arXiv subjects

Elisabeth De Carvalho

Publications and source records attributed to Elisabeth De Carvalho.

17 recordsLinked to original sources

arXiv2022

Electromagnetic Based Communication Model for Dynamic Metasurface Antennas

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.

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arXiv2022

Tensor-based Channel Tracking for RIS-Empowered Multi-User MIMO Wireless Systems

The accurate estimation of Channel State Information (CSI) is of crucial importance for the successful operation of Multiple-Input Multiple-Output (MIMO) communication systems, especially in a Multi-User (MU) time-varying environment and when employing the emerging technology of Reconfigurable Intelligent Surfaces (RISs). Their predominantly passive nature renders the estimation of the channels involved in the user-RIS-base station link a quite challenging problem. Moreover, the time-varying nature of most of the realistic wireless channels drives up the cost of real-time channel tracking significantly, especially when RISs of massive size are deployed. In this paper, we develop a channel tracking scheme for the uplink of RIS-enabled MU MIMO systems in the presence of channel fading. The starting point is a tensor representation of the received signal and we rely on its PARAllel FACtor (PARAFAC) analysis to both get the initial estimate and track the channel time variation. Simulation results for various system settings are reported, which validate the feasibility and effectiveness of the proposed channel tracking approach.

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arXiv2021

Reconfigurable, Intelligent, and SustainableWireless Environments for 6G Smart Connectivity

Various visions on the forthcoming sixth Generation (6G) networks point towards flexible connect-and-compute technologies to support future innovative services and the corresponding use cases. 6G should be capable to accommodate ever-evolving and heterogeneous applications, future regulations, and diverse user-, service-, and location-based requirements. A key element towards building smart and energy sustainable wireless systems beyond 5G is the Reconfigurable Intelligent Surface (RIS), which offers programmable control and shaping of the wireless propagation environment. Capitalizing on this technology potential, in this article we introduce two new concepts: i) wireless environment as a service, which leverages a novel RIS-empowered networking paradigm to trade off diverse, and usually conflicting, connectivity objectives; and ii) performance-boosted areas enabled by RIS-based connectivity, representing competing service provisioning areas that are highly spatially and temporally focused. We discuss the key technological enablers and research challenges with the proposed networking paradigm, and highlight the potential profound role of RISs in the recent Open Radio Access Network (O-RAN) architecture.

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arXiv2021

Wireless Environment as a Service Enabled by Reconfigurable Intelligent Surfaces: The RISE-6G Perspective

The design of 6th Generation (6G) wireless networks points towards flexible connect-and-compute technologies capable to support innovative services and use cases. Targeting the 2030 horizon, 6G networks are poised to pave the way for sustainable human-centered smart societies and vertical industries, such that wireless networks will be transformed into a distributed smart connectivity infrastructure, where new terminal types are embedded in the daily environment. In this context, the RISE-6G project aims at investigating innovative solutions that capitalize on the latest advances in the emerging technology of Reconfigurable Intelligent Surfaces (RISs), which offers dynamic and goal-oriented radio wave propagation control, enabling the concept of the wireless environment as a service. The project will focus on: i) the realistic modeling of RIS-assisted signal propagation, ii) the investigation of the fundamental limits of RIS-empowered wireless communications and sensing, and iii) the design of efficient algorithms for orchestrating networking RISs, in order to implement intelligent, sustainable, and dynamically programmable wireless environments enabling diverse services that go well beyond the 5G capabilities. RISE-6G will offer two unprecedented proof-of-concepts for realizing controlled wireless environments in near-future use cases.

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arXiv2020

Frequency-Mixing Intelligent Reflecting Surfaces for Nonlinear Wireless Propagation

We introduce the concept of frequency-mixing intelligent reflecting surface (FMx-IRS), where the elements of the surface continuously change the phases of the incident signals. In this way, the FMx-IRS acts as a frequency mixer and makes the propagation environment nonlinear, thereby introducing new frequencies. We study the basic features of the proposed concept and demonstrate its advantages that stem from the novel type of control over the wireless propagation. The channel decoupling feature and the correlation between reflected channels are elaborated for the architecture, and are validated by the simulations.

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arXiv2020

Intelligent Reflecting Surface Operation under Predictable Receiver Mobility: A Continuous Time Propagation Model

The operation of an intelligent reflecting surface (IRS) under predictable receiver mobility is investigated. We develop a continuous time system model for multipath channels and discuss the optimal IRS configuration with respect to received power, Doppler spread, and delay spread. It is shown that the received power can be maximized without adding Doppler spread to the system. In a numerical case study, we show that an IRS having the size of just two large billboards can improve the link budget of ground to Low Earth Orbit (LEO) satellite links by up to 6 dB. It also adds a second, almost equivalently strong, communication path that improves the link reliability.

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arXiv2020

Outage Analysis of Downlink URLLC in Massive MIMO systems with Power Allocation

Massive MIMO is seen as a main enabler for low latency communications, thanks to its high spatial degrees of freedom. The channel hardening and favorable propagation properties of Massive MIMO are particularly important for multiplexing several URLLC devices. However, the actual utility of channel hardening and spatial multiplexing is dependent critically on the accuracy of channel knowledge. When several low latency devices are multiplexed, the cost for acquiring accurate knowledge becomes critical, and it is not evident how many devices can be served with a latency-reliability requirement and how many pilot symbols should be allocated. This paper investigates the trade-off between achieving high spectral efficiency and high reliability in the downlink, by employing various power allocation strategies, for maximum ratio and minimum mean square error precoders. The results show that using max-min SINR power allocation achieves the best reliability, at the expense of lower sum spectral efficiency.

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arXiv2020

A Communication Model for Large Intelligent Surfaces

The purpose of this paper is to introduce a communication model for Large Intelligent Surfaces (LIS). A LIS is modelled 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 modelling the surface as continuous. The gain is theoretically unbounded as the element density increases for a constant aperture.

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arXiv2019

An Optimal Channel Estimation Scheme for Intelligent Reflecting Surfaces based on a Minimum Variance Unbiased Estimator

In a wireless system with Intelligent Reflective Surfaces (IRS) containing many passive elements, we consider the problem of channel estimation. All the links from the transmitter to the receiver via each IRS elements (or groups) are estimated. As the estimation performance are dependent on the setting of the IRS, we design an optimal channel estimation scheme where the IRS elements follow an optimal series of activation patterns. The optimal design is guided by results for the minimum variance unbiased estimation. The IRS setting during the channel estimation period mimics a series of discrete Fourier transforms. We show theoretically and with simulations that the estimation variance is one order smaller compared to existing on/off methods proposed in the literature.

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arXiv2019

Non-Stationarities in Extra-Large Scale Massive MIMO

Massive MIMO, a key technology for increasing area spectral efficiency in cellular systems, was developed assuming moderately sized apertures. In this paper, we argue that massive MIMO systems behave differently in large-scale regimes due to spatial non-stationarity. In the large-scale regime, with arrays of around fifty wavelengths, the terminals see the whole array but non-stationarities occur because different regions of the array see different propagation paths. At even larger dimensions, which we call the extra-large scale regime, terminals see a portion of the array and inside the first type of non-stationarities might occur. We show that the non-stationarity properties of the massive MIMO channel changes several important MIMO design aspects. In simulations, we demonstrate how non-stationarity is a curse when neglected but a blessing when embraced in terms of computational load and multi-user transceiver design.

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arXiv2019

Stochastic Geometric Coverage Analysis in mmWave Cellular Networks with Realistic Channel and Antenna Radiation Models

Millimeter-wave (mmWave) bands will play an important role in 5G wireless systems. The system performance can be assessed by using models from stochastic geometry that cater for the directivity in the desired signal transmissions as well as the interference, and by calculating the signal-to-interference-plus-noise ratio (SINR) coverage. Nonetheless, the correctness of the existing coverage expressions derived through stochastic geometry may be questioned, as it is not clear whether they capture the impact of the detailed mmWave channel and antenna features. In this study, we propose an SINR coverage analysis framework that includes realistic channel model (from NYU) and antenna element radiation patterns (with isotropic/directional radiation). We first introduce two parameters, aligned gain and misaligned gain, associated with the desired signal beam and the interfering signal beam, respectively. We provide the distributions of the aligned and misaligned gains through curve fitting of system-simulation results. The distribution of these gains is used to determine the distribution of the SINR. We compare the obtained analytical SINR coverage with the corresponding SINR coverage calculated via system-level simulations. The results show that both aligned and misaligned gains can be modeled as exponential-logarithmically distributed random variables with the highest accuracy, and can further be approximated as exponentially distributed random variables with reasonable accuracy. These approximations are thus expected to be useful to evaluate the system performance under ultra-reliable and low-latency communication (URLLC) and evolved mobile broadband (eMBB) scenarios, respectively.

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arXiv2018

Sparse Signal Processing for Grant-Free Massive Connectivity: A Future Paradigm for Random Access Protocols in the Internet of Things

The next wave of wireless technologies will proliferate in connecting sensors, machines, and robots for myriad new applications, thereby creating the fabric for the Internet of Things (IoT). A generic scenario for IoT connectivity involves a massive number of machine-type connections. But in a typical application, only a small (unknown) subset of devices are active at any given instant, thus one of the key challenges for providing massive IoT connectivity is to detect the active devices first and then to decode their data with low latency. This article outlines several key signal processing techniques that are applicable to the problem of massive IoT access, focusing primarily on advanced compressed sensing technique and its application for efficient detection of the active devices. We show that massive multiple-input multiple-output (MIMO) is especially well-suited for massive IoT connectivity in the sense that the device detection error can be driven to zero asymptotically in the limit as the number of antennas at the base station goes to infinity by using the multiple-measurement vector (MMV) compressed sensing techniques. The paper also provides a perspective on several related important techniques for massive access, such as embedding of short messages onto the device activity detection process and the coded random access.

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arXiv2017

Hybrid Precoding for Massive MIMO Systems in Cloud RAN Architecture with Capacity-Limited Fronthauls

Cloud RAN (C-RAN) is a promising enabler for distributed massive MIMO systems, yet is vulnerable to its fronthaul congestion. To cope with the limited fronthaul capacity, this paper proposes a hybrid analog-digital precoding design that adaptively adjusts fronthaul compression levels and the number of active radio-frequency (RF) chains out of the entire RF chains in a downlink distributed massive MIMO system based on C-RAN architecture. Following this structure, we propose an analog beamformer design in pursuit of maximizing multi-user sum average data rate (sum-rate). Each element of the analog beamformer is constructed based on a weighted sum of spatial channel covariance matrices, while the size of the analog beamformer, i.e. the number of active RF chains, is optimized so as to maximize the large-scale approximated sum-rate. With these analog beamformer and RF chain activation, a regularized zero- forcing (RZF) digital beamformer is jointly optimized based on the instantaneous effective channel information observed through the given analog beamformer. The effectiveness of the proposed hybrid precoding algorithm is validated by simulation, and its design criterion is clarified by analysis.

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arXiv2017

Stochastic Geometric Coverage Analysis in mmWave Cellular Networks with a Realistic Channel Model

Millimeter-wave (mmWave) bands have been attracting growing attention as a possible candidate for next-generation cellular networks, since the available spectrum is orders of magnitude larger than in current cellular allocations. To precisely design mmWave systems, it is important to examine mmWave interference and SIR coverage under large-scale deployments. For this purpose, we apply an accurate mmWave channel model, derived from experiments, into an analytical framework based on stochastic geometry. In this way we obtain a closed-form SIR coverage probability in large-scale mmWave cellular networks.

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arXiv2016

Geometry-Based Stochastic Channel Models for 5G: Extending Key Features for Massive MIMO

This paper introduces three key features in geometry-based stochastic channel models in order to include massive MIMO channels. Those key features consists of multi-user (MU) consistency, non-stationarities across the base station array and inclusion of spherical wave modelling. To ensure MU consistency, we introduce the concept of "user aura", which is a circle around the user with radius defined according to the stationarity interval. The overlap between auras determines the share of common clusters among users. To model non-stationarities across a massive array, sub-arrays are defined for which clusters are independently generated. At last, we describe a procedure to incorporate spherical wave modelling, where a cluster focal point is defined to account for distance between user and cluster.

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arXiv2016

Design and Performance Analysis of Non-Coherent Detection Systems with Massive Receiver Arrays

Harvesting the gain of a large number of antennas in a mmWave band has mainly been relying on the costly operation of channel state information (CSI) acquisition and cumbersome phase shifters. Recent works have started to investigate the possibility to use receivers based on energy detection (ED), where a single data stream is decoded based on the channel and noise energy. The asymptotic features of the massive receiver array lead to a system where the impact of the noise becomes predictable due to a noise hardening effect. This in effect extends the communication range compared to the receiver with a small number of antennas, as the latter is limited by the unpredictability of the additive noise. When the channel has a large number of spatial degrees of freedom, the system becomes robust to imperfect channel knowledge due to channel hardening. We propose two detection methods based on the instantaneous and average channel energy, respectively. Meanwhile, we design the detection thresholds based on the asymptotic properties of the received energy. Differently from existing works, we analyze the scaling law behavior of the symbol-error-rate (SER). When the instantaneous channel energy is known, the performance of ED approaches that of the coherent detection in high SNR scenarios. When the receiver relies on the average channel energy, our performance analysis is based on the exact SER, rather than an approximation. It is shown that the logarithm of SER decreases linearly as a function of the number of antennas. Additionally, a saturation appears at high SNR for PAM constellations of order larger than two, due to the uncertainty on the channel energy. Simulation results show that ED, with a much lower complexity, achieves promising performance both in Rayleigh fading channels and in sparse channels.

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arXiv2015

Towards Very Large Aperture Massive MIMO: a measurement based study

Massive MIMO is a new technique for wireless communications that claims to offer very high system throughput and energy efficiency in multi-user scenarios. The cost is to add a very large number of antennas at the base station. Theoretical research has probed these benefits, but very few measurements have showed the potential of Massive MIMO in practice. We investigate the properties of measured Massive MIMO channels in a large indoor venue. We describe a measurement campaign using 3 arrays having different shape and aperture, with 64 antennas and 8 users with 2 antennas each. We focus on the impact of the array aperture which is the main limiting factor in the degrees of freedom available in the multiple antenna channel. We find that performance is improved as the aperture increases, with an impact mostly visible in crowded scenarios where the users are closely spaced. We also test MIMO capability within a same user device with user proximity effect. We see a good channel resolvability with confirmation of the strong effect of the user hand grip. At last, we highlight that propagation conditions where line-of-sight is dominant can be favorable.

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