Fifty Years of Noise Modeling and Mitigation in Power-Line Communications.

Building on the ubiquity of electric power infrastructure, power line communications (PLC) has been successfully used in diverse application scenarios, including the smart grid and in-home broadband communications systems as well as industrial and home automation. However, the power line channel exhibits deleterious properties, one of which is its hostile noise environment. This article aims for providing a review of noise modeling and mitigation techniques in PLC. Specifically, a comprehensive review of representative noise models developed over the past fifty years is presented, including both the empirical models based on measurement campaigns and simplified mathematical models. Following this, we provide an extensive survey of the suite of noise mitigation schemes, categorizing them into mitigation at the transmitter as well as parametric and non-parametric techniques employed at the receiver. Furthermore, since the accuracy of channel estimation in PLC is affected by noise, we review the literature of joint noise mitigation and channel estimation solutions. Finally, a number of directions are outlined for future research on both noise modeling and mitigation in PLC

Effects of errorless learning on the acquisition of velopharyngeal movement control

Session 1pSC - Speech Communication: Cross-Linguistic Studies of Speech Sound Learning of the Languages of Hong Kong (Poster Session)The implicit motor learning literature suggests a benefit for learning if errors are minimized during practice. This study investigated whether the same principle holds for learning velopharyngeal movement control. Normal speaking participants learned to produce hypernasal speech in either an errorless learning condition (in which the possibility for errors was limited) or an errorful learning condition (in which the possibility for errors was not limited). Nasality level of the participants’ speech was measured by nasometer and reflected by nasalance scores (in %). Errorless learners practiced producing hypernasal speech with a threshold nasalance score of 10% at the beginning, which gradually increased to a threshold of 50% at the end. The same set of threshold targets were presented to errorful learners but in a reversed order. Errors were defined by the proportion of speech with a nasalance score below the threshold. The results showed that, relative to errorful learners, errorless learners displayed fewer errors (50.7% vs. 17.7%) and a higher mean nasalance score (31.3% vs. 46.7%) during the acquisition phase. Furthermore, errorless learners outperformed errorful learners in both retention and novel transfer tests. Acknowledgment: Supported by The University of Hong Kong Strategic Research Theme for Sciences of Learning © 2012 Acoustical Society of Americapublished_or_final_versio

A Unified Multi-Functional Dynamic Spectrum Access Framework: Tutorial, Theory and Multi-GHz Wideband Testbed

Dynamic spectrum access is a must-have ingredient for future sensors that are ideally cognitive. The goal of this paper is a tutorial treatment of wideband cognitive radio and radar—a convergence of (1) algorithms survey, (2) hardware platforms survey, (3) challenges for multi-function (radar/communications) multi-GHz front end, (4) compressed sensing for multi-GHz waveforms—revolutionary A/D, (5) machine learning for cognitive radio/radar, (6) quickest detection, and (7) overlay/underlay cognitive radio waveforms. One focus of this paper is to address the multi-GHz front end, which is the challenge for the next-generation cognitive sensors. The unifying theme of this paper is to spell out the convergence for cognitive radio, radar, and anti-jamming. Moore’s law drives the system functions into digital parts. From a system viewpoint, this paper gives the first comprehensive treatment for the functions and the challenges of this multi-function (wideband) system. This paper brings together the inter-disciplinary knowledge

Review of Cetacean's click detection algorithms

The detection of echolocation clicks is key in understanding the intricate behaviors of cetaceans and monitoring their populations. Cetacean species relying on clicks for navigation, foraging and even communications are sperm whales (Physeter macrocephalus) and a variety of dolphin groups. Echolocation clicks are wideband signals of short duration that are often emitted in sequences of varying inter-click-intervals. While datasets and models for clicks exist, the detection and classification of clicks present a significant challenge, mostly due to the diversity of clicks' structures, overlapping signals from simultaneously emitting animals, and the abundance of noise transients from, for example, snapping shrimps and shipping cavitation noise. This paper provides a survey of the many detection and classification methodologies of clicks, ranging from 2002 to 2023. We divide the surveyed techniques into categories by their methodology. Specifically, feature analysis (e.g., phase, ICI and duration), frequency content, energy based detection, supervised and unsupervised machine learning, template matching and adaptive detection approaches. Also surveyed are open access platforms for click detections, and databases openly available for testing. Details of the method applied for each paper are given along with advantages and limitations, and for each category we analyze the remaining challenges. The paper also includes a performance comparison for several schemes over a shared database. Finally, we provide tables summarizing the existing detection schemes in terms of challenges address, methods, detection and classification tools applied, features used and applications.Comment: 23 pages, 6 tables, 4 figure

Graphical model driven methods in adaptive system identification

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution September 2016Identifying and tracking an unknown linear system from observations of its inputs and outputs is a problem at the heart of many different applications. Due to the complexity and rapid variability of modern systems, there is extensive interest in solving the problem with as little data and computation as possible. This thesis introduces the novel approach of reducing problem dimension by exploiting statistical structure on the input. By modeling the input to the system of interest as a graph-structured random process, it is shown that a large parameter identification problem can be reduced into several smaller pieces, making the overall problem considerably simpler. Algorithms that can leverage this property in order to either improve the performance or reduce the computational complexity of the estimation problem are developed. The first of these, termed the graphical expectation-maximization least squares (GEM-LS) algorithm, can utilize the reduced dimensional problems induced by the structure to improve the accuracy of the system identification problem in the low sample regime over conventional methods for linear learning with limited data, including regularized least squares methods. Next, a relaxation of the GEM-LS algorithm termed the relaxed approximate graph structured least squares (RAGS-LS) algorithm is obtained that exploits structure to perform highly efficient estimation. The RAGS-LS algorithm is then recast into a recursive framework termed the relaxed approximate graph structured recursive least squares (RAGSRLS) algorithm, which can be used to track time-varying linear systems with low complexity while achieving tracking performance comparable to much more computationally intensive methods. The performance of the algorithms developed in the thesis in applications such as channel identification, echo cancellation and adaptive equalization demonstrate that the gains admitted by the graph framework are realizable in practice. The methods have wide applicability, and in particular show promise as the estimation and adaptation algorithms for a new breed of fast, accurate underwater acoustic modems. The contributions of the thesis illustrate the power of graphical model structure in simplifying difficult learning problems, even when the target system is not directly structured.The work in this thesis was supported primarily by the Office of Naval Research through an ONR Special Research Award in Ocean Acoustics; and at various times by the National Science Foundation, the WHOI Academic Programs Office and the MIT Presidential Fellowship Program

Algorithms for propagation-aware underwater ranging and localization

Mención Internacional en el título de doctorWhile oceans occupy most of our planet, their exploration and conservation are one of the crucial research problems of modern time. Underwater localization stands among the key issues on the way to the proper inspection and monitoring of this significant part of our world. In this thesis, we investigate and tackle different challenges related to underwater ranging and localization. In particular, we focus on algorithms that consider underwater acoustic channel properties. This group of algorithms utilizes additional information about the environment and its impact on acoustic signal propagation, in order to improve the accuracy of location estimates, or to achieve a reduced complexity, or a reduced amount of resources (e.g., anchor nodes) compared to traditional algorithms. First, we tackle the problem of passive range estimation using the differences in the times of arrival of multipath replicas of a transmitted acoustic signal. This is a costand energy- effective algorithm that can be used for the localization of autonomous underwater vehicles (AUVs), and utilizes information about signal propagation. We study the accuracy of this method in the simplified case of constant sound speed profile (SSP) and compare it to a more realistic case with various non-constant SSP. We also propose an auxiliary quantity called effective sound speed. This quantity, when modeling acoustic propagation via ray models, takes into account the difference between rectilinear and non-rectilinear sound ray paths. According to our evaluation, this offers improved range estimation results with respect to standard algorithms that consider the actual value of the speed of sound. We then propose an algorithm suitable for the non-invasive tracking of AUVs or vocalizing marine animals, using only a single receiver. This algorithm evaluates the underwater acoustic channel impulse response differences induced by a diverse sea bottom profile, and proposes a computationally- and energy-efficient solution for passive localization. Finally, we propose another algorithm to solve the issue of 3D acoustic localization and tracking of marine fauna. To reach the expected degree of accuracy, more sensors are often required than are available in typical commercial off-the-shelf (COTS) phased arrays found, e.g., in ultra short baseline (USBL) systems. Direct combination of multiple COTS arrays may be constrained by array body elements, and lead to breaking the optimal array element spacing, or the desired array layout. Thus, the application of state-of-the-art direction of arrival (DoA) estimation algorithms may not be possible. We propose a solution for passive 3D localization and tracking using a wideband acoustic array of arbitrary shape, and validate the algorithm in multiple experiments, involving both active and passive targets.Part of the research in this thesis has been supported by the EU H2020 program under project SYMBIOSIS (G.A. no. 773753).This work has been supported by IMDEA Networks InstitutePrograma de Doctorado en Ingeniería Telemática por la Universidad Carlos III de MadridPresidente: Paul Daniel Mitchell.- Secretario: Antonio Fernández Anta.- Vocal: Santiago Zazo Bell

MIMO underwater acoustic communications over time-varying channels: from theory to practice

Despite more than 70% of our planet surface is covered by water, today the underwater world can still be considered largely unknown. Rivers, lakes, seas and oceans have always been a fundamental resource for human life development, but at the same time they have often represented natural obstacles very hard to surmount. The most impressive example is probably given by the ocean, whose vastness severely limited geographical explorations and discoveries for tens of centuries. Anyway, the growing curiosity about what happens below the water surface has gradually led man to immerse in this unknown environment, trying to overcome its inaccessibility and figure out its secrets. Underwater investigation and exploring have been increasingly supported by technology, advanced over time for different purposes (military, commercial, scientific). In this regard, providing a communication link between remote users has been recognized as one of the main issues to be addressed. The first significant solutions derived from the radio-frequency world, subject of study since the 19th century. Unfortunately both wired and wireless RF inspired signal propagation strategies were not evaluated as successful. The former ones, since considering the deployment of meters (up to kilometers) of cable in depth, were too costly and difficult, while the latter ones did not offer good performance in terms of communication range due to signal attenuation. An alternative way, examined with particular interest from the beginning of the 20th century, has been that one offered by acoustics. Actually, the study of sound and its propagation through different media has been an intriguing topic since the Old World Age, hence the attempt of messaging underwater has seemed to be a great opportunity to convey theoretical principles in a real application. In addition, not only humans but also marine animals use acoustic waves to communicate, even over several kilometers distances as demonstrated by whales. So, since already existing in nature, acoustic communications have been considered as potentially successful, furthermore representing an effective trade-off between feasibility and performance, especially if compared to the other electromagnetic signals-based methods. Communication over RF channels has been extensively investigated so as to become a mature technology. The thorough knowledge about OSI (Open Systems Interconnection) model physical layer issues has allowed the researchers attention to be drawn to the upper layers. Following this direction, the recent advances in technology in this field have been accomplished mainly due to novelties in networks managing rather than to enhancements in the signal propagation study. Moving to acoustics, unfortunately this approach results to be failing if applied in the underwater scenario, as the major challenges rise indeed from physics matters. The underwater environment is varied and variable, so understanding the mechanisms that govern the propagation of sound in water is a key element for the design of a well-performing communication system. In this sense, the physical layer has therefore regained the centrality that has been diminished in other contexts. The underwater acoustic communications can be adopted in a wide range of applications. The best-known are coastal monitoring, target detection, AUVs (Autonomous Underwater Vehicles) remote control, tsunami alarm, environmental data collection and transmission. Those ones are very specific activities, so the devices to be employed must sometimes meet very strict requirements. In this regard, the solutions commercially available provide good performance (that are paid in terms of high costs). On the other hand, the fact that hardware and software are usually copyrighted leads to have a closed system. Having reconfigurable devices is instead an opportunity to match the technology with the environment features and variations, especially in real-time applications. Recently, the need to overcome these constraints has encouraged the debate about underwater technology challenges. The work by Demirors et al. [1] reports an interesting discussion about the implementation of software-defined underwater acoustic networks (UWANs), highlighting how this solution can provide enhancements in terms of software portability, computational capacity, energy efficiency and real-time reconfigurability. Furthermore, the authors propose the architecture of a software-defined acoustic modem and evaluate its performance and capabilities with tank and lake experiments. Considering the comments outlined above, the following dissertation deals with the design of an acoustic communication system. The preliminary theoretical analysis regarding physical layer concerns, such as signal propagation and channel behavior, represents the starting point from which several proposals regarding the implementation of UWANs are introduced. In particular the context of Multiple-Input Multiple-Output (MIMO) communications is investigated, presenting several solutions about transmission schemes and receiver implementation. Furthermore, concerning UWANs management, some strategies for access and error control, established at the data link layer level, are detailed. It is worth highlighting that the goal of this contribution is not to present a disjointed discussion about the topics just listed. The objective is instead to propose practical solutions developed hand in hand with theory, making choices firstly by looking at what nature allows

Journal of Telecommunications and Information Technology, 2018, nr 1

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