RIS-Parametrized Rich-Scattering Environments: Physics-Compliant Models, Channel Estimation, and Optimization

The tunability of radio environments with reconfigurable intelligent surfaces (RISs) enables the paradigm of smart radio environments in which wireless system engineers are no longer limited to only controlling the radiated signals but can in addition also optimize the wireless channels. Many practical radio environments include complex scattering objects, especially indoor and factory settings. Multipath propagation therein creates seemingly intractable coupling effects between RIS elements, leading to the following questions: How can a RIS-parametrized rich-scattering environment be modelled in a physics-compliant manner? Can the parameters of such a model be estimated for a specific but unknown experimental environment? And how can the RIS configuration be optimized given a calibrated physics-compliant model? This chapter summarizes the current state of the art in this field, highlighting the recently unlocked potential of frugal physical-model-based open-loop control of RIS-parametrized rich-scattering radio environments.Comment: 29 pages, 3 figures, author's version of chapter from forthcoming book "Reconfigurable Metasurfaces for Wireless Communications: Architectures, Modeling, and Optimization

Efficient Computation of Physics-Compliant Channel Realizations for (Rich-Scattering) RIS-Parametrized Radio Environments

Physics-compliant channel models of RIS-parametrized radio environments require the inversion of an "interaction matrix" to capture the mutual coupling between wireless entities (transmitters, receivers, RIS, environmental scattering objects) due to proximity and reverberation. The computational cost of this matrix inversion is typically dictated by the environmental scattering objects in non-trivial radio environments, and scales unfavorably with the latter's complexity. In addition, many problems of interest in wireless communications (RIS optimization, fast fading, object or user-equipment localization, etc.) require the computation of multiple channel realizations. To overcome the potentially prohibitive computational cost of using physics-compliant channel models, we i) introduce an isospectral reduction of the interaction matrix from the canonical basis to an equivalent reduced basis of primary wireless entities (antennas and RIS), and ii) leverage the fact that interaction matrices for different channel realizations only differ regarding RIS configurations and/or some wireless entities' locations.Comment: 12 pages, 1 figure, submitted to an IEEE Journa

Leveraging Chaos for Wave-Based Analog Computation: Demonstration with Indoor Wireless Communication Signals

In sight of fundamental thermal limits on further substantial performance improvements of modern digital computational processing units, wave-based analog computation is becoming an enticing alternative. A wave, as it propagates through a carefully tailored medium, performs the desired computational operation. Yet, the necessary designs are so intricate that experimental demonstrations will necessitate further technological advances. Here, we show that, counterintuitively, the carefully tailored medium can be replaced with a random medium, subject to an appropriate shaping of the incident wave front. Using tunable metasurface reflect-arrays, we demonstrate our concept experimentally in a chaotic microwave cavity. We conclude that off-the-shelf wireless communication infrastructure in combination with a simple reflect-array suffices to perform analog computation with Wi-Fi waves reverberating in a room.Comment: 13 pages including 5 figures + 7 pages Supplemental Materia

A self-adaptive RIS that estimates and shapes fading rich-scattering wireless channels

We present a framework for operating a self-adaptive RIS inside a fading rich-scattering wireless environment. We model the rich-scattering wireless channel as being double-parametrized by (i) the RIS, and (ii) dynamic perturbers (moving objects, etc.). Within each coherence time, first, the self-adaptive RIS estimates the status of the dynamic perturbers (e.g., the perturbers' orientations and locations) based on measurements with an auxiliary wireless channel. Then, second, using a learned surrogate forward model of the mapping from RIS configuration and perturber status to wireless channel, an optimized RIS configuration to achieve a desired functionality is obtained. We demonstrate our technique using a physics-based end-to-end model of RIS-parametrized communication with adjustable fading (PhysFad) for the example objective of maximizing the received signal strength indicator. Our results present a route toward convergence of RIS-empowered localization and sensing with RIS-empowered channel shaping beyond the simple case of operation in free space without fading.Comment: 5 pages, 3 figures, submitted to an IEEE Conferenc

Turning Optical Complex Media into Universal Reconfigurable Linear Operators by Wavefront Shaping

Performing linear operations using optical devices is a crucial building block in many fields ranging from telecommunication to optical analogue computation and machine learning. For many of these applications, key requirements are robustness to fabrication inaccuracies and reconfigurability. Current designs of custom-tailored photonic devices or coherent photonic circuits only partially satisfy these needs. Here, we propose a way to perform linear operations by using complex optical media such as multimode fibers or thin scattering layers as a computational platform driven by wavefront shaping. Given a large random transmission matrix (TM) representing light propagation in such a medium, we can extract a desired smaller linear operator by finding suitable input and output projectors. We discuss fundamental upper bounds on the size of the linear transformations our approach can achieve and provide an experimental demonstration. For the latter, first we retrieve the complex medium's TM with a non-interferometric phase retrieval method. Then, we take advantage of the large number of degrees of freedom to find input wavefronts using a Spatial Light Modulator (SLM) that cause the system, composed of the SLM and the complex medium, to act as a desired complex-valued linear operator on the optical field. We experimentally build several $16\times16$ complex-valued operators, and are able to switch from one to another at will. Our technique offers the prospect of reconfigurable, robust and easy-to-fabricate linear optical analogue computation units