Ce travail de thèse concerne la modélisation du canal de propagation dans les milieux industriels. Dans ce contexte, le canal de propagation a un comportement différent de celui classiquement rencontré en indoor. Cela est dû à l'aménagement des bâtiments qui sont plus grand et ouverts ainsi qu'à la présence de machines, d'objets mobiles et d'autres matériaux métalliques rencontrés dans ces environnements. Ainsi, les modèles de canaux indoor existants ne sont plus valides. L'utilisation de modèles déterministes comme alternative est possible mais limitée en raison du temps de calcul qui en découle.Pour répondre à cette problématique, nous proposons un modèle hybride de canal s'inspirant d'une méthode à tracer de rayons 3D et du modèle WINNER. L'originalité de ce modèle repose sur son caractère hybride consistant, en prétraitement, à partitionner l'environnement en zones de visibilité ou de non-visibilité «faible» et «forte» sur des critères déterministes liés à la propagation des ondes. Un modèle statistique, type WINNER, reprenant le concept de cluster est ensuite "joué" au sein de chacune des ces zones reproduisant ainsi fidèlement l'évolution des paramètres caractéristiques des clusters identifiés. Nous avons validé notre modèle en le comparant d'abord à un modèle déterministe et ensuite à la mesure. Sa robustesse ainsi que celle de WINNER sont testées en les simulant dans trois environnements différents et en les comparant au modèle déterministe à tracer de rayons. / This thesis focuses on the modeling of the propagation channel in industrial environments. In this context, the propagation channel has a different behavior than typically encountered in indoor. This is due to the construction of buildings that are larger and open and the presence of machines, moving objects and metal materials encountered in these environments. Thus, the existing indoor channel models are not valid. Using deterministic models as an alternative is possible, but limited by the computing time.To address this problem, we propose a hybrid channel model for communications in industrial environments inspired by a ray tracing method and Winner model. The originality of this model is its hybrid nature consisting, in preprocessing, in partitionning the environment in areas of visibility or non-visibility «weak» and «strong» based on deterministic criteria related to the wave propagation. A statistical model, as WINNER , using the concept of cluster is then played in each of these areas and faithfully reproducing the evolution of the characteristic parameters of the identified clusters. We have validated our model by comparing it firstly to a deterministic model and then to measurement. Its robustness as well that of WINNER are tested by simulating them in three different environments and by comparing them with the deterministic model.

The subject of this work deals with the problem of channel estimation for CDMA systems. This method of multiple access when individual users share the same full bandwidth simultaneously and are differentiated with any of pseudorandom sequences, is now the most perspective method. That is proved by its wide implementation in mobile networks of the third generation and higher systems. This work describes basic theory principles of spread spectrum, above all DS-CDMA (Direct Sequence-CDMA) and furthermore some phenomena of radio wireless channel that affect changes in transmitted signal in its way from transmitter to receiver. Terms of fading, multipath propagation, loss, refraction, scattering of the wave and Rice and Rayleigh probability density functions are mentioned. The third chapter deals with yet known and used capabilities of channel estimation. Differences, advantages and disadvantages of so-called blind estimation or training-based estimation are discussed. Two algorithms: LS method and sliding correlator are analyzed in more detail. There is also description of their simulations in Matlab and some results of these simulations are discussed. The last chapter deals with comparison of main characteristics and achievable accuracy of wireless channel impulse response estimation by both methods, and their possible utilization in real live.

No description available.

Cette thèse porte sur l’étude des stratégies d’amélioration de la qualité d’image dans les systèmes de communication sans fil et sur la conception de nouvelles métriques d’évaluation de la qualité. Tout d'abord, une nouvelle métrique de qualité d'image à référence réduite, basée sur un modèle statistique dans le domaine des ondelettes complexes, a été proposée. Les informations d’amplitude et de phase relatives des coefficients issues de la transformée en ondelettes complexes sont modélisées à l'aide de fonctions de densité de probabilité. Les paramètres associés à ces fonctions constituent la référence réduite qui sera transmise au récepteur. Ensuite, une approche basée sur les réseaux de neurones à régression généralisée est exploitée pour construire la relation de cartographie entre les caractéristiques de la référence réduite et le score objectif.Deuxièmement, avec la nouvelle métrique, une nouvelle stratégie de décodage est proposée pour la transmission d’image sur un canal de transmission sans fil réaliste. Ainsi, la qualité d’expérience (QoE) est améliorée tout en garantissant une bonne qualité de service (QoS). Pour cela, une nouvelle base d’images a été construite et des tests d’évaluation subjective de la qualité de ces images ont été effectués pour collecter les préférences visuelles des personnes lorsqu’elles sélectionnent les images avec différentes configurations de décodage. Un classificateur basé sur les algorithmes SVM et des k plus proches voisins sont utilisés pour la sélection automatique de la meilleure configuration de décodage.Enfin, une amélioration de la métrique a été proposée permettant de mieux prendre en compte les spécificités de la distorsion et la préférence des utilisateurs. Pour cela, nous avons combiné les caractéristiques globales et locales de l’image conduisant ainsi à une amélioration de la stratégie de décodage.Les résultats expérimentaux valident l'efficacité des métriques de qualité d'image et des stratégies de transmission d’images proposées. / This thesis focuses on the study of image quality strategies in wireless communication systems and the design of new quality evaluation metrics:Firstly, a new reduced-reference image quality metric, based on statistical model in complex wavelet domain, has been proposed. The magnitude and the relative phase information of the Dual-tree Complex Wavelet Transform coefficients are modelled by using probability density function and the parameters served as reduced-reference features which will be transmitted to the receiver. Then, a Generalized Regression Neural Network approach is exploited to construct the mapping relation between reduced-reference feature and the objective score.Secondly, with the new metric, a new decoding strategy is proposed for a realistic wireless transmission system, which can improve the quality of experience (QoE) while ensuring the quality of service (QoS). For this, a new database including large physiological vision tests has been constructed to collect the visual preference of people when they are selecting the images with different decoding configurations, and a classifier based on support vector machine or K-nearest neighboring is utilized to automatically select the decoding configuration.Finally, according to specific property of the distortion and people's preference, an improved metric has been proposed. It is the combination of global feature and local feature and has been demonstrated having a good performance in optimization of the decoding strategy.The experimental results validate the effectiveness of the proposed image quality metrics and the quality strategies.

Le contexte de cette thèse est celui des communications optiques sans fil pour des applications en environnements indoor. Pour discuter des performances d'une liaison optique sans fil, il est nécessaire d'établir une étude caractéristique du comportement du canal de propagation. Cette étude passe par l'étape de la mesure ou de l'estimation par la simulation de la réponse impulsionnelle. Après avoir décrit la composition d'une liaison et passé en revue les méthodes de simulation existantes, nous présentons nos algorithmes de simulation dans des environnements réalistes, en nous intéressant à leurs performances en termes de précision et de temps de calcul. Ces méthodes sont basées sur la résolution des équations de transport de la lumière par du lancer de rayons associées aux méthodes d'intégration stochastique de Monte Carlo. La version classique de ces méthodes est à la base de trois algorithmes de simulations proposés. En utilisant une optimisation par des chaînes de Markov, nous présentons ensuite deux autres algorithmes. Un bilan des performances de ces algorithmes est établi dans des scénarios mono et multi-antennes. Finalement, nous appliquons nos algorithmes pour caractériser l'impact de l'environnement de simulation sur les performances d'une liaison de communication par lumière visible, à savoir les modèles d'émetteurs, les matériaux des surfaces, l'obstruction du corps de l'utilisateur et sa mobilité, et la géométrie de la scène de simulation. / The context of this PhD thesis falls within the scope of optical wireless communications for applications in indoor environments. To discuss the performance of an optical wireless link, it is necessary to establish a characteristic study of the behavior of the optical wave propagation channel. This study can be realized by measurement or by the simulation of the channel impulse response. After describing the composition of an optical wireless link and reviewing existing simulation methods, we present our new simulation algorithms channel in realistic environments by focusing on their performances in terms of accuracy and their complexity in terms of computation time. These methods are based on solving the light transport equations by ray-tracing techniques associated with stochastic Monte Carlo integration methods. The classical version of these methods is the basis of three proposed simulation algorithms. By applying an optimization using Markov Chain, we present two new algorithms. A performance assessment of our simulation algorithms is established in mono and multi-antenna scenarios of our simulation algorithms. Finally, we present the application of these algorithms for characterizing the impact of the simulation environment on the performances of a visible light communication link. We particularly focus on the transmitter models, surface coating materials, obstruction of the user's body and its mobility, and the geometry of the simulation scene.

Η υλοποίηση πρακτικών ασύρματων συστημάτων επικοινωνίας δεδομένων στην τεχνολογία UWB παρουσιάζει ιδιαίτερες προκλήσεις, κυρίως λόγω της χαμηλής ισχύος εκπομπής και της πολύ σύντομης διάρκειας των παλμών που χρησιμοποιούνται, οι οποίοι θα πρέπει να στέλνονται με πολύ μεγάλες ταχύτητες για την επίτευξη των επιθυμητών ρυθμών μετάδοσης. Το κανάλι μετάδοσης είναι ιδιαίτερα επιλεκτικό ως προς την συχνότητα και εξαιρετικά πυκνό και πλούσιο σε πολυοδικές συνιστώσες με αρκετά μεγάλες καθυστερήσεις. Αυτές οι συνιστώσες μπορούν να ανιχνευθούν και να συλλεχθούν χρησιμοποιώντας κατάλληλες δομές δεκτών RAKE, οι οποίοι τις συνθέτουν ώστε να μεγιστοποιηθεί η ενέργεια του ωφέλιμου σήματος, αυξάνοντας την απόδοση του συστήματος. Οι δομές αυτές παρουσιάζουν την καλύτερη απόδοση σε τέτοια συστήματα, αλλά έχουν μεγάλη υπολογιστική πολυπλοκότητα, καθώς για την ικανοποιητική απόδοση του συστήματος πρέπει να συνδυάσουν πολλές συνιστώσες, δεδομένης και της χαμηλής ισχύος εκπομπής της τεχνολογίας. Συνεπώς, για την υλοποίηση ενός πρακτικού και αποδοτικού συστήματος, σημαντικό ζήτημα αποτελεί ο τρόπος επιλογής και συνδυασμού των συνιστωσών μέσω ενός αλγορίθμου που θα χρησιμοποιεί τον μικρότερο δυνατό αριθμό δακτύλων. Στόχοι της διατριβής ήταν η μελέτη της τεχνολογίας UWB, η διερεύνηση των παραμέτρων των παλμικών UWB συστημάτων, η μελέτη και εξομοίωση μοντέλων του καναλιού, η κατανόηση των οποίων είναι απαραίτητη για την αποτελεσματική ανίχνευση του σήματος και τον σχεδιασμό των αλγορίθμων ψηφιακής επεξεργασίας του σήματος, η διερεύνηση δεκτών RAKE καθώς και εναλλακτικών δομών, οι εξομοιώσεις πομποδέκτη παλμικού UWB σε επίπεδο συστήματος με έμφαση στον RAKE και τον εκτιμητή καναλιού, η διερεύνηση παραμέτρων και τεχνικών για την υλοποίηση σε υλικό και τέλος η ανάπτυξη, ο σχεδιασμός και υλοποίηση μιας πρακτικής δομής δέκτη με RAKE αποδιαμορφωτή και εκτιμητή καναλιού που συνδυάζει χαμηλή πολυπλοκότητα και ικανοποιητική απόδοση. Παρουσιάζονται και συγκρίνονται τρεις νέες διαφορετικές προσεγγίσεις σχεδίασης, οι οποίες βασίζονται σε προτεινόμενο υβριδικό αλγόριθμο (HPS) για την μείωση της πολυπλοκότητας του RAKE και δίνονται αποτελέσματα που αφορούν στην αξιοποίηση του υλικού και στις επιδόσεις του συστήματος. Tα αποτελέσματα παρουσιάζουν το trade-off ανάμεσα στην συλλογή ενέργειας, την απόδοση του δέκτη και την πολυπλοκότητά του. Η αποτελεσματικότητα των προτεινόμενων αρχιτεκτονικών επαληθεύεται μέσω ειδικής πλατφόρμας αναδιατασσόμενου υλικού στην οποία υλοποιήθηκε η σχεδίαση. / Τhe implementation of practical wireless data communications systems for the UWB technology is very challenging due to the use of low-power ns-duration pulses which have to be sent in a high-frequency in order to achieve the desirable data rates. The UWB channel is highly frequency selective and it is characterized by dense and rich multipath propagation and large multipath delay spreads in some cases. A RAKE receiver can be employed in order to exploit multipath diversity and effectively capture the desired signal energy which is dispersed over the various multipath components, helping to mitigate fading. However, the particular nature of UWB results in very low-energy paths which, in conjunction with high multipath diversity, leads to a RAKE receiver that must exploit a large number of MPCs in order to optimize the received SNR. Thus, for the implementation of a low-complexity system it is important to define a novel method for the selection and combining of MPCs and develop an algorithm that is able to utilize a minimum number of fingers in the RAKE structure. Our work was focused in the study of UWB technology, the investigation of the parameters of IR-UWB systems, the study and understanding of the channel models which is necessary for the design of practical and efficient DSP algorithms, the investigation of RAKE type receivers as well as other alternative structures, the system-level simulations of the IR-UWB transceiver with emphasis given to the algorithms for the RAKE demodulator and channel estimator, the investigation of the parameters and techniques for the implementation of the system in hardware and finally, the development, design, and implementation of a practical receiver structure that includes a RAKE demodulator and a channel estimator and combines low complexity and satisfactory performance. The ultimate goal of this work is the presentation and investigation of the proposed channel estimator and (MRC)-RAKE receiver architecture which is based on a proposed novel hybrid algorithm called HPS. Three different design approaches aiming to a practical system implementation in an FPGA are proposed and compared and system/algorithm performance, hardware utilization results are provided. The obtained results demonstrate the trade-off between energy capture, performance and receiver complexity. The effectiveness of the proposed architectures is verified on a special FPGA platform which was used for the implementation of the receiver structure.

Bayesian approaches for sparse signal recovery have enjoyed a long-standing history in signal processing and machine learning literature. Among the Bayesian techniques, the expectation maximization based Sparse Bayesian Learning(SBL) approach is an iterative procedure with global convergence guarantee to a local optimum, which uses a parameterized prior that encourages sparsity under an evidence maximization frame¬work. SBL has been successfully employed in a wide range of applications ranging from image processing to communications. In this thesis, we propose novel, efficient and low-complexity SBL-based algorithms that exploit structured sparsity in the presence of fully/partially known measurement matrices. We apply the proposed algorithms to the problem of channel estimation and data detection in Orthogonal Frequency Division Multiplexing(OFDM) systems. Further, we derive Cram´er Rao type lower Bounds(CRB) for the single and multiple measurement vector SBL problem of estimating compressible vectors and their prior distribution parameters. The main contributions of the thesis are as follows: We derive Hybrid, Bayesian and Marginalized Cram´er Rao lower bounds for the problem of estimating compressible vectors drawn from a Student-t prior distribution. We derive CRBs that encompass the deterministic or random nature of the unknown parameters of the prior distribution and the regression noise variance. We use the derived bounds to uncover the relationship between the compressibility and Mean Square Error(MSE) in the estimates. Through simulations, we demonstrate the dependence of the MSE performance of SBL based estimators on the compressibility of the vector. OFDM is a well-known multi-carrier modulation technique that provides high spectral efficiency and resilience to multi-path distortion of the wireless channel It is well-known that the impulse response of a wideband wireless channel is approximately sparse, in the sense that it has a small number of significant components relative to the channel delay spread. In this thesis, we consider the estimation of the unknown channel coefficients and its support in SISO-OFDM systems using a SBL framework. We propose novel pilot-only and joint channel estimation and data detection algorithms in block-fading and time-varying scenarios. In the latter case, we use a first order auto-regressive model for the time-variations, and propose recursive, low-complexity Kalman filtering based algorithms for channel estimation. Monte Carlo simulations illustrate the efficacy of the proposed techniques in terms of the MSE and coded bit error rate performance. • Multiple Input Multiple Output(MIMO) combined with OFDM harnesses the inherent advantages of OFDM along with the diversity and multiplexing advantages of a MIMO system. The impulse response of wireless channels between the Nt transmit and Nr receive antennas of a MIMO-OFDM system are group approximately sparse(ga-sparse),i.e. ,the Nt Nr channels have a small number of significant paths relative to the channel delay spread, and the time-lags of the significant paths between transmit and receive antenna pairs coincide. Often, wire¬less channels are also group approximately-cluster sparse(ga-csparse),i.e.,every ga-sparse channel consists of clusters, where a few clusters have all strong components while most clusters have all weak components. In this thesis, we cast the problem of estimating the ga-sparse and ga-csparse block-fading and time-varying channels using a multiple measurement SBL framework. We propose a bouquet of novel algorithms for MIMO-OFDM systems that generalize the algorithms proposed in the context of SISO-OFDM systems. The efficacy of the proposed techniques are demonstrated in terms of MSE and coded bit error rate performance.

Multiple-Input Multiple-Output (MIMO) communication using multiple antennas has received significant attention in recent years, both in the academia and industry, as they offer additional spatial dimensions for high-rate and reliable communication, without expending valuable bandwidth. However, exploiting these promised benefits of MIMO systems critically depends on fast and accurate acquisition of Channel State Information (CSI) at the Receiver (CSIR) and the Transmitter (CSIT). In Time Division Duplex (TDD) MIMO systems, where the forward channel and the reverse channel are the same, it is possible to exploit this reciprocity to reduce the overhead involved in acquiring CSI, both in terms of training duration and power. Further, many popular and efficient transmission schemes such as beam forming, spatial multiplexing over dominant channel modes, etc. do not require full CSI at the transmitter. In such cases, it is possible to reduce the Reverse Channel Training (RCT) overhead by only learning the part of the channel that is required for data transmission at the transmitter. In this thesis, we propose and analyze several novel channel-dependent RCT schemes for MIMO systems and analyze their performance in terms of (a) the mean-square error in the channel estimate, (b) lower bounds on the capacity, and (c) the diversity-multiplexing gain tradeoff. We show that the proposed training schemes offer significant performance improvement relative to conventional channel-agnostic RCT schemes. The main take-home messages from this thesis are as follows: • Exploiting CSI while designing the RCT sequence improves the performance. • The training sequence should be designed so as to convey only the part of the CSI required for data transmission by the transmitter. • Power-controlled RCT, when feasible, significantly outperforms fixed power RCT.