Abstract: This tutorial aims to present the current research efforts on implementing machine learning algorithms in wireless systems. Specifically, we provide a comprehensive coverage of a distributed learning paradigm based on over-the-air computing, a.k.a. over-the-air machine learning (OTA-ML). We will present the general architecture, model training algorithm, and an analytical framework that quantifies the convergence rate of OTA-ML. The analysis takes into account the effects from key system factors, such as channel fading and interference, as well as real-world noisy data, on the convergence performance and discloses how interference is deteriorating the model training process. Then, we demonstrate several improvements to the OTA-ML from different aspects. Particularly, we introduce model pruning schemes that reduce the computation and communication overheads for OTA-ML. We also discuss the system enhancements from an algorithmic perspective, e.g., adopting the momentum-based approach and/or adaptive optimizations to accelerate the model training. Moreover, a personalization framework will be introduced to enhance performance and robustness for OTA-ML. Finally, we will elaborate on the analysis of generalization error of the statistical models trained by OTA-ML, which shows that wireless interference has the positive potential of improving the generalization capability. A few signal processing methods that exploit interference to improve generalization will also be discussed. We conclude this tutorial by shedding light on future works.
Abstract: The development of metasurfaces has provided a novel multi-antenna technology for wireless communication networks to improve performance by manipulating the propagation environment. Intelligent omni-surface (IOS), an innovative technique in this category, is proposed for coverage extension via its high spatial diversity gain. Capable of integrating a massive number of elements without introducing extra hardware cost compared to the traditional phased arrays, the IOS technique serves as a cost-efficient method to achieve massive MIMO. In contrast to the widely studied reflective metasurfaces, i.e., intelligent reflecting surfaces (IRSs), which can only serve receivers located on the same side of the transmitter, the IOS can achieve full-dimensional wireless communications by enabling the simultaneous reflection and refraction of the surface, similar to a two-sided mirror, and thus users on both sides can be served. In this tutorial, we provide a comprehensive overview of the state-of-the-art IOS-related research from the perspective of wireless communications, with the emphasis on their design principles, beamforming design, experimental implementation and measurements. We first describe the basic concepts of IOS and introduce its great potential in realizing massive MIMO. We then present the key techniques for the IOS enabled full-dimensional wireless communications. In particular, we present the implementation of our own developed IOS-aided wireless communication prototype and report its experimental measurement results indicating the coupling of reflection and refraction. Finally, we outline some potential future directions and challenges in this area.
Abstract: Terahertz (THz) communications are envisioned as an enabling and highly promising wireless technology for the sixth generation (6G) and beyond wireless systems, which aim to provide full and unlimited wireless connectivity for the ubiquitous intelligent information society of 2030 and beyond. In particular, the ultra-wide THz band ranging from 0.1 to 10 THz offers enormous potential to alleviate the spectrum scarcity and break the capacity limitation of emerging wireless systems (such as 4G-LTE and 5G). To overcome the short transmission distance and huge propagation loss, ultra-massive (UM) MIMO systems with beamforming technologies that employ sub-millimeter wavelength antenna arrays are essential to enable an enticingly high array gain. In UM-MIMO systems, hybrid beamforming stands out for its great potential in promisingly high data rate and reduced power consumption. The resulting beamforming technologies in THz UM-MIMO communications will undoubtedly support the epoch-making wireless applications that demand ultra-high quality of service requirements and multi-terabits per second data transmission in the 6G and beyond era, such as terabit-per-second backhaul and wireless local area networks, holographic communications, metaverse, ultra-high-definition content streaming among mobile devices, and wireless highbandwidth secure transmission. Against this background, the proposed tutorial will provide a comprehensive look at cutting-edge beamforming technologies in THz UM-MIMO communications. First, this tutorial provides a highlevel overview of THz UM-MIMO communications and illustrates its importance of wireless systems in the next decades. Then, this tutorial introduces the fundamental yet unique peculiarities of hardware systems and propagation channels research of THz UM-MIMO communications. After this, the tutorial presents a structured and comprehensive survey of the THz beamforming solutions, including far-field beamforming, near-field beamfocusing, hybrid farnear-field technologies, and distance-adaptive multi-user beamforming. With narrowbeams, the tutorial next focuses on THz beam management, describing beam training/alignment, beam tracking, and beam-guided medium access. Finally, this tutorial identifies and discusses the outstanding barriers that future wireless system designers must tackle to reap the full benefits of THz communications in the 6G and beyond era. Overall, the proposed tutorial will help a wide range of audience across the academic, industry, and professional communities to thoroughly understand the role of THz communications in 6G and beyond era and unlock its potential for the future ubiquitous intelligent information society.
Abstract: Extremely large-scale multiple-input-multiple-output (XL-MIMO) is a promising technology to empower the next-generation mobile communication networks. Compared with existing 5G massive MIMO, XL-MIMO is not simply an increase of the antenna elements, but possesses new channel characteristics and faces new design challenges and opportunities, in terms of channel modelling, performance analysis, CSI acquisition, and transmission technologies. However, XLMIMO is still in its early stage of research, and some preliminary efforts have been devoted to hardware schemes and performance analysis by taking into account new channel characteristics. To illustrate the differences and similarities among these schemes, we comprehensively review existing XL-MIMO hardware designs and channel characteristics in this article. Then, we thoroughly discuss the research status of XL-MIMO from “channel modeling”, “performance analysis”, and “signal processing”. Several existing challenges are introduced and respective solutions are provided. We then propose two case studies for the hybrid propagation channel modeling and the effective degrees of freedom (EDoF) computations for practical scenarios. Using our proposed solutions, we perform numerical results to investigate the EDoF performance for the scenarios with unparallel XL-MIMO surfaces and multiple user equipment, respectively. Furthermore, we discuss a novel inter-symbol interference (ISI) mitigation technique, termed delay alignment modulation (DAM), by exploiting the extremely large spatial dimension brought by large antenna arrays and the multi-path sparsity of millimeter wave and Terahertz channels. DAM enables manipulable channel delay spread for more efficient single-carrier or multi-carrier communications and sensing. Finally, we discuss several future research directions.
Abstract: Future wireless networks are envisioned to support ubiquitous connectivity to a wide range of emerging applications, spanning from autonomous cars to unmanned aerial/underwater vehicles (UAV/UUV). This requires novel wireless technology to provide highly reliable data transmission and highly robust sensing simultaneously. However, the strong multipath, high delay, and Doppler features in vehicular environments can impose great challenges for reliable wireless communications and robust sensing. Consequently, the conventional orthogonal frequency division multiplexing (OFDM) modulation may fail due to the high dynamical channel fluctuations. The recently proposed orthogonal time frequency space (OTFS) modulation has provided a fundamentally different perspective of waveform design in the delay-Doppler (DD) domain in contrast to the conventional timefrequency (TF) domain designs. Since both functionalities can be unified in the same domain, promising performance over various channels has been shown and the advantages have been widely evident from both academic and industry perspectives. This tutorial aims to provide a comprehensive understanding of the DD domain communications and sensing with specific focuses on its fundamentals, advanced designs, performance analysis, and applications.
In this tutorial, we will first overview the background and fundamentals of DD domain communications and sensing. As a step further, we will introduce the state-of-the-art research progress on this topic, which consists of 4 technical parts: 1) Fundamentals of DD domain communications in single-antenna systems, 2) Recent advances of DD domain multiple-input multiple-output (MIMO) communications, 3) DD signal processing for wireless sensing, and 4) DD domain communications with integrated sensing functionality. Finally, we will conclude the tutorial by summarizing the future directions and open problems of DD domain communications and sensing.
Abstract: For the design, performance evaluation, and optimization of wireless communication systems, channel measurements and realistic channel models with good accuracy-complexity-pervasiveness trade-off are indispensable. The proposed tutorial is intended to offer a comprehensive and in-depth course to communication professionals/academics, aiming to address recent advances and future challenges on channel measurements and modeling methods for sixth generation (6G) wireless systems. Network architecture and key technologies for 6G that will enable global coverage, all spectra, and full applications will be first discussed. Channel measurements and non-predictive channel models are then reviewed for challenging 6G scenarios and frequency bands, focusing on millimeter wave, terahertz, and optical wireless communication channels under all spectra, satellite, unmanned aerial vehicle, and maritime communication channels under global coverage scenarios, and vehicle-to-vehicle, ultra-massive multiple-input multiple-output (MIMO), industrial Internet of things (IoT), reconfigurable intelligent surface (RIS), and integrated sensing and communication (ISAC) channels under full application scenarios. New beam domain channel models and artificial intelligence (AI)/machine learning (ML) based space-time-frequency predictive channel models will also be investigated. A non-predictive 6G pervasive channel model for all frequency bands and all scenarios will then be proposed, which is expected to serve as a baseline for future standardized 6G channel models. Future research challenges and trends for 6G channel measurements and models will be discussed in the end of the tutorial.
Abstract: Future 6G wireless communication systems are expected to realize an intelligent communication, sensing, computing and software reconfigurable functionality paradigm, where all parts of device hardware will adapt to the changes of the wireless environment, and provide various high-accuracy sensing services, positioning, etc. Furthermore. with the rapid development of wireless networks and Internet of things (IoT), emerging applications continue to appear, such as artificial intelligence (AI) task, immersive service, and digital twins. Those emerging applications have put forward higher demands on sixth generation (6G) networks for end-to-end information processing capabilities. In order to meet the higher performance demands, 6G will be an end-to-end information processing and service system, and its core functions will expand from information transmission to information collection, information computing and information application, providing stronger sensing, communication, and computation capabilities. Thus, this has led to the emergence of a fast-growing area, called joint sensing, communication, and computation. It is widely expected that the advancements in joint sensing, communication, and computation would provide a platform for implementing AI in 6G systems and solving large-scale problems in our society ranging from autonomous driving to personalized healthcare. However, one fundamental problem is how we implement AI, sensing, computing into the wireless communications. In the recent period, a brand-new technology was brought to the attention of the wireless research community, the “Reconfigurable intelligent surfaces (RIS)”. Following the recent breakthrough on the fabrication of programmable metamaterials, reconfigurable intelligent metasurfaces have the potential to materialize the intelligent software-based control of the environment in wireless communication systems, when coated on the otherwise passive surfaces of various objects. Being a newly proposed concept going beyond massive MIMO, intelligent surfaces are low cost, ultra-thin, light weight, and low power consumption hardware structures that provide a transformative means of the wireless environment into a programmable smart entity. Therefore, we expect that to implement the ubiquitous intelligence, sensing, computing by leveraging the advance of the RIS. Achieving the goal of RIS-empowered joint sensing, communications, and computation with high communication efficiencies calls for the designs of new wireless techniques based on a sensingcommunication-and-learning integration approach. The observation of the recent surge in relevant research and the emergence of many exciting opportunities motivate us to propose the tutorial of “RIS-empowered Joint Sensing, Communication, and Computation”. Thereby, this tutorial will seek to provide a comprehensive introduction to RIS-empowered sensing and computing over wireless communications while delineating the potential opportunities, roadblocks, and challenges.
Abstract: The next generation mobile communications network is envisioned to face both significant user-side paradigm shifts and network-side challenges. On the one hand, trillions of IoT devices will connect to the network, and astronomical amount of data uploading traffic will deplete network bandwidth. On the other hand, network costs (e.g., infrastructure deployment and energy costs) are surging, and high-quality spectrum resources have been exhausted. Furthermore, the future 6G radio access networks (RANs) are anticipated to be multi-functional, which should serve as edge infrastructure to provide site-specific services for surrounding users. More interestingly, the future cellular network are expected to sense or even image the surrounding environment to enable intelligent location-aware services, ranging from the physical to application layers. Nevertheless, the current architecture of large-scale RANs still remains as the combination of individual cells, which provides communication-only functionality.
This tutorial will first provide insights on the evolution of RAN through investigating the existing paradigms and future trends, followed by introducing a disruptive fully-decoupled radio access network (FD-RAN) architecture for 6G. The FD-RAN aligns with the trends by integrating existing paradigms and introducing new features such as physical decoupling of uplink and downlink base stations. On this basis, this tutorial will further shed light on the recent progress on the 6G Integrated Sensing and Communications (ISAC) technology, including the fundamental limits, signal processing, networked sensing, and sensing-assisted communications. Throughout the tutorial, the necessity of decoupled RAN and sensing functionality for 6G will be emphasized.
