Contribution à la conception d'un système de radio impulsionnelle ultra large bande intelligent

Faced with an ever increasing demand of high data-rates and improved adaptability among existing systems, which inturn is resulting in spectrum scarcity, the development of new radio solutions becomes mandatory in order to answer the requirements of these emergent applications. Among the recent innovations in the field of wireless communications,ultra wideband (UWB) has generated significant interest. Impulse based UWB (IR-UWB) is one attractive way of realizing UWB systems, which is characterized by the transmission of sub nanoseconds UWB pulses, occupying a band width up to 7.5 GHz with extremely low power density. This large band width results in several captivating features such as low-complexity low-cost transceiver, ability to overlay existing narrowband systems, ample multipath diversity, and precise ranging at centimeter level due to extremely fine temporal resolution.In this PhD dissertation, we investigate some of the key elements in the realization of an intelligent time-hopping based IR-UWB system. Due to striking resemblance of IR-UWB inherent features with cognitive radio (CR) requirements, acognitive UWB based system is first studied. A CR in its simplest form can be described as a radio, which is aware ofits surroundings and adapts intelligently. As sensing the environment for the availability of resources and then consequently adapting radio’s internal parameters to exploit them opportunistically constitute the major blocks of any CR, we first focus on robust spectrum sensing algorithms and the design of adaptive UWB waveforms for realizing a cognitive UWB radio. The spectrum sensing module needs to function with minimum a-priori knowledge available about the operating characteristics and detect the primary users as quickly as possible. Keeping this in mind, we develop several spectrum sensing algorithms invoking recent results on the random matrix theory, which can provide efficient performance with a few number of samples. Next, we design the UWB waveform using a linear combination of Bsp lines with weight coefficients being optimized by genetic algorithms. This results in a UWB waveform that is spectrally efficient and at the same time adaptable to incorporate the cognitive radio requirements. In the 2nd part of this thesis, some research challenges related to signal processing in UWB systems, namely synchronization and dense multipath channel estimation are addressed. Several low-complexity non-data-aided (NDA) synchronization algorithms are proposed for BPSK and PSM modulations, exploiting either the orthogonality of UWB waveforms or theinherent cyclostationarity of IR-UWB signaling. Finally, we look into the channel estimation problem in UWB, whichis very demanding due to particular nature of UWB channels and at the same time very critical for the coherent Rake receivers. A method based on a joint maximum-likelihood (ML) and orthogonal subspace (OS) approaches is proposed which exhibits improved performance than both of these methods individually.Face à une demande sans cesse croissante de haut débit et d’adaptabilité des systèmes existants, qui à son tour se traduit par l’encombrement du spectre, le développement de nouvelles solutions dans le domaine des communications sans fil devient nécessaire afin de répondre aux exigences des applications émergentes. Parmi les innovations récentes dans ce domaine, l’ultra large bande (UWB) a suscité un vif intérêt. La radio impulsionnelle UWB (IR-UWB), qui est une solution intéressante pour réaliser des systèmes UWB, est caractérisée par la transmission des impulsions de très courte durée, occupant une largeur de bande allant jusqu’à 7,5 GHz, avec une densité spectrale de puissance extrêmement faible. Cette largeur de bande importante permet de réaliser plusieurs fonctionnalités intéressantes, telles que l’implémentation à faible complexité et à coût réduit, la possibilité de se superposer aux systèmes à bande étroite, la diversité spatiale et la localisation très précise de l’ordre centimétrique, en raison de la résolution temporelle très fine.Dans cette thèse, nous examinons certains éléments clés dans la réalisation d'un système IR-UWB intelligent. Nous avons tout d’abord proposé le concept de radio UWB cognitive à partir des similarités existantes entre l'IR-UWB et la radio cognitive. Dans sa définition la plus simple, un tel système est conscient de son environnement et s'y adapte intelligemment. Ainsi, nous avons tout d’abord focalisé notre recherché sur l’analyse de la disponibilité des ressources spectrales (spectrum sensing) et la conception d’une forme d’onde UWB adaptative, considérées comme deux étapes importantes dans la réalisation d'une radio cognitive UWB. Les algorithmes de spectrum sensing devraient fonctionner avec un minimum de connaissances a priori et détecter rapidement les utilisateurs primaires. Nous avons donc développé de tels algorithmes utilisant des résultats récents sur la théorie des matrices aléatoires, qui sont capables de fournir de bonnes performances, avec un petit nombre d'échantillons. Ensuite, nous avons proposé une méthode de conception de la forme d'onde UWB, vue comme une superposition de fonctions B-splines, dont les coefficients de pondération sont optimisés par des algorithmes génétiques. Il en résulte une forme d'onde UWB qui est spectralement efficace et peut s’adapter pour intégrer les contraintes liées à la radio cognitive. Dans la 2ème partie de cette thèse, nous nous sommes attaqués à deux autres problématiques importantes pour le fonctionnement des systèmes UWB, à savoir la synchronisation et l’estimation du canal UWB, qui est très dense en trajets multiples. Ainsi, nous avons proposé plusieurs algorithmes de synchronisation, de faible complexité et sans séquence d’apprentissage, pour les modulations BPSK et PSM, en exploitant l'orthogonalité des formes d'onde UWB ou la cyclostationnarité inhérente à la signalisation IR-UWB. Enfin, nous avons travaillé sur l'estimation du canal UWB, qui est un élément critique pour les récepteurs Rake cohérents. Ainsi, nous avons proposé une méthode d’estimation du canal basée sur une combinaison de deux approches complémentaires, le maximum de vraisemblance et la décomposition en sous-espaces orthogonaux,d’améliorer globalement les performances

High-Performance Modelling and Simulation for Big Data Applications

This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications

High-Performance Modelling and Simulation for Big Data Applications

This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications

The Wireless Craze, The Unlimited Bandwidth Myth, The Spectrum Auction Faux Pas, and the Punchline to Ronald Coase's 'Big Joke': An Essay on Airwave Allocation Policy

In 1959 the Federal Communications Commission invited economist Ronald Coase to testify about his proposal for market allocation of radio spectrum rights. The FCC's first question: 'Is this all a big joke'' Today, however, leading policy makers, including the current FCC Chair, decry the 'spectrum drought' produced by administrative allocation and call for the creation of private bandwidth markets. This essay examines marketplace trends driving regulators' change of humor, and considers the path of spectrum policy liberalization in light of emerging technologies, theories of unlimited bandwidth, reforms such as FCC license auctions, and recent progress in deregulating wireless markets in the U.S. and around the globe.

Applications

Volume 3 describes how resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples: in health and medicine for risk modelling, diagnosis, and treatment selection for diseases in electronics, steel production and milling for quality control during manufacturing processes in traffic, logistics for smart cities and for mobile communications

Radio Communications

In the last decades the restless evolution of information and communication technologies (ICT) brought to a deep transformation of our habits. The growth of the Internet and the advances in hardware and software implementations modified our way to communicate and to share information. In this book, an overview of the major issues faced today by researchers in the field of radio communications is given through 35 high quality chapters written by specialists working in universities and research centers all over the world. Various aspects will be deeply discussed: channel modeling, beamforming, multiple antennas, cooperative networks, opportunistic scheduling, advanced admission control, handover management, systems performance assessment, routing issues in mobility conditions, localization, web security. Advanced techniques for the radio resource management will be discussed both in single and multiple radio technologies; either in infrastructure, mesh or ad hoc networks

Applications

Volume 3 describes how resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples: in health and medicine for risk modelling, diagnosis, and treatment selection for diseases in electronics, steel production and milling for quality control during manufacturing processes in traffic, logistics for smart cities and for mobile communications

Technology and Management Applied in Construction Engineering Projects

This book focuses on fundamental and applied research on construction project management. It presents research papers and practice-oriented papers. The execution of construction projects is specific and particularly difficult because each implementation is a unique, complex, and dynamic process that consists of several or more subprocesses that are related to each other, in which various aspects of the investment process participate. Therefore, there is still a vital need to study, research, and conclude the engineering technology and management applied in construction projects. This book present unanimous research approach is a result of many years of studies, conducted by 35 well experienced authors. The common subject of research concerns the development of methods and tools for modeling multi-criteria processes in construction engineering

An analysis of regulatory frameworks for wireless communications, societal concerns and risk: the case of radio frequency (RF) allocation and licensing.

This thesis analyses how and why culture and geography influence the allocation and licensing of the radio frequency (RF) spectrum in different nations. Based on a broad study of 235 countries, an inter-disciplinary approach is used to explore regulatory frameworks and attitudes toward risk. In addition, detailed case studies of the UK, France, the US and Ecuador provide deeper insights into the main contrasting regulatory styles. Three alternative sociological theories are used to analyse and explain the results for both the in-depth and broad brush studies. The Cultural Theory of Mary Douglas and co-workers is first used to categorise countries in terms of perceptual filters. The empirical findings indicate some countries to be apparently exceptional in their behaviour. The theory of Bounded Rationality is used to investigate and explain these apparent irrationalities. Finally, Rational Field Theory shows how beliefs and values guide administrations in their RF regulation. A number of key factors are found to dominate and patterns emerge. The European RF harmonisation is unique. Following European unification, wireless regulation is divided into two major camps (the EU and the US), which differ in their risk concerns, approach to top-down mandated standards, allocation of RF spectrum to licence-exempt bands and type approval process. The adoption of cellular and TV standards around the world reflects geopolitical and colonial influence. The language of a country is a significant indicator of its analogue TV standard. Interestingly, the longitude of a country to a fair extent defines RF allocation: Africa and West Asia follow Europe, whereas the Americas approximate the US. RF regulation and risk tolerability differ between tropical and non-tropical climates. The collectivised/centralised versus the individualised/market-based rationalities result in different regulatory frameworks and contrasting societal and risk concerns. The success of the top-down European GSM and the bottom-up Wi-Fi standards reveal how the central- planning and market-based approaches have thrived. Attitudes to RF human hazards and spurious emissions levels reveal that the US, Canada and Japan are more tolerant of these risks than Europe. Australia, Canada, New Zealand, UK and USA encourage technological innovation. A practical benefit of this study is that it will give regulators more freedom to choose a rational RF licensing protocol, by better understanding the possibly self-imposed boundaries of cultural and geographical factors which are currently shaping allocation. Academically, there is utility in undertaking a cultural and geographic analysis of a topic that is mostly the domain of engineering, economic and legal analysts

IoT Applications Computing

The evolution of emerging and innovative technologies based on Industry 4.0 concepts are transforming society and industry into a fully digitized and networked globe. Sensing, communications, and computing embedded with ambient intelligence are at the heart of the Internet of Things (IoT), the Industrial Internet of Things (IIoT), and Industry 4.0 technologies with expanding applications in manufacturing, transportation, health, building automation, agriculture, and the environment. It is expected that the emerging technology clusters of ambient intelligence computing will not only transform modern industry but also advance societal health and wellness, as well as and make the environment more sustainable. This book uses an interdisciplinary approach to explain the complex issue of scientific and technological innovations largely based on intelligent computing