Preface

The need to implement cutting-edge technologies to satisfy the demands of fast growing mobile usage by efficiently utilizing scarce spectrum resources is a critical requirement in modern wireless networks. Though several antenna configurations have been proposed to alleviate this problem, the existing techniques have not adequately addressed prevailing issues such as severe pathloss, limited network performance, interference, among others. A possible alternative is applying an advanced antenna technology called massive multiple-input multiple-output (MIMO). Massive MIMO is a key-enabling technology in ubiquitous 5G wireless systems, and it poses enormous prospects for the envisioned 6G and future wireless networks. Massive MIMO could integrate other cutting-edge technologies to improve rates, energy, and spectral efficiency, opening new frontiers in wireless communications.

In massive MIMO, a single base station (BS) can be exploited to eliminate inter-cell interference, employing directional beamforming. First, however, the problem of gaining an insightful understanding of the fundamental limits of massive MIMO persists. Second, the performance evaluation of massive MIMO under ideal and nonideal practical scenarios requires detailed investigation. Third, billions of massive devices communicate via open wireless channels, posing huge security risks to sensitive user data. Thus, robust security architectures for privacy preservation and security of critical information have become imperative in massive MIMO wireless communication networks.

This book presents applications and technology for massive MIMO in 6G and beyond. Specifically, the book presents a unified theoretical framework for analyzing the fundamental limits of massive MIMO, considering several practical network constraints. The book presents advanced signal processing algorithms to enable massive MIMO applications in realistic environments. Additionally, the book presents advanced mathematical tools to analyze multiuser dynamics in evolving wireless communication channels.

The key highlights of the book are outlined as follows:

• The book provides industry and academic researchers with new insights into the real-world deployment scenarios, design and implementation, application, technological trends, and associated benefits of massive MIMO in emerging wireless communication systems.
• The book addresses the need to design energy and spectral-efficient massive MIMO models to resolve several network issues, such as interference, pathloss, delay, traffic outage, and so on, in modern wireless communication systems.
• The book critically examines the fundamental limits of massive MIMO and proffer solutions to revamp the traditional MIMO architecture toward addressing the vast network issues, especially at the wireless edge.
• The book discusses critical security and privacy issues affecting all stakeholders in the wireless ecosystem, and provides practical and effective solutions to address these problems.

The book is structured into 13 chapters collected from industry experts and world-class academic researchers, resulting in diverse and high-quality work for the readers.

Chapter 1 provides introduction to massive MIMO for future wireless communication systems. Starting with the fundamentals of wireless communications and providing background information to facilitate understanding the book. The chapter examines how wireless communication has revolutionized the way we interact with technology, enabling seamless connectivity and communication between devices and networks without needing physical cables. As technology has advanced, each generation of wireless communication has brought significant improvements, leading us to the era of 5G and the promise of even more transformative advancements in the future with 6G and beyond. Wireless communication rely on electromagnetic waves to carry signals through the air or space. Understanding the fundamentals of wireless communication is essential to grasp how these systems work and their various applications. The key fundamentals are the electromagnetic spectrum, radio frequency, modulation, demodulation, antennas, propagation, signal-to-noise ratio (SNR), multiple access techniques, wireless standards, security, and latency, among others.

Chapter 2 examines the security and privacy of future wireless communication systems. The chapter summarizes the proliferating security vulnerability issues in wireless networks. Key challenges, including evolving security threats, massive MIMO security issues, and privacy risks from advanced data collection, are highlighted. Physical layer security methodologies, access control, monitoring tools, and privacy technologies are proposed as viable solutions. The impact of government policies, regulations, and emerging technologies like blockchain are highlighted. Last, open research issues are presented, emphasizing lightweight cryptography, new architectures, and aligning standards with the prevailing regulations.

Chapter 3 presents the applications of massive MIMO in wireless communication systems. The chapter presents a detailed capacity analysis, quantifying the immense throughput gains possible with large antenna arrays and wider bandwidths. Promising solutions drawing from existing literature are reviewed, including antenna architectures, estimation algorithms, signal processing advancements, network topologies, and cross-technology convergence that can help realize the potential of massive MIMO at mmWave/THz bands. The chapter identifies critical open-research challenges related to experimental validation, complexity, security, and standardization that need to be investigated to fully materialize the disruptive capabilities of massive MIMO for 6G and beyond. Last, the chapter provides a holistic perspective on harnessing the potential of massive MIMO in 6G by building on prior art while highlighting open problems, requiring further innovation tailored to wireless networks demands.

Chapter 4 considers cell-free massive MIMO technology and its applications in 6G. The chapter presents an overview of CF mMIMO systems, emphasizing the superiority of such systems over traditional cellular networks. The study covers the system architecture, namely centralized and distributed, along with recent research developments and beamforming algorithms to address the scalability issue of conventional CF systems. These techniques include the user-centric (UC) approach that seeks to build a realistic deployment, where each user equipment (UE) is only served by a small number of cooperative APs. In particular, the chapter considers the integration of CF with radio stripes (RSs) that improve robustness and reduce the high costs/complexity by employing a sequential topology, sharing the same cable for fronthaul and then connecting each RS to a single or multiple CPUs.

Chapter 5 focuses on localization in massive MIMO networks, considering the scenario from near-field to far-field. The chapter considers two subspace-based approaches; Multiple SIgnal Classification (MUSIC) and Estimation of Signal Parameters by Rotational Invariance Techniques (ESPRIT). Originally designed for far-field source localization, these methods have undergone several modifications to accommodate near-field scenarios. The chapter presents the foundations of MUSIC and ESPRIT algorithms and introduces some of their variations for both far-field and near-field localization by a single array of antennas. Finally, the chapter provides numerical examples to demonstrate the performance of the presented methods.

Chapter 6 considers energy-efficient (EE) uplink (UL) transmission in RIS-aided M-MIMO internet of things (IoT) systems. The chapter focuses on the EE UL transmission of M-MIMO IoT systems aided by an RIS. The work proposes and evaluates different schemes to minimize the total UL transmit power by optimizing the transmit power of IoT devices, the RIS phase-shift element, and the combining matrix at the BS. Particularly, special attention is given to manifold optimization techniques, which are well suited to the RIS phase-shifts optimization problems. Herein, the authors treat jointly via iterative alternating optimization (i-AO) approach, the three optimization variables: RIS phase-shift vector, BS combining matrix, and unit terminal (UT) power allocation vector. Extensive numerical results are provided and discussed, revealing that the proposed conjugate gradient (CG) method based on Riemannian manifold (RM) with the ZF combining achieves the highest power savings, being able to reduce the UL transmit power under typical operation conditions scenarios in comparison with conventional systems without RIS.

Chapter 7 deals with energy efficiency (EE) optimization of massive multiple-input multiple-output (M-MIMO) wireless communication systems aided by reconfigurable intelligent surfaces (RISs) and extralarge-scale M-MIMO (XL-MIMO) systems. The chapter presents a unified mathematical model for the wireless propagation channel and a set of optimization tools to optimize the EE in systems operating under realistic constraints. Particularly, two EE problem were formulated and solutions developed by considering different system configurations. In order to maximize the EE in RIS-aided M-MIMO systems, a sequential optimization method for joint RIS phase-shifts design, power allocation (PA), and optimization of the number of active BS antennas is proposed. Summarily, the chapter provides useful optimization tools and analytical frameworks, including techniques from convex optimization and evolutionary heuristic that can be applied to tackle a...