A comparison of different modulation techniques performances in an underground multiuser communications scenario

The potential use of typical commercial communication systems with ultra high frequencies for the underground emergency/military situations will be investigated, as commercial systems have already a fully developed market that makes them cheap and reliable. The possible usage of broadband techniques like CDMA in the direct sequence will be studied because most commercial communication systems have already been designed to support multiple users, as the underground propagation has many possible applications. The performances of both modulation techniques are evaluated from the point of view of the quality of the signals, power spectral density and the effect that the propagation medium has on the transmitted signals such that the best modulation technique is determined. The 16QAM and QPSK modulations (two of the most popular modulation techniques in the terrestrial wireless system) are compared in a scenario where a number of underground sources share the same physical channel (and antenna) - the receiver is placed at the ground level so the generated signals must propagate through the dielectric layer in order to reach it. The transmitted power, electric and magnetic fields as well as occupied bandwidth are also calculated

State-of-the-art in Power Line Communications: from the Applications to the Medium

In recent decades, power line communication has attracted considerable attention from the research community and industry, as well as from regulatory and standardization bodies. In this article we provide an overview of both narrowband and broadband systems, covering potential applications, regulatory and standardization efforts and recent research advancements in channel characterization, physical layer performance, medium access and higher layer specifications and evaluations. We also identify areas of current and further study that will enable the continued success of power line communication technology.Comment: 19 pages, 12 figures. Accepted for publication, IEEE Journal on Selected Areas in Communications. Special Issue on Power Line Communications and its Integration with the Networking Ecosystem. 201

Mobile and Wireless Communications

Mobile and Wireless Communications have been one of the major revolutions of the late twentieth century. We are witnessing a very fast growth in these technologies where mobile and wireless communications have become so ubiquitous in our society and indispensable for our daily lives. The relentless demand for higher data rates with better quality of services to comply with state-of-the art applications has revolutionized the wireless communication field and led to the emergence of new technologies such as Bluetooth, WiFi, Wimax, Ultra wideband, OFDMA. Moreover, the market tendency confirms that this revolution is not ready to stop in the foreseen future. Mobile and wireless communications applications cover diverse areas including entertainment, industrialist, biomedical, medicine, safety and security, and others, which definitely are improving our daily life. Wireless communication network is a multidisciplinary field addressing different aspects raging from theoretical analysis, system architecture design, and hardware and software implementations. While different new applications are requiring higher data rates and better quality of service and prolonging the mobile battery life, new development and advanced research studies and systems and circuits designs are necessary to keep pace with the market requirements. This book covers the most advanced research and development topics in mobile and wireless communication networks. It is divided into two parts with a total of thirty-four stand-alone chapters covering various areas of wireless communications of special topics including: physical layer and network layer, access methods and scheduling, techniques and technologies, antenna and amplifier design, integrated circuit design, applications and systems. These chapters present advanced novel and cutting-edge results and development related to wireless communication offering the readers the opportunity to enrich their knowledge in specific topics as well as to explore the whole field of rapidly emerging mobile and wireless networks. We hope that this book will be useful for students, researchers and practitioners in their research studies

Policies for Carbon Energy Footprint Reduction of Overhead Multiple-Input Multiple-Output High Voltage Broadband over Power Lines Networks

The impact of different environmental policies on the broadband performance of overhead multiple-input multiple-output high-voltage/broadband over power lines (MIMO/HV/BPL) networks is investigated in this paper. The examined environmental policies focus on the carbon energy footprint reduction of overhead MIMO/HV/BPL networks while respecting their broadband character.The contribution of this paper is three-fold. First, the spectral and environmental performance of various configurations and topologies of overhead MIMO/HV/BPL networks is assessed with regard to respective spectral efficient (SE) and newly presented environmental efficient (EE) metrics. Second, further insights regarding the performance of overhead MIMO/HV/BPL networks highlight the better spectral and environmental performance of these networks against other today’s overhead HV/BPL networks, such as single-input single-output (SISO), single-input multiple-output (SIMO), or multiple-input single-output (MISO) ones. Third, the definition of appropriate environmental policies that optimize the coexistence of the three main sectors of concern, which are the Quality of Service (QoS) requirements, protection of existing radioservices and promotion of environmentally aware limits, is promoted. Towards that direction, the proposed SE/EE trade-off relation of this paper is expected to prove an extremely helpful SE/EE optimization technique.Citation: Lazaropoulos, A. G. (2015). Policies for Carbon Energy Footprint Reduction of Overhead Multiple-Input Multiple-Output High Voltage Broadband over Power Lines Networks. Trends in Renewable Energy, 1(2), 87-118. DOI: 10.17737/tre.2015.1.2.001

Machine learning for signal detection and estimation in wireless communications

Wireless communications systems have become an irreplaceable part of daily life. In recent years, machine-learning (ML) algorithms have been widely applied in various industries. Particularly, they are often employed in wireless communications because of the correlations in the time and space dimensions of wireless signals, channels, and energy. In this thesis, the performances of different conventional ML algorithms, deep-learning (DL) algorithms, and adversarial attack methods are evaluated in a wireless powered communications (WPC) system, wireless channel prediction, and signal detection in a multiuser orthogonal frequency-division multiplexing (OFDM) communications system. Numerical results are presented to show the performances of these algorithms. First, for efficient operation of an energy harvester in a WPC system, four different ML algorithms are used to model the radio frequency energy data. Linear regression (LR) is found to have the highest accuracy and the most stable performance for energy prediction. Next, five conventional ML algorithms are compared for channel prediction and further signal detection based on the prediction. The support vector machine (SVM) is found to have the best performance in terms of prediction accuracy and stability. For signal detection, SVM and LR give similar or even better performances to the existing scheme at high constellation size. Then, three DL algorithms are proposed for signal detection in an uncoded multiuser OFDM communications system. Additionally, the relationships between the bit error rate (BER) and different factors are investigated. The DL methods outperform linear minimum mean-squared error, and they are robust when the channel has a high variability. Finally, different attack algorithms are evaluated against a DL-based multiuser OFDM detector. The BERs under these attack methods show that the perturbation efficiency of adversarial attacks is higher than general multiuser interference. Virtual adversarial method and the zeroth-order-optimization attack are the most efficient among the white- and black-box methods, respectively

UWB Radio Wireless Communication System Design for Railway Tunnels

Railway is an economical and comfortable mode of transportation for long distances. Safety, reliability and good quality of service are the main concern of railway industries which are maintained by railway management and communication system. There are several existing management systems like CCCS, ATCS, PTC and many more. With increasing population, demand for railway services also increases. To full fill these demands railway infrastructure has been developing continuously. By implementing latest technologies for railway communication we can make railway transportation safer, efficient, and more accessible. Ultra wideband radio communication system is amongst those very latest and rapidly growing technologies. This research work focuses on the study of UWB radio based wireless communication system for railway tunnels, whose main task is to maintain an uninterrupted data transmission between train driver to wayside controller

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

Étude d'un réseau de capteur UWB pour la localisation et la communication dans un environnement minier

Le jour n'est peut-être pas très loin où une mine pourra compter sur un système de communication sans fil pour échanger des données, transmettre des informations ou localiser des travailleurs dans le cas d'une activité normale ou en cas d'urgence. Au point de vue de la sécurité, un système de communications sans fil aurait l'avantage de localiser en temps réel un travailleur ou un engin. Les travailleurs se déplacent sans cesse dans une mine. Avec une technologie sans fil permanente, on pourrait localiser les personnes de manière relativement précise. Même en cas d'éboulement, avec une technologie adaptée, il serait possible de savoir où se trouve la personne en détresse. Notre travail de recherche s'inscrit dans la perspective du développement d'un réseau de capteurs ultra large bande (UWB) pour deux applications : l'aide à la radiolocalisation et l'extension du réseau de capteurs sans fil dans la mine. Cette étude est focalisée sur trois aspects. La première partie de notre étude consiste à étudier tous les problèmes reliés à la radiolocalisation dans la mine. Vue l'importance de cette application, nous avons mis en oeuvre un réseau de capteurs en tenant compte d'un futur déploiement dans la mine. La technologie utilisée repose sur la technologie ultra large bande. Comme il n'existe pas de travaux qui traitent ce genre de problèmes, nous avons commencé notre étude par une caractérisation du canal UWB dans les mines souterraines. Pour atteindre ces objectifs, plusieurs campagnes de mesure sur site (mine expérimentale) ont été menées. Nous sommes parvenus à une modélisation du canal de propagation et à avancer des recommandations pour aider au dimensionnement d'un réseau de capteurs dans ce type d'environnement. Dans la première partie, le but est d'étudier le problème de radiolocalisation avec les réseaux de capteurs. Notre scénario proposé serait de placer des capteurs sur chaque agent (mineur, engin). On suppose que chaque noeud (agent) qui circule à travers un réseau d'ancre maillé (déjà déployé), va extraire des informations de distance (en utilisant le critère de temps d'arrivée), ensuite il va utiliser un algorithme de positionnement distribué afin de déterminer sa propre position. Lors de cette partie nous avons aussi étudié quelques estimateurs cohérents et non-cohérents du temps d'arrivée. La caractérisation de l'erreur de mesure utilisant le temps d'arrivée dans un environnement minier a été aussi évaluée. Enfin, dans la dernière partie, nous avons analysé par simulations un déploiement d'un réseau de capteurs UWB ad hoc dans la mine. Nous avons choisi d'adopter une approche théorique afin d'évaluer les performances de cette configuration. Une conception intercouche pour un routage optimal a été étudiée. Nous avons utilisé la couche physique/réseau afin de minimiser l'énergie consommée lors de l'acheminement du données

Information Technology, Artificial Intelligence and Machine Learning in Smart Grid – Performance Comparison between Topology Identification Methodology and Neural Network Identification Methodology for the Branch Number Approximation of Overhead Low-Voltage Broadband over Power Lines Network Topologies

Broadband over Power Lines (BPL) networks that are deployed across the smart grid can benefit from the usage of machine learning, as smarter grid diagnostics are collected and analyzed. In this paper, the neural network identification methodology of Overhead Low-Voltage (OV LV) BPL networks that aims at identifying the number of branches for a given OV LV BPL topology channel attenuation behavior is proposed, which is simply denoted as NNIM-BNI. In order to identify the branch number of an OV LV BPL topology through its channel attenuation behavior, NNIM-BNI exploits the Deterministic Hybrid Model (DHM), which has been extensively tested in OV LV BPL networks for their channel attenuation determination, and the OV LV BPL topology database of Topology Identification Methodology (TIM). The results of NNIM-BNI towards the branch number identification of OV LV BPL topologies are compared against the ones of a newly proposed TIM-based methodology, denoted as TIM-BNI.Citation: Lazaropoulos, A. G. (2021). Information Technology, Artificial Intelligence and Machine Learning in Smart Grid-Performance Comparison between Topology Identification Methodology and Neural Network Identification Methodology for the Branch Number Approximation of Overhead Low-Voltage Broadband over Power Lines Network Topologies. Trends in Renewable Energy, 7, 87-113. DOI: 10.17737/tre.2021.7.1.0013