter presents semi‐definite programming (SDP)‐based iterative approach for phase optimization, whereas a heuristic approach for mode selection is adopted. In addition, a deep reinforcement learning (DRL) framework is presented with proximal policy optimization (PPO) and double deep policy gradient (DDPG) based solutions to optimize phase shifts.
Chapter 9 investigates the significant role that IRS will play in B5G and 6G wireless networks. Precisely, the chapter discusses the potential of IRS in supporting IRS‐assisted multi‐user communication, IRS‐assisted RF sensing and imaging, IRS‐assisted unmanned aerial vehicle (UAV) communication, IRS‐assisted wireless power transfer, and IRS‐assisted indoor localization. In this context, the authors examine their performance and highlight major performance limiting factors, which open the door for future research directions.
In Chapter 10, the authors study the channel modelling and characterization for multi‐IRS‐assisted wireless systems. For a distributed multi‐IRS (DMI)‐assisted system, in which the IRSs have different geometric sizes and are distributively deployed to aid wireless communications, the authors propose a mathematical framework based on the moment‐matching method to determine the statistical characterization of the end‐to‐end (e2e) channel fading of the DMI system. The obtained approximate distributions are employed to derive tight approximate closed‐form expressions of the outage probability (OP) and ergodic capacity (EC) of the DMI system.
Chapter 11 presents the fundamental characteristics of the UAVs, major paradigms for integrating the UAVs into the wireless networks, and their possible applications, as well as addressing open problems and challenges in the UAV communications. The chapter sheds light on the possible IRS‐assisted UAV systems scenarios. Furthermore, this chapter investigates the performance analysis of the IRS‐assisted UAV systems.
Chapter 12 sets the scene for the integration of IRS with optical wireless communication (OWC), as a promising candidate to support blockage‐free, and therefore, extended coverage communication. The chapter sheds light on the advantages accomplished by leveraging various RIS functionalities in OWC networks, from a transceiver, as well as propagation environment perspectives. The authors present a case study for an IRS‐assisted indoor LiFi system and examine the performance of the considered scenario. The chapter finally highlights some of the challenges and open research directions related to the integration of IRS in OWC.
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