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

All-cause and cause-specific mortality in individuals with zero and minimal coronary artery calcium: A long-term, competing risk analysis in the Coronary Artery Calcium Consortium.

Background and aimsThe long-term associations between zero, minimal coronary artery calcium (CAC) and cause-specific mortality are currently unknown, particularly after accounting for competing risks with other causes of death.MethodsWe evaluated 66,363 individuals from the CAC Consortium (mean age 54 years, 33% women), a multi-center, retrospective cohort study of asymptomatic individuals undergoing CAC scoring for clinical risk assessment. Baseline evaluations occurred between 1991 and 2010.ResultsOver a mean of 12 years of follow-up, individuals with CAC = 0 (45% prevalence, mean age 45 years) had stable low rates of coronary heart disease (CHD) death, cardiovascular disease (CVD) death (ranging 0.32 to 0.43 per 1000 person-years), and all-cause death (1.38-1.62 per 1000 person-years). Cancer was the predominant cause of death in this group, yet rates were also very low (0.47-0.79 per 1000 person-years). Compared to CAC = 0, individuals with CAC 1-10 had an increased multivariable-adjusted risk of CVD death only under age 40. Individuals with CAC>10 had multivariable-adjusted increased risks of CHD death, CVD death and all-cause death at all ages, and a higher proportion of CVD deaths.ConclusionsCAC = 0 is a frequent finding among individuals undergoing CAC scanning for risk assessment and is associated with low rates of all-cause death at 12 years of follow-up. Our results support the emerging consensus that CAC = 0 represents a unique population with favorable all-cause prognosis who may be considered for more flexible treatment goals in primary prevention. Detection of any CAC in young adults could be used to trigger aggressive preventive interventions

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

Reinforcement Learning for Joint Detection & Mapping using Dynamic UAV Networks

Dynamic radar networks, usually composed of flying UAVs, have recently attracted great interest for time-critical applications, such as search-and-rescue operations, involving reliable detection of multiple targets and situational awareness through environment radio mapping. Unfortunately, the time available for detection is often limited, and in most settings, there are no reliable models of the environment, which should be learned quickly. One possibility to guarantee short learning time is to enhance cooperation among UAVs. For example, they can share information for properly navigating the environment if they have a common goal. Alternatively, in case of multiple and different goals or tasks, they can exchange their available information to fitly assign tasks (e.g., targets) to each network agent. In this paper, we consider ad-hoc approaches for task assignment and a multi-agent RL algorithm that allow the UAVs to learn a suitable navigation policy to explore an unknown environment while maximizing the accuracy in detecting targets. The obtained results demonstrate that cooperation at different levels accelerates the learning process and brings benefits in accomplishing the team's goals

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

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

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