This is a code package is related to the following scientific article:
Emil Björnson, Henk Wymeersch, Bho Matthiesen, Petar Popovski, Luca Sanguinetti, and Elisabeth de Carvalho “Reconfigurable Intelligent Surfaces: A Signal Processing Perspective With Wireless Applications,” IEEE Signal Processing Magazine, to appear.
The package contains a simulation environment, based on Matlab, that reproduces some of the numerical results and figures in the article. We encourage you to also perform reproducible research!
Antenna array technology enables directional transmission and reception of wireless signals, for communications, localization, and sensing purposes. The signal processing algorithms that underpin this technology began to be developed several decades ago [1], but it is first with the ongoing deployment of the fifth-generation (5G) wireless mobile networks that it becomes a mainstream technology [2]. The number of antenna elements in the arrays of the 5G base stations and user devices can be measured at the order of 100 and 10, respectively. As the networks shift towards using higher frequency bands, more antennas fit into a given aperture. For communication purposes, the arrays are used to form beams in desired directions to improve the signal-to-noise ratio (SNR), multiplex data signals in the spatial domain (to one or multiple devices), and suppress interference by spatial filtering [2]. For localization purposes, these arrays are used to maintain the SNR when operating over wider bandwidths, for angle-of-arrival estimation, and to separate multiple sources and scatterers [3]. The practical use of these features requires that each antenna array is equipped with well-designed signal processing algorithms.
The 5G developments enhance the transmitter and receiver functionalities, but the wireless channel propagation remains an uncontrollable system. This is illustrated in Fig. 1(a) and its mathematical notation will be introduced later. Transmitted signals with three different frequencies are shown to illustrate the fact that attenuation can vary greatly across frequencies. Looking beyond 5G, the advent of electromagnetic components that can shape how they interact with wireless signals enables partial control of the propagation. A reconfigurable intelligent surface (RIS) is a two-dimensional surface of engineered material whose properties are reconfigurable rather than static [4]. As illustrated in Fig. 1(b), the surface consists of an array of discrete elements, where each color represents a certain amplitude and phase response curve. A controller and switch determine which curve to utilize, on a per-element or group-of-elements level. The scattering, absorption, reflection, and diffraction properties of the entire RIS can thereby be changed with time and controlled by software. In principle, the surface can be used to synthesize an arbitrarily shaped object of the same size, when it comes to how electromagnetic waves interact with it [5]. Fig. 1(b) shows how the RIS adds new controllable paths to complement the uncontrollable propagation, each containing a wireless channel to an RIS element, filtering inside the element, and a wireless channel to the receiver. These paths can be tuned to improve the channel quality in a variety of ways [6]. For example, Fig. 1(a) shows how the uncontrollable channel attenuates some signal frequencies more than others, while Fig. 1(b) shows how the RIS can be tuned to mitigate this issue. An RIS can be utilized to support wireless communications as well as localization, sensing, and wireless power transfer [7], [8].
The long-term vision of the RIS technology is to create smart radio environments [9], where the wireless propagation conditions are co-engineered with the physical-layer signaling, and investigate how to utilize this new capability. The traditional protocol stack consists of seven layers and wireless technology is chiefly focused on the first three layers (physical, link, and network) [10]. The conventional design starts at Layer 1, where the physical signals are generated and radiated by the transmitter and then measured and decoded by the receiver. The wireless medium between the transmitter and receiver, called Layer 0, is commonly seen as uncontrollable and decided by “nature”. The RIS technology changes this situation by extending the protocol design to Layer 0, which can profoundly change wireless systems beyond 5G.
This article provides a tutorial on the fundamental properties of the RIS technology from a signal processing perspective. It is meant as a complement to recent surveys of electromagnetic and hardware aspects [4], [7], [11], acoustics [12], communication theory [13], and localization [8]. We will provide the formulas and derivations that are required to understand and analyze RIS-aided systems using signal processing, and exemplify how they can be utilized for improved communication, localization, and sensing. We will also elaborate on the fundamentally new possibilities enabled by Layer 0 engineering and phenomena that remain to be modeled and utilized for improved signal processing design.
The article contains 4 simulation figures, numbered 1, 4, 6, and 8. The Matlab script simulateFigureX.m generates Figure X.
See each file for further documentation.
We would like to thank Gonzalo Seco-Granados, Kamran Keykhosravi, Özlem Tugfe Demir, and Robin J. Williams for their comments and feedback during the writing. This work has been partially supported by H2020 RISE-6G project, under grant 101017011, the German Research Foundation (DFG) under Germany’s Excellence Strategy (EXC 2077 at University of Bremen, University Allowance), the Italian Ministry of Education and Research in the framework of the CrossLab Project, and the FFL18-0277 grant from the Swedish Foundation for Strategic Research.
This code package is licensed under the GPLv2 license. If you in any way use this code for research that results in publications, please cite our original article listed above.