Communication Modes with Large Intelligent Surfaces in the near Field

This paper proposes a practical method for the definition of communication modes when antennas operate in the near-field region, by realizing ad-hoc beams exploiting the focusing capability of large antennas. The beamspace modeling proposed to define the communication modes is then exploited to derive expressions for their number (i.e., the degrees of freedom) in a generic setup, beyond the traditional paraxial scenario, together with closed-form definitions for the basis set at the transmitting and receiving antennas for several cases of interest, such as for the communication between a large antenna and a small antenna. Numerical results show that quasi-optimal communication can be obtained starting from focusing functions. This translates into the possibility of a significant enhancement of the channel capacity even in line-of-sight channel condition, without the need of implementing optimal but complex phase/amplitude profiles on transmitting/receiving antennas as well as resorting to intensive numerical solutions. Traditional results valid under paraxial approximation are revised in light of the proposed modeling, showing that similar conclusions can be obtained from different perspectives

Establishing Multi-User MIMO Communications Automatically Using Retrodirective Arrays

Communications in the mmWave and THz bands will be a key technological pillar for next-generation wireless networks. However, the increase in frequency results in an increase in path loss, which must be compensated for by using large antenna arrays. This introduces challenging issues due to power consumption, signalling overhead for channel estimation, hardware complexity, and slow beamforming and beam alignment schemes, which are in contrast with the requirements of next-generation wireless networks. In this paper, we propose the adoption of a retro-directive antenna array (RAA) at the user equipment (UE) side, where the signal sent by the base station (BS) is reflected towards the source after being conjugated and phase-modulated according to the UE data. By making use of modified Power Methods for the computation of the eigenvectors of the resulting round-trip channel, it is shown that, in single and multi-user multiple-input multiple-output (MIMO) scenarios, ultra-low complexity UEs can establish parallel communication links automatically with the BS in a very short time. This is done in a blind way, also by tracking fast channel variations while communicating, without the need for ADC chains at the UE as well as without explicit channel estimation and time-consuming beamforming and beam alignment schemes

Near-Field Tracking with Large Antenna Arrays: Fundamental Limits and Practical Algorithms

Applications towards 6G have brought a huge interest towards arrays with a high number of antennas and operating within the millimeter and sub-THz bandwidths for joint communication, sensing, and localization. With such large arrays, the plane wave approximation is often not accurate because the system may operate in the (radiating) near-field propagation region, namely the Fresnel region, where the electromagnetic field wavefront is spherical. In such a case, the curvature of arrival (CoA) is a measure of the spherical wavefront that can be used to infer the source position using only a single large antenna array. In this paper, we study a near-field tracking problem for inferring the position and the velocity of a moving source with an ad-hoc observation model that accounts for the phase-difference profile of a large receiving array. For this tracking problem, we derive the posterior Cramér-Rao Lower Bound (P-CRLB), and we provide insights on how the loss of positioning information outside the Fresnel region results from an increase of the ranging error rather than from inaccuracies of angular estimation. Then, we investigate the accuracy and complexity performance of different Bayesian tracking algorithms in the presence of model parameter mismatches and abrupt trajectory changes. Our results demonstrate the feasibility and high accuracy of most tracking approaches without the need for wideband signals and of any synchronization scheme

Performance Analysis of Dynamic Downlink PPP Cellular Networks over Generalized Fading Channels with MRC Diversity

This paper proposes novel and generalized expressions to characterize the performance of modern cellular networks under realistic user mobility behavior. The η-μ distribution is employed to derive the received power probability density function, the average bit error rate for different modulation schemes, and the coverage probability assuming a Poisson point process spatial distribution of base stations in downlink. The user is assumed to experience fading with Maximum Ratio Combining (MRC) and move according to a random way-point mobility model. To get more insights on the achivable diversity order, accurate asymptotic expressions for the coverage probability and average bit error rate are derived. The derived expressions are applicable to different widely-used fading environments, such as Rayleigh and Nakagami-m as particular cases, by an appropriate selection of the η-μ parameters. Monte Carlo simulation was used to show the validity of the proposed expressions. In addition, the generalized expressions allow the system designer to quantify the effects of user mobility on the cellular network performance, in different propagation environments, and network topologies as a function of the number of base stations and MRC branches

Human Being Detection from UWB NLOS Signals: Accuracy and Generality of Advanced Machine Learning Models

This paper studies the problem of detecting human beings in non-line-of-sight (NLOS) conditions using an ultra-wideband radar. We perform an extensive measurement campaign in realistic environments, considering different body orientations, the obstacles’ materials, and radar– obstacle distances. We examine two main scenarios according to the radar position: (i) placed on top of a mobile cart; (ii) handheld at different heights. We empirically analyze and compare several input representations and machine learning (ML) methods—supervised and unsupervised, symbolic and non-symbolic—according to both their accuracy in detecting NLOS human beings and their adaptability to unseen cases. Our study proves the effectiveness and flexibility of modern ML techniques, avoiding environment-specific configurations and benefiting from knowledge transference. Unlike traditional TLC approaches, ML allows for generalization, overcoming limits due to unknown or only partially known observation models and insufficient labeled data, which usually occur in emergencies or in the presence of time/cost constraints

Layered Video Transmission on Adaptive OFDM Wireless Systems

Future wireless video transmission systems will consider orthogonal frequency division multiplexing (OFDM) as the basic modulation technique due to its robustness and low complexity implementation in the presence of frequency-selective channels. Recently, adaptive bit loading techniques have been applied to OFDM showing good performance gains in cable transmission systems. In this paper a multilayer bit loading technique, based on the so called "ordered subcarrier selection algorithm," is proposed and applied to a Hiperlan2-like wireless system at 5 GHz for efficient layered multimedia transmission. Different schemes realizing unequal error protection both at coding and modulation levels are compared. The strong impact of this technique in terms of video quality is evaluated for MPEG-4 video transmission

Range estimation in multicarrier systems in the presence of interference: Performance limits and optimal signal design

Cataloged from PDF version of article.Theoretical limits on time-of-arrival (equivalently, range) estimation are derived for multicarrier systems in the presence of interference. Specifically, closed-form expressions are obtained for Cramer-Rao bounds (CRBs) in various scenarios. In addition, based on CRB expressions, an optimal power allocation (or, spectrum shaping) strategy is proposed. This strategy considers the constraints not only from the sensed interference level but also from the regulatory emission mask. Numerical results are presented to illustrate the improvements achievable with the optimal power allocation scheme, and a maximum likelihood time-of-arrival estimation algorithm is studied to assess the effects of the proposed approach in practical estimators. © 2011 IEEE

Crowd-based cognitive perception of the physical world: Towards the internet of senses

This paper introduces a possible architecture and discusses the research directions for the realization of the Cognitive Perceptual Internet (CPI), which is enabled by the convergence of wired and wireless communications, traditional sensor networks, mobile crowd-sensing, and machine learning techniques. The CPI concept stems from the fact that mobile devices, such as smartphones and wearables, are becoming an outstanding mean for zero-effort world-sensing and digitalization thanks to their pervasive diffusion and the increasing number of embedded sensors. Data collected by such devices provide unprecedented insights into the physical world that can be inferred through cognitive processes, thus originating a digital sixth sense. In this paper, we describe how the Internet can behave like a sensing brain, thus evolving into the Internet of Senses, with network-based cognitive perception and action capabilities built upon mobile crowd-sensing mechanisms. The new concept of hyper-map is envisioned as an efficient geo-referenced repository of knowledge about the physical world. Such knowledge is acquired and augmented through heterogeneous sensors, multi-user cooperation and distributed learning mechanisms. Furthermore, we indicate the possibility to accommodate proactive sensors, in addition to common reactive sensors such as cameras, antennas, thermometers and inertial measurement units, by exploiting massive antenna arrays at millimeter-waves to enhance mobile terminals perception capabilities as well as the range of new applications. Finally, we distillate some insights about the challenges arising in the realization of the CPI, corroborated by preliminary results, and we depict a futuristic scenario where the proposed Internet of Senses becomes true

5G mmwave positioning for vehicular networks

5G technologies present a new paradigm to provide connectivity to vehicles, in support of high data-rate services, complementing existing inter-vehicle communication standards based on IEEE 802.11p. As we argue, the specific signal characteristics of 5G communication turn out to be highly conducive for vehicle positioning. Hence, 5G can work in synergy with existing on-vehicle positioning and mapping systems to provide redundancy for certain applications, in particular automated driving. This article provides an overview of the evolution of cellular positioning and discusses the key properties of 5G as they relate to vehicular positioning. Open research challenges are presented

Near-Field Wireless Power Transfer with Dynamic Metasurface Antennas

Radio frequency wireless power transfer (WPT) enables charging low-power mobile devices without relying on wired infrastructure. Current existing WPT systems are typically designed assuming far-field propagation, where the radiated energy is steered in given angles, resulting in limited efficiency and possible radiation in undesired locations. When large arrays at high frequencies, such as dynamic metasurface antenna (DMA), are employed, WPT might take place in the radiating nearfield (Fresnel) region where spherical wave propagation holds, rather than plane wave propagation as in the far-field. In this paper, we study WPT systems charging multiple devices in the Fresnel region, where the energy transmitter is equipped with an emerging DMA, exploring how the antenna configuration can exploit the spherical wavefront to generate focused energy beams. In particular, after presenting a mathematical model for DMA-based radiating near-field WPT systems, we characterize the weighted sum-harvested energy maximization problem of the considered system, and we propose an efficient solution to jointly design the DMA weights and digital precoding vector. Simulation results show that our design generates focused energy beams that are capable of improving energy transfer efficiency in the radiating near-field with minimal energy pollution