Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

Reconfigurable intelligent surfaces (RISs) are an emerging transmission technology for application to wireless communications. RISs can be realized in different ways, which include (i) large arrays of inexpensive antennas that are usually spaced half of the wavelength apart; and (ii) metamaterial-based planar or conformal large surfaces whose scattering elements have sizes and inter-distances much smaller than the wavelength. Compared with other transmission technologies, e.g., phased arrays, multi-antenna transmitters, and relays, RISs require the largest number of scattering elements, but each of them needs to be backed by the fewest and least costly components. Also, no power amplifiers are usually needed. For these reasons, RISs constitute a promising software-defined architecture that can be realized at reduced cost, size, weight, and power (C-SWaP design), and are regarded as an enabling technology for realizing the emerging concept of smart radio environments (SREs). In this paper, we (i) introduce the emerging research field of RIS-empowered SREs; (ii) overview the most suitable applications of RISs in wireless networks; (iii) present an electromagnetic-based communication-theoretic framework for analyzing and optimizing metamaterial-based RISs; (iv) provide a comprehensive overview of the current state of research; and (v) discuss the most important research issues to tackle. Owing to the interdisciplinary essence of RIS-empowered SREs, finally, we put forth the need of reconciling and reuniting C. E. Shannon’s mathematical theory of communication with G. Green’s and J. C. Maxwell’s mathematical theories of electromagnetism for appropriately modeling, analyzing, optimizing, and deploying future wireless networks empowered by RISs.

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Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How It Works, State of Research, and The Road Ahead

What is a reconfigurable intelligent surface? What is a smart radio environment? What is a metasurface? How do metasurfaces work and how to model them? How to reconcile the mathematical theories of communication and electromagnetism? What are the most suitable uses and applications of reconfigurable intelligent surfaces in wireless networks? What are the most promising smart radio environments for wireless applications? What is the current state of research? What are the most important and challenging research issues to tackle? 
These are a few of the many questions that we investigate in this short opus, which has the threefold objective of introducing the emerging research field of smart radio environments empowered by reconfigurable intelligent surfaces, putting forth the need of reconciling and reuniting C. E. Shannon's mathematical theory of communication with G. Green's and J. C. Maxwell's mathematical theories of electromagnetism, and reporting pragmatic guidelines and recipes for employing appropriate physics-based models of metasurfaces in wireless communications.

Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How it Works, State of Research, and Road Ahead.

Reconfigurable intelligent surfaces (RISs) have the potential of realizing the emerging concept of smart radio environments by leveraging the unique properties of meta-surfaces. In this article, we discuss the potential applications of RISs in wireless networks that operate at high-frequency bands, e.g., millimeter wave (30-100 GHz) and sub-millimeter wave (greater than 100 GHz) frequencies. When used in wireless networks, RISs may operate in a manner similar to relays. This paper elaborates on the key differences and similarities between RISs that are configured to operate as anomalous reflectors and relays. In particular, we illustrate numerical results that highlight the spectral efficiency gains of RISs when their size is sufficiently large as compared with the wavelength of the radio waves. In addition, we discuss key open issues that need to be addressed for unlocking the potential benefits of RISs.

Reconfigurable Intelligent Surfaces vs. Relaying: Differences, Similarities, and Performance Comparison

Reconfigurable intelligent surfaces (RISs) are an emerging technology for application to wireless networks. We introduce a physics and electromagnetic (EM) compliant communication model for analyzing and optimizing RIS-assisted wireless systems. The proposed model has four main notable attributes: (i) it is end-to-end , i.e., it is formulated in terms of an equivalent channel that yields a one-to-one mapping between the voltages fed into the ports of a transmitter and the voltages measured at the ports of a receiver; (ii) it is EM-compliant , i.e., it accounts for the generation and propagation of the EM fields; (iii) it is mutual coupling aware , i.e., it accounts for the mutual coupling among the sub-wavelength unit cells of the RIS; and (iv) it is unit cell aware , i.e., it accounts for the intertwinement between the amplitude and phase response of the unit cells of the RIS.

End-to-End Mutual Coupling Aware Communication Model for Reconfigurable Intelligent Surfaces: An Electromagnetic-Compliant Approach Based on Mutual Impedances

The purpose of this paper is to introduce a communication model for Large Intelligent Surfaces (LIS). A LIS is modeled as a collection of tiny closely spaced antenna elements. Due to the proximity of the elements, mutual coupling arises. An optimal transmitter design depends on the mutual coupling matrix. For single user communication, the optimal transmitter uses the inverse of the mutual coupling matrix in a filter matched to the channel vector. We give the expression of the mutual coupling for two types of planar arrays. The conditioning number of the mutual coupling matrix is unbounded as the antenna element density increases, so only the dominant values can be inverted within reasonable computation. The directivity is partial but still significant compared to the conventional gain. When the spacing between elements becomes small (smaller than half a wavelength), the directivity surpasses the conventional directivity equal to the number of antennas, as well as the gain obtained when modeling the surface as continuous. The gain is theoretically unbounded as the element density increases for a constant aperture.

A Communication Model for Large Intelligent Surfaces

Bluetooth Mesh (BM) is a new communication standard, which is designed for the upcoming Internet of Things. It builds on the Bluetooth Low Energy (BLE) protocol and allows devices to extend the range and create a mesh network. BM introduces a publisher/ observer structure where a publisher node can broadcast a packet, known also as an advertisement, and all observers can receive the packet. Typically, in BM networks flooding is used to propagate the advertisements. Flooding is known to suffer from broadcast storm problem and be nonreli-able. To improve packet delivery ratio we propose an approach where only a few nodes, relays, are involved in packet forwarding. Selection of the relay nodes, which is a focus of the paper, is a nontrivial task: on the one hand, a minimization of number of relays is desired, on the other hand, using a minimum dominated set would not provide redundancy. We consider three different relay selection mechanisms and develop their extensions that are capable to operate in a distributed fashion. Their performance is evaluated via extensive simulations.

On Relay Selection Approaches in Bluetooth Mesh Networks

This paper presents the simulated performance of a dual S- and X-band shared aperture antenna design. The antenna is 82 by 82 mm and it has a total height of $\leq 4$ mm. This size allows the antenna to fit within the parameters of a nano-satellite unit structure. The antenna is right hand circularly polarized in both bands. The Antenna is tuned to a S-band frequency range from 2.025 to 2.075 GHz and a X-band frequency range from 7.75 to 8.75 GHz. The design has a Realized right hand circularly polarized gain of $\geq$6dB in the S-band and $\geq$12dB in the X-band. The impedance bandwidth is very wide as it exceeds the selected frequency ranges. The cross-coupling is below -25dB in the S-band and below -30dB in the selected X-band frequency range.

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Shared Aperture Dual S- and X-band Antenna for Nano-Satellite Applications

One of the beyond-5G developments that is often highlighted is the integration of wireless communication and radio sensing. This paper addresses the potential of communication-sensing integration of Large Intelligent Surfaces (LIS) in an exemplary Industry 4.0 scenario. Besides the potential for high throughput and efficient multiplexing of wireless links, an LIS can offer a high-resolution rendering of the propagation environment. This is because, in an indoor setting, it can be placed in proximity to the sensed phenomena, while the high resolution is offered by densely spaced tiny antennas deployed over a large area. By treating an LIS as a radio image of the environment, we develop sensing techniques that leverage the usage of computer vision combined with machine learning. We test these methods for a scenario where we need to detect whether an industrial robot deviates from a predefined route. The results show that the LIS-based sensing offers high precision and has a high application potential in indoor industrial environments.

A Primer on Large Intelligent Surface (LIS) for Wireless Sensing in an Industrial Setting

Dynamic metasurface antennas (DMAs) arise as a promising technology in the field of massive multiple-input multiple-output (mMIMO) systems, offering the possibility of integrating a large number of antennas in a limited —and potentially large— aperture while keeping the required number of radio-frequency (RF) chains under control. Although envisioned as practical realizations of mMIMO systems, DMAs represent a new paradigm in the design of signal processing techniques (such as beamforming) due to the constraints inherent to their physical implementation, for which no complete models are available yet. In this work, we propose a complete and electromagnetic-compliant narrowband communication model for a generic DMA based system. Specifically, the model accounts for: i) the wave propagation and reflections throughout the waveguides that feed the antenna elements, ii) the mutual coupling both through the air and the waveguides, and iii) the insertion losses. Also, we integrate the electromagnetic model in the conventional digital communication model, providing a complete and useful framework to design and characterize the performance of these systems. Finally, the accuracy of the model is verified through full-wave simulations.

Robin Jess Williams

Papers

A Communication Model for Large Intelligent Surfaces

On Relay Selection Approaches in Bluetooth Mesh Networks

Shared Aperture Dual S- and X-band Antenna for Nano-Satellite Applications

A Primer on Large Intelligent Surface (LIS) for Wireless Sensing in an Industrial Setting

Electromagnetic Based Communication Model for Dynamic Metasurface Antennas