Dr. Alessio Zappone
University of Cassino and Southern Lazio, Italy
Dr. Marco Di Renzo
CNRS, University Paris-Saclay, France
Dr. Shi Jin
Southeast University, China
Dr. Merouane Debbah
Huawei France R&D, France
As 5G networks take their final form, connectivity demands continue to increase exponentially and new services pose more performance constraints. A technological breakthrough with the potential to meet these demands is that of reconfigurable intelligent surfaces. RIS-based communications put forth the idea of treating the communication environment not as a fixed entity, but as an optimization variable. In principle, the possibility of creating more convenient electromagnetic paths is already provided by the use of relay stations. However, relays are based on traditional active antenna technology with transmit amplifiers and complex hardware circuitry, leading to large power consumptions, large size of the devices, and high costs. Instead, RISs are nearly-passive structures with very limited power consumption, size, and deployment costs. RISs are planar structures made of special materials, known as meta-materials, on which elementary electromagnetic reflectors are placed and spaced at sub-wavelength distances. RISs can reflect/refract incoming electromagnetic signals in directions that can be fully customized. RISs can be configured in real-time, adapting to the sudden changes of the network and/or of the traffic demands. RISs can be deployed on the walls of buildings or can be used to coat the environmental objects between the communicating devices, which effectively makes the wireless channel a new variable to be optimized. Thanks to their reduced size and cost, RISs can be equipped with a much larger number of reflectors than the number of antennas in traditional antenna arrays. A tutorial on the principles and latest approaches of RIS will be of great value for both academics and industry practitioners.
This tutorial is endorsed by the Emerging Technology Initiative on RISs for Smart Radio Environments of the IEEE Communications Society, in which A. Zappone is the founding vice-chair, M. Di Renzo, is the founding liason officer on behalf of the IEEE emerging technology committee, S. Jin is the founding officer for testbeds, devices, and Proof-of-concepts, M. Debbah is the founding industry liason officer.
Moreover, this tutorial is also endorsed by the special interest groups REFLECTIONS, chaired by A. Zappone and activated within the SPCC-TC, and RISE, chaired by M. Di Renzo and activated within the WTC.
Structure and content
Introduction. The tutorial starts by discussing 5G standardization activities, the performance that 5G networks will be able to grant, and how this appears inadequate to keep the pace with the exponentially increasing number of connected devices and with therise of many new heterogeneous services. The main challenges thatstand in our way towards meeting the requirements of future networks will be identified, namely the extreme heterogeneity of the tasks to execute, which range from broadband communications, tovery low-latency communications, extreme energy efficiency and high data rates, and localization. The use of RIS to enable this 6G vision will be discussed. Both an academic and industrial perspective will be provided. Moreover, the economical and societal opportunities that overcoming 5G holds will be analyzed. After this first part, the audience will have a proper understanding of the main principles that make the RIS technology possible, of the potential of RISs, and of the challenges and opportunities related to overcoming 5G networks.
Meta-material fundamentals and experimental results. This part of the tutorial will introduce the fundamentals of meta-material technology and, in order to substantiate the gains that RIS can bring to wireless communications, will present experimental results obtained by using the world’s first meta-surface assisted wireless prototype testbed for RIS-based communications, which has been developed at Southeast university by the group of Prof. Shi Jin. The tutorial will explain how packing reflecting elements at sub-wavelength distances enables to obtain a non-homogeneous surface for which the conventional Snell’s laws do not hold. Experimental results will show that, despite not having any transmit amplifier, by properly designing the elementary reflecting elements, it is possible to achieve high data-rates. Moreover, by embedding stimuli-responsive materials in the meta-surface, e.g. liquid crystals or magnetic ferrite, which can rapidly vary their physical properties inresponse to external stimuli, it is possible to dynamically program the behavior of the meta-surface in real-time. The tutorial will show how RISs can be used to improve the communication reliability (e.g. by ensuring that the different signal paths add coherently at the receiver), energy efficiency (since RISs can increase the data-rate with an extremely limited energy consumption), and security (since RIS can be used to focus the reflected/refracted energy only towards desired directions).
Modeling and Design of RIS-based wireless networks. This part of the tutorial will address both modeling and design issues of RIS-based wireless networks, presenting the latest research trends in both directions. Specifically, at first the tutorial will introduce equivalent electromagnetic-based and physics-inspired mathematical models of RIS, showing how they can be employed to model RIS-based wireless networks, in order to come to new expressions of the SNR in a RIS-based communication channel. Next, it will be shownhow the unique properties of RISs are expected to yield different scaling laws from those currently encountered in wireless networks, e.g., a different received power expression as a function of the distance between transmitters and receivers, or a received SNR as a function of the number of reflecting elements equipped at the RIS. As a result of this discussion, the advantages and limitations of RISs will be discussed in comparison with other more traditional technologies, such as massive MIMO and relaying. In this context, it will be also observed how RISs can be used to perform specific tasks in a much simpler and more energy-efficient way than with available transmission technologies, such as implementing spatial modulation techniques, improving the security and reliability of wireless networks. Also, the tutorial will elaborate on how RISs can be used for improving the performance of wireless networks, e.g., for communication at high frequency bands, such as the mmWave frequency range.
Then, the tutorial will address the most recent results and techniques for the optimization of RIS-based wireless networks. At first, the new optimization challenges posed by the use of RISs will be identified, and a thorough literature survey about resource allocation for RIS-based wireless networks design will be given. Namely, the fact that the RIS is a (nearly) passive device without neither a dedicated transmit and receive hardware, nor a digital signal processor, results in: 1) more challenging resource allocation problems to solve; 2)more sophisticated channel estimation and feedback protocols, which poses additional constraints on the resource allocation algorithms, and leads to the need of performing overhead-aware resource allocation as well as joint channel estimation and resource allocation, unlike what typically happens for the design of present wireless communication systems. As a first step, the latest techniques for resource allocation in RIS-based wireless networks will be discussed, without explicitly accounting for the channel estimation and feedback phases. Both point-to-point and multi-user MIMO wireless networks will be considered and it will be shown how to handle the more challenging resource allocation problems encountered when designing RIS-based wireless networks. Different performance metrics will be optimized, including the system spectral efficiency, energy efficiency, and their trade-off, with respect to the RIS phase shifts, the number of RIS reflecting elements, the transmit powers, transmit beamforming, and receive filters. Moreover, it will be shown how the previous approaches can be extended to the scenario in which the overhead related to channel estimation and to the computation and configuration of the optimal RIS phase matrix are explicitly accounted for in the resource allocation problem. This leads to a more challenging optimization problem, which is solved again with respect to the RIS phase shifts, the number of RIS reflecting elements, the transmit powers, transmit beamforming, and receive filters. Also in this case, different performance metrics are optimized including the system spectral efficiency, energy efficiency, and their trade-off. Overhead-aware algorithms for the optimization of the RIS phase shifts, the number of RIS reflecting elements, the transmit powers, beamformers, and receive filters will be presented. Different performance metrics are optimized including the spectral efficiency, energy efficiency, and their trade-off.