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The advent of the sixth-generation (6G) networks presents another round of revolution for the mobile communication landscape, promising an immersive experience, robust reliability, minimal latency, extreme connectivity, ubiquitous coverage, and capabilities beyond communication, including intelligence and sensing. To achieve these ambitious goals, it is apparent that 6G networks need to incorporate the state-of-the-art technologies. One of the technologies that has garnered rising interest is fluid antenna system (FAS) which represents any software-controllable fluidic, conductive, or dielectric structure capable of dynamically changing its shape and position to reconfigure essential radio-frequency (RF) characteristics. Compared to traditional antenna systems (TASs) with fixed-position radiating elements, the core idea of FAS revolves around the unique flexibility of reconfiguring the radiating elements within a given space. One recent driver of FAS is the recognition of its position-flexibility as a new degree of freedom (dof) to harness diversity and multiplexing gains. In this paper, we provide a comprehensive tutorial, covering channel modeling, signal processing and estimation methods, information-theoretic insights, new multiple access techniques, and hardware designs. Moreover, we delineate the challenges of FAS and explore the potential of using FAS to improve the performance of other contemporary technologies. By providing insights and guidance, this tutorial paper serves to inspire researchers to explore new horizons and fully unleash the potential of FAS., Comment: 50 pages, 45 figures, 5 tables. Submitted for potential publication

Estimating the probability of rare channel conditions is a central challenge in ultra-reliable wireless communication, where random events, such as deep fades, can cause sudden variations in the channel quality. This paper proposes a sample-efficient framework for predicting the statistics of such events by utilizing spatial dependency between channel measurements acquired from various locations. The proposed framework combines radio maps with non-parametric models and extreme value theory (EVT) to estimate rare-event channel statistics under a Bayesian formulation. The framework can be applied to a wide range of problems in wireless communication and is exemplified by rate selection in ultra-reliable communications. Notably, besides simulated data, the proposed framework is also validated with experimental measurements. The results in both cases show that the Bayesian formulation provides significantly better results in terms of throughput compared to baselines that do not leverage measurements from surrounding locations. It is also observed that the models based on EVT are generally more accurate in predicting rare-event statistics than non-parametric models, especially when only a limited number of channel samples are available. Overall, the proposed methods can significantly reduce the number of measurements required to predict rare channel conditions and guarantee reliability., Comment: Submitted for IEEE Transaction on Communications

Powered by position-flexible antennas, the emerging fluid antenna system (FAS) technology postulates as a key enabler for massive connectivity in 6G networks. The free movement of antenna elements enables the opportunistic minimization of interference, allowing several users to share the same radio channel without the need of precoding. However, the true potential of FAS is still unknown due to the extremely high spatial correlation of the wireless channel between very close-by antenna positions. To unveil the multiplexing capabilities of FAS, proper (simple yet accurate) modeling of the spatial correlation is prominently needed. Realistic classical models such as Jakes' are prohibitively complex, rendering intractable analyses, while state-of-the-art approximations often are too simplistic and poorly accurate. Aiming to fill this gap, we here propose a general framework to approximate spatial correlation by block-diagonal matrices, motivated by the well-known block fading assumption and by statistical results on large correlation matrices. The proposed block-correlation model makes the performance analysis possible, and tightly approximates the results obtained with realistic models (Jakes' and Clarke's). Our framework is leveraged to analyze fluid antenna multiple access (FAMA) systems, evaluating their performance for both one- and two-dimensional fluid antennas.

Location information is often used as a proxy to guarantee the performance of a wireless communication link. However, localization errors can result in a significant mismatch with the guarantees, particularly detrimental to users operating the ultra-reliable low-latency communication (URLLC) regime. This paper unveils the fundamental statistical relations between location estimation uncertainty and wireless link reliability, specifically in the context of rate selection for ultra-reliable communication. We start with a simple one-dimensional narrowband Rayleigh fading scenario and build towards a two-dimensional scenario in a rich scattering environment. The wireless link reliability is characterized by the meta-probability, the probability with respect to localization error of exceeding the outage capacity, and by removing other sources of errors in the system, we show that reliability is sensitive to localization errors. The $\epsilon$-outage coherence radius is defined and shown to provide valuable insight into the problem of location-based rate selection. However, it is generally challenging to guarantee reliability without accurate knowledge of the propagation environment. Finally, several rate-selection schemes are proposed, showcasing the problem's dynamics and revealing that properly accounting for the localization error is critical to ensure good performance in terms of reliability and achievable throughput., Comment: Submitted for IEEE Transactions of Wireless Communications on July 16th 2023

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.

High reliability guarantees for Ultra-Reliable Low-Latency Communications (URLLC) require accurate knowledge of channel statistics, used as an input for rate selection. Exploiting the spatial consistency of channel statistics arises as a promising solution, allowing a base station to predict the propagation conditions and select the communication parameters for a new user from samples collected from previous users of the network. Based on this idea, this article provides a timely framework to exploit long-range channel spatial correlation through so-called statistical radio maps, enabling URLLC communications with given statistical guarantees. The framework is exemplified by predicting the channel capacity distribution both in a location-based radio map and in a latent space rendered by a channel chart, the latter being a localization-free approach based on channel state information (CSI). It is also shown how to use the maps to select the transmission rate in a new location that achieves a target level of reliability. Finally, several future directions and research challenges are also discussed., Comment: 6 figures in total. Submitted for publication

This paper evaluates the performance of multi-user massive multiple-input multiple-output (MIMO) systems in which the base station is equipped with a dynamic metasurface antenna (DMA). Due to the physical implementation of DMAs, conventional models widely-used in MIMO are no longer valid, and electromagnetic phenomena such as mutual coupling, insertion losses and reflections inside the waveguides need to be considered. Hence, starting from a recently proposed electromagnetic model for DMAs, we formulate a zero-forcing optimization problem, yielding an unconstrained objective function with known gradient. The performance is compared with that of full-digital and hybrid massive MIMO, focusing on the impact of insertion losses and mutual coupling.

This paper proposes exploiting the spatial correlation of wireless channel statistics beyond the conventional received signal strength maps by constructing statistical radio maps to predict any relevant channel statistics to assist communications. Specifically, from stored channel samples acquired by previous users in the network, we use Gaussian processes (GPs) to estimate quantiles of the channel distribution at a new position using a non-parametric model. This prior information is then used to select the transmission rate for some target level of reliability. The approach is tested with synthetic data, simulated from urban micro-cell environments, highlighting how the proposed solution helps to reduce the training estimation phase, which is especially attractive for the tight latency constraints inherent to ultra-reliable low-latency (URLLC) deployments., Comment: Accepted for IEEE Globecom 2022. Contains five figures

Massive MIMO base stations use multiple spatial diversity branches, which are often assumed to be uncorrelated in theoretical work. Correlated branches are considered seldom since they are mathematically less tractable. For correlated Rician fading, only the first- and second-order moments have been explored. To describe propagation environments more accurately, full distribution functions are needed. This manuscript provides these functions for the maximum ratio combining effective channel, a quadratic form of a random complex normal channel vector. Its mean vector and covariance matrix are based on a plane wave model incorporating array geometry, antenna element pattern, power angular spectra and power delay profiles. Closed-form approximations of the distribution functions are presented, to allow the fast evaluation of many real-world scenarios. The statistical framework is used to show that low-directivity antenna elements provide better performance in angular constricted Rician fading with off-axis incidence than high-directivity elements. Moreover, two base station array layouts are compared, showing that a half-circle array illuminates a cell more evenly than a uniform linear array. With the full distribution functions available, performance can be compared over the full range of received powers and not only based on the average SNR., Comment: 10 pages, 10 figures, 1 table, under review

This paper leverages the potential of Large Intelligent Surface (LIS) for radio sensing in 6G wireless networks. Major research has been undergone about its communication capabilities but it can be exploited as a formidable tool for radio sensing. By taking advantage of arbitrary communication signals occurring in the scenario, we apply direct processing to the output signal from the LIS to obtain a radio map that describes the physical presence of passive devices (scatterers, humans) which act as virtual sources due to the communication signal reflections. We then assess the usage of machine learning (k-means clustering), image processing and computer vision (template matching and component labeling) to extract meaningful information from these radio maps. As an exemplary use case, we evaluate this method for both active and passive user detection in an indoor setting. The results show that the presented method has high application potential as we are able to detect around 98% of humans passively and 100% active users by just using communication signals of commodity devices even in quite unfavorable Signal-to-Noise Ratio (SNR) conditions.

Location information is often used as a proxy to infer the performance of a wireless communication link. Using a very simple model, this letter unveils a basic statistical relation between the location estimation uncertainty and wireless link reliability. First, a Cram\'er-Rao bound for the localization error is derived. Then, wireless link reliability is characterized by how likely the outage probability is to be above a target threshold. We show that the reliability is sensitive to location errors, especially when the channel statistics are also sensitive to the location. Finally, we highlight the difficulty of choosing a rate that meets target reliability while accounting for the location uncertainty., Comment: 6 pages and 3 figures. This is an extended version of the article submitted to IEEE Wireless Communication Letters. The extension differs from the letter in section V, which here contain some derivations

Sensing capability is one of the most highlighted new feature of future 6G wireless networks. This paper addresses the sensing potential of Large Intelligent Surfaces (LIS) in an exemplary Industry 4.0 scenario. Besides the attention received by LIS in terms of communication aspects, it 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 relying on the received signal power, we develop techniques to sense the environment, by leveraging the tools of image processing and machine learning. Once a holographic image is obtained, a Denoising Autoencoder (DAE) network can be used for constructing a super-resolution image leading to sensing advantages not available in traditional sensing systems. Also, we derive a statistical test based on the Generalized Likelihood Ratio (GLRT) as a benchmark for the machine learning solution. 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., Comment: arXiv admin note: text overlap with arXiv:2006.06563

This paper proposes a communication model for multiuser multiple-input multiple-output (MIMO) systems based on large intelligent surfaces (LIS), where the LIS is modeled as a collection of tightly packed antenna elements. The LIS system is first represented in a circuital way, obtaining expressions for the radiated and received powers, as well as for the coupling between the distinct elements. Then, this circuital model is used to characterize the channel in a line-of-sight propagation scenario, rendering the basis for the analysis and design of MIMO systems. Due to the particular properties of LIS, the model accounts for superdirectivity and mutual coupling effects along with near field propagation, necessary in those situations where the array dimension becomes very large. Finally, with the proposed model, the matched filter transmitter and the weighted minimum mean square error precoding are derived under both realistic constraints: limited radiated power and maximum ohmic losses., Comment: 6 pages, 3 figures; This paper is submitted to IEEE International Conference on Communications (ICC) 2021

The physical layer security (PLS) performance of a wireless communication link through a large reflecting surface (LRS) with phase errors is analyzed. Leveraging recent results that express the \ac{LRS}-based composite channel as an equivalent scalar fading channel, we show that the eavesdropper's link is Rayleigh distributed and independent of the legitimate link. The different scaling laws of the legitimate and eavesdroppers signal-to-noise ratios with the number of reflecting elements, and the reasonably good performance even in the case of coarse phase quantization, show the great potential of LRS-aided communications to enhance PLS in practical wireless set-ups., Comment: This work has been submitted to the IEEE for publication. Copyright may be transferred without notice, after which this version may no longer be accessible

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.

In this paper, we investigate the impact of correlation between the energy and information links in wireless power transfer systems, from a physical layer security perspective. With that aim, we first determine how correlation can affect system capacity in practical energy harvesting set-ups in the absence of eavesdroppers. We quantify that even though link correlation improves the average signal-to-noise ratio (SNR) for a fixed transmit power, it also increases its variance, which ultimately degrades capacity. Based on this observation, we show that correlation between the energy and information links may be detrimental/beneficial for the secrecy capacity in the high/low legitimate SNR regime, whenever such correlation affects the legitimate user. Conversely, we also point out that when link correlation for the wiretap link is rigorously accounted for, it barely affects secrecy performance, causing only a minor degradation in some instances., Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible

We show that for a legitimate communication under multipath quasi-static fading with a reduced number of scatterers, it is possible to achieve perfect secrecy even in the presence of a passive eavesdropper for which no channel state information is available. Specifically, we show that the outage probability of secrecy capacity (OPSC) is zero for a given range of average signal-to-noise ratios (SNRs) at the legitimate and eavesdropper's receivers. As an application example, we analyze the OPSC for the case of two scatterers, explicitly deriving the relationship between the average SNRs, the secrecy rate $R_s$ and the fading model parameters required for achieving perfect secrecy. The impact of increasing the number of scatterers is also analyzed, showing that it is always possible to achieve perfect secrecy in this scenario, provided that the dominant specular component for the legitimate channel is sufficiently large compared to the remaining scattered waves.

We introduce a general approach to characterize composite fading models based on inverse gamma (IG) shadowing. We first determine to what extent the IG distribution is an adequate choice for modeling shadow fading, by means of a comprehensive test with field measurements and other distributions conventionally used for this purpose. Then, we prove that the probability density function and cumulative distribution function of any IG-based composite fading model are directly expressed in terms of a Laplace-domain statistic of the underlying fast fading model and, in some relevant cases, as a mixture of wellknown state-of-the-art distributions. Also, exact and asymptotic expressions for the outage probability are provided, which are valid for any choice of baseline fading distribution. Finally, we exemplify our approach by presenting several application examples for IG-based composite fading models, for which their statistical characterization is directly obtained in a simple form., Comment: This work has been submitted to the IEEE for publication. Copyright may be transferred without notice, after which this version may no longer be accessible

We introduce the {\alpha}-{\kappa}-{\mu} shadowed ({\alpha}-KMS) fading distribution as a natural generalization of the versatile {\alpha}-{\kappa}-{\mu} and {\alpha}-{\eta}-{\mu} distributions. The {\alpha}-KMS fading distribution unifies a wide set of fading distributions, as it includes the {\alpha}-{\kappa}-{\mu}, {\alpha}- {\eta}-{\mu}, {\alpha}-{\mu}, Weibull, {\kappa}-{\mu} shadowed, Rician shadowed, {\kappa}-{\mu} and {\eta}- {\mu} distributions as special cases, together with classical models like Rice, Nakagami-m, Hoyt, Rayleigh and one-sided Gaussian. Notably, the {\alpha}-KMS distribution reduces to a finite mixture of {\alpha}-{\mu} distributions when the fading parameters {\mu} and m take positive integer values, so that performance analysis over {\alpha}-KMS fading channels can be tackled by leveraging previous (existing) results in the literature for the simpler {\alpha}-{\mu} case. As application examples, important performance metrics like the outage probability and average channel capacity are analyzed., Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible

This paper proposes a novel approach to the statistical characterization of non-central complex Gaussian quadratic forms (CGQFs). Its key strategy is the generation of an auxiliary random variable (RV) that converges in distribution to the original CGQF. Since the mean squared error between both is given in a simple closed-form formulation, the auxiliary RV can be particularized to achieve the required accuracy. The technique is valid for both definite and indefinite CGQFs and yields simple expressions of the probability density function (PDF) and the cumulative distribution function (CDF) that involve only elementary functions. This overcomes a major limitation of previous approaches, in which the complexity of the resulting PDF and CDF prevents from using them for subsequent calculations. To illustrate this end, the proposed method is applied to maximal ratio combining systems over correlated Rician channels, for which the outage probability and the average bit error rate are derived.

We here introduce an extension and natural generalization of both the \kappa-\mu$\,$shadowed and the classical Beckmann fading models: the Fluctuating Beckmann (FB) fading model. This new model considers the clustering of multipath waves on which the line-of-sight (LoS) components randomly fluctuate, together with the effect of in-phase/quadrature power imbalance in the LoS and non-LoS components. Thus, it unifies a variety of important fading distributions as the one-sided Gaussian, Rayleigh, Nakagami-m, Rician, \kappa-\mu, \eta-\mu, \eta-\kappa, Beckmann, Rician shadowed and the \kappa-\mu$\,$shadowed distribution. The chief probability functions of the FB fading model, namely probability density function, cumulative distribution function and moment generating function are derived. The second-order statistics such as the level crossing rate and the average fade duration are also analyzed. These results can be used to derive some performance metrics of interest of wireless communication systems operating over FB fading channels., Comment: This work has been submitted to the IEEE for publication. Copyright may be transferred without notice, after which this version may no longer be accesible