Les années récentes ont vu l’explosion du trafic sur les réseaux mobiles depuis l’apparition de nouveaux terminaux (smartphones, tablettes) et des usages qu’ils permettent, en particulier les données multimédia, le trafic voix restant sensiblement constant. Une conséquence est le besoin de plus de spectre, ou la nécessité de mieux utiliser le spectre déjà alloué. Comme il n’y a pas de coordination entre les utilisateurs secondaire(s) et primaire, avant toute transmission les premiers doivent mettre en œuvre des traitements pour détecter les périodes dans lesquelles l’utilisateur primaire transmet, ce qui est le scénario considéré dans cette thèse. Nous considérons donc une autre approche, reposant sur l’utilisation de codes correcteurs d’effacements en mode paquet. La dernière partie de la thèse aborde un scénario dans lequel il n’y a plus d’utilisateur primaire, tous les utilisateurs ayant le même droit à transmettre dans le canal. Nous décrivons une modification de la couche MAC du 802.11 consistant à réduire les différents temps consacrés à attendre (SIFS, DIFS, backoff, . . .) afin d’accéder plus souvent au canal, au prix de quelques collisions supplémentaires qu’il est possible de récupérer en mettant en œuvre des codes correcteurs d’effacements. / The emergence of new devices especially the smartphones and tablets having a lot of new applications have rocketed the wireless traffic in recent years and this is the cause of main surge in the demand of radio spectrum. There is a need of either more spectrum or to use existing spectrum more efficiently due to dramatic increase in the demand of limited spectrum. Among the new dynamic access schemes designed to use the spectrum more efficiently opportunistic spectrum access (OSA) is currently addressed when one or more secondary users (SU) are allowed to access the channel when the PU is not transmitting. The erasure correcting codes are therefore envisioned to recover the lost data due to sensing impairments. We define the parameter efficiency of SU and optimize it in-terms of spectrum utilization keeping into account sensing impairments, code parameters and the activity of PU. Finally, the spectrum access for multiple secondary users is addressed when there is no primary and each user has equal right to access the channel. The interesting scenarios are Cognitive radio networks and WiFi where 802.11 protocol gives the specification for MAC layer. The throughput curvesachieved by retransmission and using various erasure correcting codes are compared. This modification in MAC layer will reduce the long waiting time to access the channel, as the number of users are increased.

Les systèmes de communications sans fil ne cessent de se multiplier pour devenir incontournables de nos jours. Cette croissance cause une augmentation de la demande des ressources spectrales, qui sont devenues de plus en plus rares. Afin de résoudre ce problème de pénurie de fréquences, Joseph Mitola III, en 2000, a introduit l'idée de l'allocation dynamique du spectre. Il définit ainsi le terme « Cognitive Radio » (Radio Intelligente), qui est largement pressenti pour être le prochain Big Bang dans les futures communications sans fil [1]. Dans le cadre de ce travail on s'intéresse à la problématique du spectrum sensing qui est la détection de présence des Utilisateurs Primaires dans un spectre sous licence, dans le contexte de la radio intelligente. L'objectif de ce travail est de proposer des méthodes de détection efficaces à faible complexité et/ou à faible temps d'observation et ceci en utilisant le minimum d'information a priori sur le signal à détecter. Dans la première partie on traite le problème de détection d'un signal aléatoire dans le bruit. Deux grandes méthodes de détection sont utilisées : la détection d'énergie ou radiomètre et la détection cyclostationnaire. Dans notre contexte, ces méthodes sont plus complémentaires que concurrentes. Nous proposons une architecture hybride de détection des bandes libres, qui combine la simplicité du radiomètre et la robustesse des détecteurs cyclostationnaires. Deux méthodes de détection sont proposées qui se basent sur cette même architecture. Grâce au caractère adaptatif de l'architecture, la détection évolue au cours du temps pour tendre vers la complexité du détecteur d'énergie avec des performances proches du détecteur cyclostationnaire ou du radiomètre selon la méthode utilisée et l'environnement de travail. Dans un second temps on exploite la propriété parcimonieuse de la Fonction d'Autocorrelation Cyclique (FAC) pour proposer un nouvel estimateur aveugle qui se base sur le compressed sensing afin d'estimer le Vecteur d'Autocorrelation Cyclique (VAC), qui est un vecteur particulier de la Fonction d'Autocorrelation Cyclique pour un délai fixe. On montre par simulation que ce nouvel estimateur donne de meilleures performances que celles obtenues avec l'estimateur classique, qui est non aveugle et ceci dans les mêmes conditions et en utilisant le même nombre d'échantillons. On utilise l'estimateur proposé, pour proposer deux détecteurs aveugles utilisant moins d'échantillons que nécessite le détecteur temporel de second ordre de [2] qui se base sur l'estimateur classique de la FAC. Le premier détecteur exploite uniquement la propriété de parcimonie du VAC tandis que le second détecteur exploite en plus de la parcimonie la propriété de symétrie du VAC, lui permettant ainsi d'obtenir de meilleures performances. Ces deux détecteurs outre qu'ils sont aveugles sont plus performants que le détecteur non aveugle de [2] dans le cas d'un faible nombre d'échantillons. / The wireless communications systems continue to grow and has become very essential nowadays. This growth causes an increase in the demand of spectrum resources, which have become more and more scarce. To solve this problem of spectrum scarcity, Joseph Mitola III, in the year 2000, introduced the idea of dynamic spectrum allocation. Mitola defines the term “Cognitive Radio”, which is widely expected to be the next Big Bang in wireless communications [1]. In this work we focus on the problem of spectrum sensing which is the detection of the presence of primary users in licensed spectrum, in the context of cognitive radio. The objective of this work is to propose effective detection methods at low-complexity and/or using short observation time, using minimal a priori information about the signal to be detected. In the first part of this work we deal with the problem of detecting a random signal in noise. Two main methods of detection are used: energy detection or radiometer and cyclostationary detection. In our context, these methods are more complementary than competitive. We propose a hybrid architecture for detecting free bands, which combines the simplicity of the radiometer and the robustness of the cyclostationary detection. Two detection methods are proposed that are based on this same hybrid architecture. Thanks to the adaptive nature of the architecture, the complexity of the detector decreases over time to tend to the one of an energy detector with close performance to the cyclostationary detector or to the performance of a radiometer, depending on the used method and on the working environment. In the second part of this work we exploit the sparse property of the Cyclic Autocorrelation Function (CAF) to propose a new blind estimator based on compressed sensing that estimates the Cyclic Autocorrelation Vector (CAV) which is a particular vector of the CAF for a given lag. It is shown by simulation that this new estimator gives better performances than those obtained with the classical estimator, which is non-blind, under the same conditions and using the same number of samples. Using the new estimator, we propose two blind detectors that require fewer samples than the second order time domain detector of [2] which is based on the classical estimator of the CAF. The first detector uses only the sparse property of the CAV while the second detector exploits the symmetry property of the CAV in addition to its sparse property, resulting in better performances. Both detectors, although they are blind, are more efficient than the non-blind detector of [2] in the case of a small number of samples.

Dans ces travaux de thèse, nous proposons un système de communication original permettant d’atteindre un haut débit et de répondre aux exigences de la qualité de service requise pour les communications courte portée dans le cadre du transport intelligent. Ce système se base sur la technologie Ultra Large Bande Impulsionnelle (IR-ULB) et sur un nouveau schéma de modulation nommé M-OAM (M-Orthogonal Amplitude Modulation). Les modulations M-OAM se basent sur le principe des modulations M-QAM en remplaçant les porteuses par des formes d’ondes ULB orthogonales de type MGF (Modified Gegenbauer Function). Ces modulations ont été évaluées sous les conditions d’un canal AWGN et des canaux IEEE 802.15.3a et IEEE 802.15.4a qui tiennent compte des paramètres réels de la route. En plus du haut débit exigé par les communications inter-véhiculaires, il faut assurer un échange d’informations simultané entre plusieurs utilisateurs de la route et garantir une bonne qualité de service. Dans cette optique, une nouvelle technique d’accès multiple adaptée est proposée. Chaque utilisateur a la possibilité d’utiliser la modulation OAM adéquate selon le débit désiré. Le récepteur de ce système se caractérise par un aspect intelligent grâce à l’intégration des principes de la Radio Cognitive (RC) qui permet de détecter l’arrivée du signal et d’identifier les paramètres de la modulation utilisée afin de s’y adapter d’une façon autonome. Une bonne qualité de service est assurée par la proposition d’une nouvelle technique de démodulation qui se base sur les Statistiques d’Ordres Supérieurs (SOS) permettant d’éliminer le bruit Gaussien. Les bonnes performances du système de communication M-OAM ainsi que l’ensemble des aspects proposés ont été validés expérimentalement au sein du laboratoire IEMN-DOAE. Dans la dernière partie de ce document nous avons présenté la réalisation d’un prototype de ce traitement en temps réel sur une plateforme FPGA, en exploitant des algorithmes parallélisables sur des architectures reconfigurables. / In this work of thesis, we propose an original communication system allowing to reach high data rate and to fulfill the requirements of quality of service necessary for the communications short range dedicated to intelligent transport. This system is based on the Ultra Wide Band Impulse (IR-ULB) technology and on new modulation scheme named M-OAM (M-states Orthogonal Amplitude Modulation). M-OAM modulations are based on the principle of modulations M-QAM by replacingthe carriers used for QAM modulation with orthogonal waveforms ULB type MGF (Modified Gegenbauer Function). These modulations were evaluated under the conditions of AWGN channel and IEEE 802.15 channels which take account of the real parameters of the road. Besides the high speed required by inter-vehicular communications, it is necessary to ensure simultaneous information exchange between several users of the road. Accordingly, new adaptive multiple access system is proposed. Each user has the possibility to use the adequate modulation OAM according to the desired speed. The receiver of this system is characterized by an intelligent aspect thanks to the integration of the principle of Cognitive Radio (RC) which makes it able to detect the signal arrival and to identify the parameters of the used modulation in order to adapt the demodulation in an autonomous way. A good quality of service is ensured by the proposed novel demodulation method based on the Higher Orders Statistics (HOS) to eliminate the Gaussian noise. The good performances of M-OAM communication system M-OAM as well as the whole of the suggested aspects are validated in experiments within IEMN-DOAE laboratory. In the last part of this document we presented the realization of prototype using real time processing developed on FPGA plateform and exploiting parallelisable algorithms on reconfigurable architectures.

Due to the highly-varying wireless channels over time, frequency, and space domains, statistical QoS provisioning, instead of deterministic QoS guarantees, has become a recognized feature in the next-generation wireless networks. In this dissertation, we study the adaptive wireless resource allocation problems for statistical QoS provisioning, such as guaranteeing the specified delay-bound violation probability, upper-bounding the average loss-rate, optimizing the average goodput/throughput, etc., in several typical types of mobile wireless networks. In the first part of this dissertation, we study the statistical QoS provisioning for mobile multicast through the adaptive resource allocations, where different multicast receivers attempt to receive the common messages from a single base-station sender over broadcast fading channels. Because of the heterogeneous fading across different multicast receivers, both instantaneously and statistically, how to design the efficient adaptive rate control and resource allocation for wireless multicast is a widely cited open problem. We first study the time-sharing based goodput-optimization problem for non-realtime multicast services. Then, to more comprehensively characterize the QoS provisioning problems for mobile multicast with diverse QoS requirements, we further integrate the statistical delay-QoS control techniques — effective capacity theory, statistical loss-rate control, and information theory to propose a QoS-driven optimization framework. Applying this framework and solving for the corresponding optimization problem, we identify the optimal tradeoff among statistical delay-QoS requirements, sustainable traffic load, and the average loss rate through the adaptive resource allocations and queue management. Furthermore, we study the adaptive resource allocation problems for multi-layer video multicast to satisfy diverse statistical delay and loss QoS requirements over different video layers. In addition, we derive the efficient adaptive erasure-correction coding scheme for the packet-level multicast, where the erasure-correction code is dynamically constructed based on multicast receivers’ packet-loss statuses, to achieve high error-control efficiency in mobile multicast networks. In the second part of this dissertation, we design the adaptive resource allocation schemes for QoS provisioning in unicast based wireless networks, with emphasis on statistical delay-QoS guarantees. First, we develop the QoS-driven time-slot and power allocation schemes for multi-user downlink transmissions (with independent messages) in cellular networks to maximize the delay-QoS-constrained sum system throughput. Second, we propose the delay-QoS-aware base-station selection schemes in distributed multiple-input-multiple-output systems. Third, we study the queueaware spectrum sensing in cognitive radio networks for statistical delay-QoS provisioning. Analyses and simulations are presented to show the advantages of our proposed schemes and the impact of delay-QoS requirements on adaptive resource allocations in various environments.

En raison de la demande croissante de services de communication sans fil et de la limitation des ressources de spectre, la radio cognitive (CR) a été initialement proposée pour résoudre la pénurie de spectre. CR divise les systèmes transmetteurs-récepteurs de communication en deux catégories : les Utilisateurs Principaux (PU) et les Utilisateurs Secondaires (SU). PU a le droit légal d'utiliser la bande spectrale, tandis que SU est un utilisateur opportuniste qui peut transmettre sur cette bande chaque fois qu'elle est vacante afin d'éviter toute interférence avec le signal de PU. De ce fait, la détection des activités de PU devient une priorité principale pour toute CR.Le Spectrum Sensing devient ainsi une partie importante d’un système CR, qui surveille les transmissions de PU. En effet, le Spectrum Sensing joue un rôle essentiel dans le mécanisme du fonctionnement du CR en localisant les canaux disponibles et, d'autre part, en protégeant les canaux occupés des interférences de la transmission SU. En fait, Spectrum Sensing a gagné beaucoup d'attention au cours de la dernière décennie, et de nombreux algorithmes sont proposés. Concernant la fiabilité de la performance, plusieurs défis comme le faible rapport signal sur bruit, l'incertitude de bruit (NU), la durée de détection du spectre, etc. Cette thèse aborde les défis de la détection du spectre et apporte quelques solutions. De nouveaux détecteurs basés sur la détection des caractéristiques cyclo-stationnaires et la densité spectrale de puissance (PSD) du signal de PU sont présentés. Un algorithme de test de signification de corrélation canonique (CCST) est proposé pour effectuer une détection cyclo-stationnaire. CCST peut détecter la présence des caractéristiques cycliques communes parmi les versions retardées du signal reçu. Ce test peut révéler la présence d'un signal cyclo-stationnaire dans le signal de mélange reçu. Une autre méthode de détection basée sur la PSD cumulative est proposée. En supposant que le bruit est blanc (sa PSD est plate), la PSD cumulative s'approche d'une droite. Cette forme devient non linéaire pour les signaux de télécommunication. Distinguer la forme cumulative PSD peut donc conduire à diagnostiquer l'état du canal.La radio cognitive Full-Duplex (FD-CR) a également été étudiée dans ce manuscrit, où plusieurs défis sont analysés en proposant de nouvelles contributions. Le fonctionnement FD permet au CR d'éviter la période de silence pendant la détection du spectre. Dans le système CR classique, le SU cesse de transmettre pendant la détection du spectre afin de ne pas affecter la fiabilité de détection. Dans FD-CR, SU peut éliminer la réflexion de son signal transmis et en même temps réaliser le Spectrum Sensing. En raison de certaines limitations, le résidu de l'auto-interférence ne peut pas être complètement annulé, alors la crédibilité de la détection du spectre est fortement affectée. Afin de réduire la puissance résiduelle, une nouvelle architecture de récepteur SU est élaborée pour atténuer les imperfections du circuit (comme le bruit de phase et la distorsion non linéaire de l'amplificateur à faible bruit du récepteur). La nouvelle architecture montre sa robustesse en assurant une détection fiable et en améliorant le débit de SU. / Due to the increasing demand of wireless communication services and the limitation in the spectrum resources, Cognitive Radio (CR) has been initially proposed in order to solve the spectrum scarcity. CR divides the communication transceiver into two categories: the Primary (PU) or the Secondary (SU) Users. PU has the legal right to use the spectrum bandwidth, while SU is an opportunistic user that can transmit on that bandwidth whenever it is vacant in order to avoid any interference to the signal of PU. Hence the detection of PU becomes a main priority for CR systems. The Spectrum Sensing is the part of the CR system, which monitors the PU activities. Spectrum Sensing plays an essential role in the mechanism of the CR functioning. It provides CR with the available channel in order to access them, and on the other hand, it protects occupied channels from the interference of the SU transmission. In fact, Spectrum Sensing has gained a lot of attention in the last decade, and numerous algorithms are proposed to perform it. Concerning the reliability of the performance, several challenges have been addressed, such as the low Signal to Noise Ratio (SNR), the Noise Uncertainty (NU), the Spectrum Sensing duration, etc. This dissertation addresses the Spectrum Sensing challenges and some solutions are proposed. New detectors based on Cyclo-Stationary Features detection and the Power Spectral Density (PSD) of the PU are presented. CanonicalCorrelation Significance Test (CCST) algorithm is proposed to perform cyclo-stationary detection. CCST can detect the presence of the common cyclic features among the delayed versions of the received signal. This test can reveal the presence of a cyclo-stationary signal in the received mixture signal. Another detection method based on the cumulative PSD is proposed. By assuming the whiteness of the noise (its PSD is at), the cumulative PSD approaches a straight line. This shape becomes non-linear when a telecommunication signal is present in the received mixture. Distinguishing the Cumulative PSD shape may lead to diagnose the channel status.Full-Duplex Cognitive Radio (FD-CR) has been also studied in this manuscript, where several challenges are analyzed by proposing a new contribution. FD functioning permits CR to avoid the silence period during the Spectrum Sensing. In classical CR system, SU stops transmitting during the Spectrum Sensing in order to do not affect the detection reliability. In FD-CR, SU can eliminate the reflection of its transmitted signal and at the same time achieving the Spectrum Sensing. Due to some limitations, the residual of the Self Interference cannot be completely cancelled, then the Spectrum Sensing credibility is highly affected. In order to reduce the residual power, a new SU receiver architecture is worked out to mitigate the hardware imperfections (such as the Phase Noise and the Non-Linear Distortion of the receiver Low-Noise Amplifier). The new architecture shows its robustness by ensuring a reliable detection and enhancing the throughput of SU.

Cognitive radio is a technology that aims to maximize the current usage of the licensed frequency spectrum. Cognitive radio aims to provide services for license-exempt users by making use of dynamic spectrum access (DSA) and opportunistic spectrum sharing strategies (OSS). Cognitive radios are defined as intelligent wireless devices capable of adapting their communication parameters in order to operate within underutilized bands while avoiding causing interference to licensed users. An underused band of frequencies in a specific location or time is known as a spectrum hole. Therefore, in order to locate spectrum holes, reliable spectrum sensing algorithms are crucial to facilitate the evolution of cognitive radio networks. Since a large and growing body of literature has mainly focused into the conventional time domain (TD) energy detector, throughout this thesis the problem of spectrum sensing is investigated within the context of a frequency domain (FD) approach. The purpose of this study is to investigate detection based on methods of nonparametric power spectrum estimation. The considered methods are the periodogram, Bartlett's method, Welch overlapped segments averaging (WOSA) and the Multitaper estimator (MTE). Another major motivation is that the MTE is strongly recommended for the application of cognitive radios. This study aims to derive the detector performance measures for each case. Another aim is to investigate and highlight the main differences between the TD and the FD approaches. The performance is addressed for independent and identically distributed (i.i.d.) Rayleigh channels and the general Rician and Nakagami fading channels. For each of the investigated detectors, the analytical models are obtained by studying the characteristics of the Hermitian quadratic form representation of the decision statistic and the matrix of the Hermitian form is identified. The results of the study have revealed the high accuracy of the derived mathematical models. Moreover, it is found that the TD detector differs from the FD detector in a number of aspects. One principal and generalized conclusion is that all the investigated FD methods provide a reduced probability of false alarm when compared with the TD detector. Also, for the case of periodogram, the probability of sensing errors is independent of the length of observations, whereas in time domain the probability of false alarm is increased when the sample size increases. The probability of false alarm is further reduced when diversity reception is employed. Furthermore, compared to the periodogram, both Bartlett method and Welch method provide better performance in terms of lower probability of false alarm but an increased probability of detection for a given probability of false alarm. Also, the performance of both Bartlett's method and WOSA is sensitive to the number of segments, whereas WOSA is also sensitive to the overlapping factor. Finally, the performance of the MTE is dependent on the number of employed discrete prolate spheroidal (Slepian) sequences, and the MTE outperforms the periodogram, Bartlett's method and WOSA, as it provides the minimal probability of false alarm.

The doctoral thesis deals with spectrum sensing and subsequent use of the frequency spectrum by multicarrier communication system, which parameters are set on the basis of the optimization technique. Adaptation settings can be made with respect to several requirements as well as state and occupancy of individual communication channels. The system, which is characterized above is often referred as cognitive radio. Equipments operating on cognitive radio principles will be widely used in the near future, because of frequency spectrum limitation. One of the main contributions of the work is the novel usage of the Kolmogorov – Smirnov statistical test as an alternative detection of primary user signal presence. The new fitness function for Particle Swarm Optimization (PSO) has been introduced and the Error Vector Magnitude (EVM) parameter has been used in the adaptive greedy algorithm and PSO optimization. The dissertation thesis also incorporates information about the reliability of the frequency spectrum sensing in the modified greedy algorithm. The proposed methods are verified by the simulations and the frequency domain energy detection is implemented on the development board with FPGA.

[pt] Nesta tese de doutorado foi investigado, por meio de simulações computacionais e em laboratório utilizando Matlab, GNU Radio e GNU Radio Companion (GRC), o desempenho de redes de Rádio Cognitivo com sensoriamento individual (SS) e com sensoriamento cooperativo (CSS) do espectro considerando o algoritmo não paramétrico de detecção de energia e diferentes abordagens deste método de detecção. Foi também implementado um cenário de medição em tempo real usando os equipamentos de rádio definido por software (SDR por suas siglas em inglês) conhecidos como Universal Software Radio Peripheral (USRP). Os cenários de medição consideram a cooperação, baseada na utilização de regras de fusão de dados do tipo hard, no sensoriamento local de sinais de TV Digital por usuários cognitivos não licenciados. A principal contribuição desta tese de doutorado baseia-se na formulação do método de energia combinando os conceitos da teoria clássica do sensoriamento de espectro das redes de Rádio Cognitivo, tanto com sensoriamento individual (SS) como sensoriamento cooperativo (CSS) de espectro, com um cenário de implementação em laboratório levando em conta os requisitos, parâmetros técnicos e de operação do equipamento de medição SDR. / [en] This PhD thesis investigate the performance of cognitive radio networks with single sensing (SS) and cooperative spectrum sensing (CSS) networks through computational and laboratory simulations using Matlab, GNU Radio and the GNU Radio Companion (GRC) computational radio software, considering the non-parametric energy detection method and different approaches to this method. The implementation also includes a real-time measurement testbed scenario using Software Defined Radio (SDR) equipment, known as Universal Software Radio Peripheral (USRP). The measurement scenarios consider the cooperative local sensing of the digital TV by non-licensed cognitive radio users, based on hard fusion rules. The main contribution of this doctoral thesis is based on the formulation of the energy detection method combining the concepts of the classical theory of the spectrum sensing of Cognitive Radio networks, with both individual sensing (SS) and cooperative spectrum sensing (CSS), in a laboratory implementation scenario according to the requirements, technical parameters and operation of the SDR measuring equipment.