arXiv subjects

Marco Di Renzo

Publications and source records attributed to Marco Di Renzo.

At least 199 records · Page 11Linked to original sources

arXiv2021

Reconfigurable Intelligent Surface-Assisted Cell-Free Massive MIMO Systems Over Spatially-Correlated Channels

Cell-Free Massive multiple-input multiple-output (MIMO) and reconfigurable intelligent surface (RIS) are two promising technologies for application to beyond-5G networks. This paper considers Cell-Free Massive MIMO systems with the assistance of an RIS for enhancing the system performance under the presence of spatial correlation among the engineered scattering elements of the RIS. Distributed maximum-ratio processing is considered at the access points (APs). We introduce an aggregated channel estimation approach that provides sufficient information for data processing with the main benefit of reducing the overhead required for channel estimation. The considered system is studied by using asymptotic analysis which lets the number of APs and/or the number of RIS elements grow large. A lower bound for the channel capacity is obtained for a finite number of APs and engineered scattering elements of the RIS, and closed-form expressions for the uplink and downlink ergodic net throughput are formulated in terms of only the channel statistics. Based on the obtained analytical frameworks, we unveil the impact of channel correlation, the number of RIS elements, and the pilot contamination on the net throughput of each user. In addition, a simple control scheme for optimizing the configuration of the engineered scattering elements of the RIS is proposed, which is shown to increase the channel estimation quality, and, hence, the system performance. Numerical results demonstrate the effectiveness of the proposed system design and performance analysis. In particular, the performance benefits of using RISs in Cell-Free Massive MIMO systems are confirmed, especially if the direct links between the APs and the users are of insufficient quality with high probability.

cs.IT↗

arXiv2021

An Overview of Signal Processing Techniques for RIS/IRS-aided Wireless Systems

In the past as well as present wireless communication systems, the wireless propagation environment is regarded as an uncontrollable black box that impairs the received signal quality, and its negative impacts are compensated for by relying on the design of various sophisticated transmission/reception schemes. However, the improvements through applying such schemes operating at two endpoints (i.e., transmitter and receiver) only are limited even after five generations of wireless systems. Reconfigurable intelligent surface (RIS) or intelligent reflecting surface (IRS) have emerged as a new and revolutionary technology that can configure the wireless environment in a favorable manner by properly tuning the phase shifts of a large number of quasi passive and low-cost reflecting elements, thus standing out as a promising candidate technology for the next-/sixth-generation (6G) wireless system. However, to reap the performance benefits promised by RIS/IRS, efficient signal processing techniques are crucial, for a variety of purposes such as channel estimation, transmission design, radio localization, and so on. In this paper, we provide a comprehensive overview of recent advances on RIS/IRS-aided wireless systems from the signal processing perspective. We also highlight promising research directions that are worthy of investigation in the future.

eess.SP↗

arXiv2021

Path Loss Modeling and Measurements for Reconfigurable Intelligent Surfaces in the Millimeter-Wave Frequency Band

Reconfigurable intelligent surfaces (RISs) provide an interface between the electromagnetic world of wireless propagation environments and the digital world of information science. Simple yet sufficiently accurate path loss models for RISs are an important basis for theoretical analysis and optimization of RIS-assisted wireless communication systems. In this paper, we refine our previously proposed free-space path loss model for RISs to make it simpler, more applicable, and easier to use. The impact of the antenna's directivity of the transmitter, receiver, and the unit cells of the RIS on the path loss is explicitly formulated as an angle-dependent loss factor. The refined model gives more accurate estimates of the path loss of RISs comprised of unit cells with a deep sub-wavelength size. Based on the proposed model, the properties of a single unit cell are evaluated in terms of scattering performance, power consumption, and area, which allows us to unveil fundamental considerations for deploying RISs in high frequency bands. Two fabricated RISs operating in the millimeter-wave (mmWave) band are utilized to carry out a measurement campaign. The measurement results are shown to be in good agreement with the proposed path loss model. In addition, the experimental results suggest an effective form to characterize the power radiation pattern of the unit cell for path loss modeling.

eess.SP↗

arXiv2021

Learning to Estimate RIS-Aided mmWave Channels

Inspired by the remarkable learning and prediction performance of deep neural networks (DNNs), we apply one special type of DNN framework, known as model-driven deep unfolding neural network, to reconfigurable intelligent surface (RIS)-aided millimeter wave (mmWave) single-input multiple-output (SIMO) systems. We focus on uplink cascaded channel estimation, where known and fixed base station combining and RIS phase control matrices are considered for collecting observations. To boost the estimation performance and reduce the training overhead, the inherent channel sparsity of mmWave channels is leveraged in the deep unfolding method. It is verified that the proposed deep unfolding network architecture can outperform the least squares (LS) method with a relatively smaller training overhead and online computational complexity.

eess.SP↗

arXiv2021

Reconfigurable Intelligent Surfaces: Performance Assessment Through a System-Level Simulator

Reconfigurable intelligent surfaces (RISs) are considered a promising technology for boosting the coverage and for enhancing the spectral efficiency of wireless systems, as well as for taming the wireless environment. The potential benefits of RISs are currently being analyzed and various approaches are being proposed to address some challenges for their integration in wireless networks. Currently available studies to quantify the potential gains of deploying RISs in wireless networks are limited to simple network topologies, while no system-level assessments have been reported to date. Network-level, e.g., on the scale of hundreds of square meters, simulations are, however, the first step to quantify the actual value of emerging technologies and the steppingstone before considering large scale system-level experimental evaluations and network deployments. Towards this direction, this article reports the first system-level simulation results and analysis of an RIS deployment in a typical urban city that is served by a fifth-generation cellular network. The obtained system-level simulation results unveil that the benefits of RISs vary depending on the operating frequency and the size of the surfaces. Specifically, we investigate the performance improvement that RISs can provide, in terms of outdoor and indoor coverage and ergodic rate, when deployed in mid (C-band) and high (millimeter-wave) frequency bands. For example, the obtained results unveil that the deployment of RISs enhances the coverage of cell-edge users from 77% to 95% in the C-band and from 46% to 95% in the millimeter-wave band.

cs.IT↗

arXiv2021

Smart Radio Environments

This Roadmap takes the reader on a journey through the research in electromagnetic wave propagation control via reconfigurable intelligent surfaces. Meta-surface modelling and design methods are reviewed along with physical realisation techniques. Several wireless applications are discussed, including beam-forming, focusing, imaging, localisation, and sensing, some rooted in novel architectures for future mobile communications networks towards 6G.

physics.class-ph↗

arXiv2021

Robust Ambient Backscatter Communications with Polarization Reconfigurable Tags

Ambient backscatter communication system is an emerging and promising low-energy technology for Internet of Things. In such system, a device named tag, sends a binary message to a reader by backscattering a radio frequency signal generated by an ambient source. Such tag can operate without battery and without generating additional wave. However, the tag-to-reader link suffers from the source-to-reader direct interference. In this paper, for the first time, we propose to exploit a "polarization reconfigurable" antenna to improve robustness of the tag-to-reader link against the source-to-reader direct interference. Our proposed new tag sends its message by backscattering as an usual tag. However, it repeats its message several times, with a different radiation pattern and polarization, each time. We expect one polarization pattern to be better detected by the reader. We show by simulations and experiments, in line-of-sight and in richly scattering environment, that a polarization reconfigurable tag limited to 4 polarization directions outperforms a nonreconfigurable tag and nearly equals an ideally reconfigurable tag in performance.

eess.SP↗

arXiv2021

First experimental evaluation of ambient backscatter communications with massive MIMO reader

Ambient backscatter communications have been introduced as low-power communications for green networking. This technology is very promising as it recycles ambient radio frequency waves, however such systems have limitations and suffer from poor performance due to their low-power. In this paper, we present and evaluate the performance of an ambient backscatter system equipped with a massive multiple input multiple output (MIMO) antenna at the reader side. A mobile device transmits a signal that is backscattered by a tag and received by the reader. Thanks to the spatial diversity of the massive MIMO antenna, the reader is able to identify, for each received signal, the state of the tag (backscattering or transparent) that corresponds to a bit of the tag message. First, we experimentally determine the channel between the device and the reader for two states of the tag. Then using a minimum mean square error algorithm we evaluate the performance of the ambient backscatter communication. We demonstrate that the performance of the ambient backscatter system is significantly improved by the massive MIMO reader.

eess.SP↗

arXiv2021

Polarization-Based Reconfigurable Tags for Robust Ambient Backscatter Communications

Ambient backscatter communication is an emerging and promising low-energy technology for the Internet of Things. In such a system, a tag sends a binary message to a reader by backscattering a radio frequency signal generated by an ambient source. The tag can operate without battery and without generating additional radio waves. However, the tag-to-reader link suffers from the source-to-reader interference. In this paper, we propose a polarization-based reconfigurable antenna in order to improve the robustness of the tag-to-reader link against the source-to-reader direct interference. More precisely, we compare different types of tags' antennas, different tags' encoding schemes, and different detectors at the reader. By using analysis, numerical simulations, and experiments, we show that a polarization-based reconfigurable tag with four polarization directions significantly outperforms a non-reconfigurable tag, and provides almost the same performance as an ideal reconfigurable tag with a large number of reconfigurable polarization patterns.

eess.SP↗

arXiv2021

Controlling Smart Propagation Environments: Long-Term versus Short-Term Phase Shift Optimization

Reconfigurable intelligent surfaces (RISs) have recently gained significant interest as an emerging technology for future wireless networks. This paper studies an RIS-assisted propagation environment, where a single-antenna source transmits data to a single-antenna destination in the presence of a weak direct link. We analyze and compare RIS designs based on long-term and short-term channel statistics in terms of coverage probability and ergodic rate. For the considered optimization designs, closed-form expressions for the coverage probability and ergodic rate are derived. We use numerical simulations to analyze and compare against analytic results in finite samples. Also, we show that the considered optimal phase shift designs outperform several heuristic benchmarks.

cs.IT↗

arXiv2021

Reconfigurable Intelligent Surface (RIS) Aided Multi-User Networks: Interplay Between NOMA and RIS

This article focuses on the exploitation of reconfigurable intelligent surfaces (RISs) in multi-user networks employing orthogonal multiple access (OMA) or non-orthogonal multiple access (NOMA), with an emphasis on investigating the interplay between NOMA and RIS. Depending on whether the RIS reflection coefficients can be adjusted only once or multiple times during one transmission, we distinguish between static and dynamic RIS configurations. In particular, the capacity region of RIS aided single-antenna NOMA networks is characterized and compared with the OMA rate region from an information-theoretic perspective, revealing that the dynamic RIS configuration is capacity-achieving. Then, the impact of the RIS deployment location on the performance of different multiple access schemes is investigated, which reveals that asymmetric and symmetric deployment strategies are preferable for NOMA and OMA, respectively. Furthermore, for RIS aided multiple-antenna NOMA networks, three novel joint active and passive beamformer designs are proposed based on both beamformer based and cluster based strategies. Finally, open research problems for RIS-NOMA networks are highlighted.

cs.IT↗

arXiv2021

Intelligent Omni-Surfaces for Full-Dimensional Wireless Communications: Principle, Technology, and Implementation

The recent development of metasurfaces has motivated their potential use for improving the performance of wireless communication networks by manipulating the propagation environment through nearly-passive sub-wavelength scattering elements arranged on a surface. However, most studies of this technology focus on reflective metasurfaces, i.e., the surface reflects the incident signals towards receivers located on the same side of the transmitter, which restricts the coverage to one side of the surface. In this article, we introduce the concept of intelligent omni-surface (IOS), which is able to serve mobile users on both sides of the surface to achieve full-dimensional communications by jointly engineering its reflective and refractive properties. The working principle of the IOS is introduced and a novel hybrid beamforming scheme is proposed for IOS-based wireless communications. Moreover, we present a prototype of IOS-based wireless communications and report experimental results. Furthermore, potential applications of the IOS to wireless communications together with relevant research challenges are discussed.

cs.IT↗

arXiv2021

RIS and Cell-Free Massive MIMO: A Marriage For Harsh Propagation Environments

This paper considers Cell-Free Massive Multiple Input Multiple Output (MIMO) systems with the assistance of an RIS for enhancing the system performance. Distributed maximum-ratio combining (MRC) is considered at the access points (APs). We introduce an aggregated channel estimation method that provides sufficient information for data processing. The considered system is studied by using asymptotic analysis which lets the number of APs and/or the number of RIS elements grow large. A lower bound for the channel capacity is obtained for a finite number of APs and engineered scattering elements of the RIS, and closed-form expression for the uplink ergodic net throughput is formulated. In addition, a simple scheme for controlling the configuration of the RIS scattering elements is proposed. Numerical results verify the effectiveness of the proposed system design and the benefits of using RISs in Cell-Free Massive MIMO systems are quantified.

cs.IT↗

arXiv2021

Achievable Rate Optimization for MIMO Systems with Reconfigurable Intelligent Surfaces

Reconfigurable intelligent surfaces (RISs) represent a radical new technology that can shape the radio wave propagation in wireless communication systems and offers a great variety of possible performance and implementation gains. Motivated by this, in this paper we study the achievable rate optimization for a multi-stream multiple-input multiple-output (MIMO) system equipped with an RIS, and formulate a joint optimization problem of the covariance matrix of the transmitted signal and the RIS elements. To solve this problem, we propose an iterative optimization algorithm that is based on the projected gradient method (PGM). We derive the step size that guarantees the convergence of the proposed algorithm and we define a backtracking line search to improve its convergence rate. Furthermore, we introduce the total free space path loss (FSPL) ratio of the indirect and direct links as a first-order measure of the applicability of an RIS in the considered communication system. Simulation results show that the proposed PGM achieves the same achievable rate as a state-of-the-art benchmark scheme, but with a significantly lower computational complexity. In addition, it is demonstrated that the RIS application is particularly suitable to increase the achievable rate in an indoor environment, as in this case even a small number of RIS elements is sufficient to provide a substantial achievable rate gain.

cs.IT↗

arXiv2021

Optimization of RIS-aided MIMO Systems via the Cutoff Rate

The main difficulty concerning optimizing the mutual information (MI) in reconfigurable intelligent surface (RIS)-aided communication systems with discrete signaling is the inability to formulate this optimization problem in an analytically tractable manner. Therefore, we propose to use the cutoff rate (CR) as a more tractable metric for optimizing the MI and introduce two optimization methods to maximize the CR, assuming perfect knowledge of the channel state information (CSI). The first method is based on the projected gradient method (PGM), while the second method is derived from the principles of successive convex approximation (SCA). Simulation results show that the proposed optimization methods significantly enhance the CR and the corresponding MI.

cs.IT↗

arXiv2021

On the Achievable Sum-rate of the RIS-aided MIMO Broadcast Channel

Reconfigurable intelligent surfaces (RISs) represent a new technology that can shape the radio wave propagation and thus offers a great variety of possible performance and implementation gains. Motivated by this, we investigate the achievable sum-rate optimization in a broadcast channel (BC) that is equipped with an RIS. We exploit the well-known duality between the Gaussian multiple-input multiple-output (MIMO) BC and multiple-access channel (MAC) to derive an alternating optimization (AO) algorithm which optimizes the users' covariance matrices and the RIS phase shifts in the dual MAC. The optimal users' covariance matrices are obtained by a dual decomposition method in which each iteration is solved in closed-form. The optimal RIS phase shifts are also computed using a derived closed-form expression. Furthermore, we present a computational complexity analysis for the proposed AO algorithm. Simulation results show that the proposed AO algorithm can provide significant achievable sum-rate gains in a BC.

cs.IT↗

arXiv2021

Spectrum Learning-Aided Reconfigurable Intelligent Surfaces for 'Green' 6G Networks

In the sixth-generation (6G) era, emerging large-scale computing based applications (for example processing enormous amounts of images in real-time in autonomous driving) tend to lead to excessive energy consumption for the end users, whose devices are usually energy-constrained. In this context, energy-efficiency becomes a critical challenge to be solved for harnessing these promising applications to realize 'green' 6G networks. As a remedy, reconfigurable intelligent surfaces (RIS) have been proposed for improving the energy efficiency by beneficially reconfiguring the wireless propagation environment. In conventional RIS solutions, however, the received signal-to-interference-plus-noise ratio (SINR) sometimes may even become degraded. This is because the signals impinging upon an RIS are typically contaminated by interfering signals which are usually dynamic and unknown. To address this issue, `learning' the properties of the surrounding spectral environment is a promising solution, motivating the convergence of artificial intelligence and spectrum sensing, termed here as spectrum learning (SL). Inspired by this, we develop an SL-aided RIS framework for intelligently exploiting the inherent characteristics of the radio frequency (RF) spectrum for green 6G networks. Given the proposed framework, the RIS controller becomes capable of intelligently `{think-and-decide}' whether to reflect or not the incident signals. Therefore, the received SINR can be improved by dynamically configuring the binary ON-OFF status of the RIS elements. The energy-efficiency benefits attained are validated with the aid of a specific case study. Finally, we conclude with a list of promising future research directions.

eess.SP↗

arXiv2021

Fairness-Oriented Multiple RISs-Aided MmWave Transmission: Stochastic Optimization Methods

In millimeter wave (mmWave) systems, it is challenging to ensure the reliable connectivity of communications due to its sensitivity to the presence of blockages. In order to improve the robustness of the mmWave system under the presence of the random blockages, multiple reconfigurable intelligent surfaces (RISs) are deployed to enhance the spatial diversity gain, and robust beamforming is then designed based on a stochastic optimization for minimizing the maximum outage probability among multiple users to ensure the fairness. Under the stochastic optimization framework, we adopt the stochastic majorization--minimization (SMM) method and the stochastic successive convex approximation (SSCA) method to construct deterministic surrogate problems at each iteration for new channel realizations, and obtain the closed-form solutions of the precoding matrix at the base station (BS) and the passive beamforming vectors at the RISs. Both stochastic optimization methods have been proved to converge to the set of stationary points of the original stochastic problems. Finally, simulation results show that the proposed robust beamforming in the RIS-aided system can effectively compensate for the performance loss caused by the presence of the random blockages, especially at high blockage probability, compared with the benchmark solutions.

cs.IT↗