Les réseaux radio actuelles utilisent le spectre inefficacement, car une bande de fréquence est allouée de façon permanente à une technologie spécifique. Vu que le spectre est une ressource limitée, cette attribution statique ne pourra bientôt plus combler les besoins des systèmes de transmission qui ne cessent de croître. On peut toutefois optimiser l'utilisation du spectre en permettant des transmissions secondaires (SU) dans les espaces libres du primaire (PU). Cette vision constitue l'objectif principal de la radio cognitive. Nous proposons d'évaluer les stratégies de transmission pour la coexistence des systèmes primaires (PU) et SU dans les mêmes réseaux. Plus concrètement, nous nous focalisons sur un scénario spatial interweave en émettant les signaux SU dans les espaces vides du PU à l'aide d'un précodeur linéaire. Néanmoins, ce précodage nécessite une connaissance a priori des canaux interférents. L'échange d'informations entre le PU et le SU étant proscrit, nous exploitons l'hypothèse de la réciprocité du canal. Cette hypothèse compense l'absence de coopération, mais elle n'est pas si évidente à exploiter en pratique à cause des perturbations des circuits radio fréquence. Nous suggérons de compenser ces perturbations par des méthodes de calibration relative. Nous proposons ensuite une implémentation temps-réel des solutions sur une plateforme LTE. Pour finir, nous généralisons l'approche RC à un système de transmission multi-utilisateurs, à travers une combinaison des techniques RC et massive MIMO, cette approche constitue s’établit comme une solution à la progression exponentielle du trafic. / The accelerated evolution of wireless transmission in recent years has dramatically increased the spectrum overcrowding. Indeed, the spectrum is inefficiently used in the conventional networks, since a frequency band is statically allocated to a specific technology called primary (PU). Whereas the radio spectrum is limited, this static frequency allocation will no longer be able to meet the increasing needs of bandwidth. However, the spectrum can be optimally used in enabling secondary (SU) transmissions, provided the latters do not harm the PU. This opportunistic vision of wireless transmissions is the main aim of Cognitive Radio (CR). CR enables smart use of wireless resources and is a key ingredient to perform high spectral efficiency. We focus on a spatial interweave (SIW) CR scenario which exploits the spatial white spaces to enable SU transmissions. The latter forms spatial beams using precoders, so that there is no interference towards the primary. Nevertheless, this precoding requires acquisition of the crosslink channel. However, due to the lack of cooperation between PU and SU, we acquire the channel thanks to channel reciprocity. Furthermore, the practical use of the reciprocity is not as straightforward as in theory, because it is is jeopardized by the nonreciprocal radio frequency front-ends. These perturbations are compensated in our study by relative calibration algorithms. Subsequently, we propose an implementation of our solutions in a real-time LTE platform. Eventually, we extend the CR model to a MU system in suggesting a combination of SIW and massive MIMO techniques. This scheme is an interesting candidate to overcome the exponential traffic growth.

CoordenaÃÃo de AperfeiÃoamento de NÃvel Superior / Em diversas aplicaÃÃes do processamento de sinais em sistemas de comunicaÃÃo sem-fio, o sinal recebido à de natureza multidimensional, possuindo uma estrutura algÃbrica multilinear. Neste contexto, a decomposiÃÃo tensorial PARAFAC tem sido utilizada em vÃrios trabalhos ao longo dos Ãltimos seis anos. Observa-se, entretanto, que decomposiÃÃes tensoriais generalizadas sÃo necessÃrias para modelar uma classe mais ampla de sistemas de comunicaÃÃo, caracterizada pela presenÃa de estruturas de transmissÃo mais complexas, por modelos de canal mais realistas, e por tÃcnicas de processamento de sinais mais eficientes no receptor. Esta tese investiga novas abordagens tensorias e suas aplicaÃÃes em modelagem de sistemas MIMO, equalizaÃÃo, separaÃÃo de sinais e estimaÃÃo paramÃtrica de canal. Inicialmente, duas novas decomposiÃÃes tensoriais (PARAFAC em blocos com restriÃÃes e CONFAC) sÃo desenvolvidas e estudadas em termos de identificabilidade. Em uma segunda parte do trabalho, novas aplicaÃÃes destas decomposiÃÃes tensoriais sÃo propostas. A decomposiÃÃo PARAFAC em blocos com restriÃÃes à aplicada, primeiramente, Âa modelagem unificada de sistemassuperamostrados, DS-CDMA e OFDM, com aplicaÃÃo em equalizaÃÃo multiusuÃria. Em seguida, esta decomposiÃÃo à utilizada na modelagem de sistemas de transmissÃo MIMO com espalhamento espaÃo-temporal e detecÃÃo conjunta. Em seguida, a decomposiÃÃo CONFAC à explorada na concepÃÃo de uma nova arquitetura generalizada de transmissÃo MIMO/CDMA que combina diversidade e multiplexagem. As propriedades de unicidade desta decomposiÃÃo permitem o uso do processamento nÃo-supervisionado no receptor, visando a reconstruÃÃo dos sinais transmitidos e a estimaÃÃo do canal. Na terceira e Ãltima parte deste trabalho, explora-se a decomposiÃÃo PARAFAC no contexto de duas aplicaÃÃes diferentes. Na primeira, uma nova estrutura de transmissÃo espaÃo-temporal-freqÃencial à proposta para sistemas MIMO multiportadora. A segunda aplicaÃÃo consiste em um novo estimador paramÃtrico para canais multipercursos. / In several signal processing applications for wireless communications, the received signal is multidimensional in nature and may exhibit a multilinear algebraic structure. In this context, the PARAFAC tensor decomposition has been the subject of several works in the past six years. However, generalized tensor decompositions are necessary for covering a wider class of wireless communication systems with more complex transmission structures, more realistic channel models and more efficient receiver signal processing. This thesis investigates tensor modeling approaches for multiple-antenna systems, channel equalization, signal separation and parametric channel estimation. New tensor decompositions, namely, the block-constrained PARAFAC and CONFAC decompositions, are developed and studied in terms of identifiability. First, the block-constrained PARAFAC decomposition is applied for a uniÂed tensor modeling of oversampled, DS-CDMA and OFDM systems with application to blind multiuser equalization. This decomposition is also used for modeling multiple-antenna (MIMO) transmission systems with block space-time spreading and blind detection, which generalizes previous tensor-based MIMO transmission models. The CONFAC decomposition is then exploited for designing new MIMO-CDMA transmission schemes combining spatial diversity and multiplexing. Blind symbol/code/channel recovery is discussed from the uniqueness properties of this decomposition. This thesis also studies new applications of third-order PARAFAC decomposition. A new space-time-frequency spreading system is proposed for multicarrier multiple-access systems, where this decomposition is used as a joint spreading and multiplexing tool at the transmitter using tridimensional spreading code with trilinear structure. Finally, we present a PARAFAC modeling approach for the parametric estimation of SIMO and MIMO multipath wireless channels with time-varying structure.

Τα τελευταία χρόνια χαρακτηρίζονται από μια αλματώδη ανάπτυξη των προϊόντων και υπηρεσιών που βασίζονται στα δίκτυα ασύρματης επικοινωνίας, ενώ προκύπτουν σημαντικές ερευνητικές προκλήσεις. Τα συστήματα πολλαπλών κεραιών στον πομπό και στο δέκτη, γνωστά και ως συστήματα MIMO (multi-input multi-output), καθώς και η τεχνολογία πολλαπλής προσπέλασης με χρήση κωδικών (code division multiple access, CDMA) αποτελούν δύο από τα βασικά μέτωπα ανάπτυξης των ασύρματων τηλεπικοινωνιών. Στα πλαίσια της παρούσας διδακτορικής διατριβής, ασχοληθήκαμε με την ανάπτυξη και μελέτη αλγορίθμων επεξεργασίας σήματος για τα δύο παραπάνω συστήματα, όπως περιγράφεται αναλυτικά παρακάτω. Σχετικά με τα συστήματα MIMO, η πρωτοποριακή έρευνα που πραγματοποιήθηκε στα Bell Labs γύρω στα 1996, όπου αναπτύχθηκε η αρχιτεκτονική BLAST (Bell Labs Layered Space-Time), απέδειξε ότι η χρήση πολλαπλών κεραιών μπορεί να οδηγήσει σε σημαντική αύξηση της χωρητικότητας των ασύρματων συστημάτων. Προκειμένου να αξιοποιηθούν οι παραπάνω δυνατότητες, απαιτείται η σχεδίαση σύνθετων δεκτών MIMO. Προς αυτήν την κατεύθυνση, έχει προταθεί ένας μεγάλος αριθμός μεθόδων ισοστάθμισης του καναλιού. Ωστόσο, οι περισσότερες από αυτές υποθέτουν ότι το ασύρματο κανάλι είναι: 1) χρονικά σταθερό, 2) συχνοτικά επίπεδο (δεν εισάγει διασυμβολική παρεμβολή), και κυρίως 3) ότι είναι γνωστό στο δέκτη. Δεδομένου ότι σε ευρυζωνικά συστήματα μονής φέρουσας οι παραπάνω υποθέσεις είναι δύσκολο να ικανοποιηθούν, στραφήκαμε προς τις προσαρμοστικές μεθόδους ισοστάθμισης. Συγκεκριμένα, αναπτύξαμε τρεις βασικούς αλγορίθμους. Ο πρώτος αλγόριθμος αποτελεί έναν προσαρμοστικό ισοσταθμιστή ανάδρασης αποφάσεων (decision feedback equalizer, DFE) για συχνοτικά επίπεδα κανάλια ΜΙΜΟ. Ο προτεινόμενος MIMO DFE ακολουθεί την αρχιτεκτονική BLAST, και ανανεώνεται με βάση τον αλγόριθμο αναδρομικών ελαχίστων τετραγώνων (RLS) τετραγωνικής ρίζας. Ο ισοσταθμιστής μπορεί να παρακολουθήσει ένα χρονικά μεταβαλλόμενο κανάλι, και, από όσο γνωρίζουμε, έχει τη χαμηλότερη πολυπλοκότητα από όλους τους δέκτες BLAST που έχουν προταθεί έως σήμερα. Ο δεύτερος αλγόριθμος αποτελεί την επέκταση του προηγούμενου σε συχνοτικά επιλεκτικά κανάλια. Μέσω κατάλληλης μοντελοποίησης του προβλήματος ισοστάθμισης, οδηγηθήκαμε σε έναν αποδοτικό DFE για ευρυζωνικά κανάλια MIMO. Τότε, η διαδικασία της ισοστάθμισης εμφανίζει προβλήματα αριθμητικής ευστάθειας, που λόγω της υλοποίησης RLS τετραγωνικής ρίζας αντιμετωπίστηκαν επιτυχώς. Κινούμενοι προς την κατεύθυνση περαιτέρω μείωσης της πολυπλοκότητας, προτείναμε έναν προσαρμοστικό MIMO DFE που ανανεώνεται με βάση τον αλγόριθμο ελαχίστων μέσων τετραγώνων (LMS) υλοποιημένο εξ ολοκλήρου στο πεδίο της συχνότητας. Με χρήση του ταχύ μετασχηματισμού Fourier (FFT), μειώνεται η απαιτούμενη πολυπλοκότητα. Παράλληλα, η μετάβαση στο πεδίο των συχνοτήτων έχει ως αποτέλεσμα την προσεγγιστική διαγωνοποίηση του συστήματος, προσφέροντας ανεξάρτητη ανανέωση των φίλτρων ανά συχνοτική συνιστώσα και επιτάχυνση της σύγκλισης του αλγορίθμου. Ο προτεινόμενος ισοσταθμιστής πετυχαίνει μια καλή ανταλλαγή μεταξύ απόδοσης και πολυπλοκότητας. Παράλληλα με τα παραπάνω, ασχοληθήκαμε με την εκτίμηση του ασύρματου καναλιού σε ένα ασύγχρονο σύστημα CDMA. Το βασικό σενάριο είναι ότι ο σταθμός βάσης γνωρίζει ήδη τους ενεργούς χρήστες, και καλείται να εκτιμήσει τις παραμέτρους του καναλιού ανερχόμενης ζεύξης ενός νέου χρήστη που εισέρχεται στο σύστημα. Το πρόβλημα περιγράφεται από μια συνάρτηση ελαχίστων τετραγώνων, η οποία είναι γραμμική ως προς τα κέρδη του καναλιού, και μη γραμμική ως προς τις καθυστερήσεις του. Αποδείξαμε ότι το πρόβλημα έχει μια προσεγγιστικά διαχωρίσιμη μορφή, και προτείναμε μια επαναληπτική μέθοδο υπολογισμού των παραμέτρων. Ο προτεινόμενος αλγόριθμος δεν απαιτεί κάποια ειδική ακολουθία διάχυσης και λειτουργεί αποδοτικά ακόμη και για περιορισμένη ακολουθία εκπαίδευσης. Είναι εύρωστος στην παρεμβολή πολλαπλών χρηστών και περισσότερο ακριβής από μια υπάρχουσα μέθοδο εις βάρος μιας ασήμαντης αύξησης στην υπολογιστική πολυπλοκότητα. / Over the last decades, a dramatic progress in the products and services based on wireless communication networks has been observed, while, at the same time, new research challenges arise. The systems employing multiple antennas at the transmitter and the receiver, known as MIMO (multi-input multi-output) systems, as well as code division multiple access (CDMA) systems, are two of the main technologies employed for the evolution of wireless communications. During this PhD thesis, we worked on the design and analysis of signal processing algorithms for the two above systems, as it is described in detail next. Concerning the MIMO systems, the pioneering work performed at Bell Labs around 1996, where the BLAST (Bell Labs Layered Space-Time) architecture has been developed, proved that by using multiple antennas can lead to a significant increase in wireless systems capacity. To exploit this potential, sophisticated MIMO receivers should be designed. To this end, a large amount of channel equalizers has been proposed. However, most of these methods assume that the wireless channel is: 1) static, 2) frequency flat (no intersymbol interference is introduced), and mainly 3) it is perfectly known at the receiver. Provided that in high rate single carrier systems these assumptions are difficult to be met, we focused our attention on adaptive equalization methods. More specifically, three basic algorithms have been developed. The first algorithm is an adaptive decision feedback equalizer (DFE) for frequency flat MIMO channels. The proposed MIMO DFE implements the BLAST architecture, and it is updated by the recursive least squares (RLS) algorithm in its square root form. The new equalizer can track time varying channels, and, to the best of our knowledge, it has the lowest computational complexity among the BLAST receivers that have been proposed up to now. The second algorithm is an extension of the previous one to the frequency selective channel case. By proper modeling of the equalization problem, we arrived at an efficient DFE for wideband MIMO channels. In this case, the equalization process encounters numerical instability problems, which were successfully treated by the square root RLS implementation employed. To further reduce complexity, we proposed an adaptive MIMO DFE that is updated by the least mean square (LMS) algorithm, fully implemented in the frequency domain. By using the fast Fourier transform (FFT), the complexity required is considerably reduced. Moreover, the frequency domain implementation leads to an approximate decoupling of the equalization problem at each frequency bin. Thus, an independent update of the filters at each frequency bin allows for a faster convergence of the algorithm. The proposed equalizer offers a good performance - complexity tradeoff. Furthermore, we worked on channel estimation for an asynchronous CDMA system. The assumed scenario is that the base station has already acquired all the active users, while the uplink channel parameters of a new user entering the system should be estimated. The problem can be described via a least squares cost function, which is linear with respect to the channel gains, and non linear to its delays. We proved that the problem is approximately decoupled, and a new iterative parameter estimation method has been proposed. The suggested method does not require any specific pilot sequence and performs well even for a short training interval. It is robust to multiple access interference and more accurate compared to an existing method, at the expense of an insignificant increase in computational complexity.

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.

La radio impulsionnelle UWB (IR-UWB) est une technologie de communication relativement récente, qui apporte une solution intéressante au problème de l’encombrement du spectre RF, et qui répond aux exigences de haut débit et localisation précise d’un nombre croissant d’applications, telles que les communications indoor, les réseaux de capteurs personnels et corporels, l’IoT, etc. Ses caractéristiques uniques sont obtenues par la transmission d’impulsions de très courte durée (inférieure à 1 ns), occupant une largeur de bande allant jusqu’à 7,5 GHz, et ayant une densité spectrale de puissance extrêmement faible (inférieure à -43 dBm/MHz). Les meilleures performances d’un système IR-UWB sont obtenues avec des récepteurs cohérents de type Rake, au prix d’une complexité accrue, due notamment à l’étape d’estimation du canal UWB, caractérisé par de nombreux trajets multiples. Cette étape de traitement nécessite l’estimation d’un ensemble de composantes spectrales du signal reçu, sans pouvoir faire appel aux techniques d’échantillonnage usuelles, en raison d’une limite de Nyquist particulièrement élevée (plusieurs GHz).Dans le cadre de cette thèse, nous proposons de nouvelles approches, à faible complexité, pour l’estimation du canal UWB, basées sur la représentation parcimonieuse du signal reçu, la théorie de l’acquisition compressée, et les méthodes de reconstruction des signaux à taux d’innovation fini. La réduction de complexité ainsi obtenue permet de diminuer de manière significative le coût d’implémentation du récepteur IR-UWB et sa consommation. D’abord, deux schémas d’échantillonnage compressé, monovoie (filtre SoS) et multivoie (MCMW) identifiés dans la littérature sont étendus au cas des signaux UWB ayant un spectre de type passe-bande, en tenant compte de leur implémentation réelle dans le circuit. Ces schémas permettent l’acquisition des coefficients spectraux du signal reçu et l’échantillonnage à des fréquences très réduites ne dépendant pas de la bande passante des signaux, mais seulement du nombre des trajets multiples du canal UWB. L’efficacité des approches proposées est démontrée au travers de deux applications : l’estimation du canal UWB pour un récepteur Rake cohérent à faible complexité, et la localisation précise en environnement intérieur dans un contexte d’aide à la dépendance.En outre, afin de réduire la complexité de l’approche multivoie en termes de nombre de voies nécessaires pour l’estimation du canal UWB, nous proposons une architecture à nombre de voies réduit, en augmentant le nombre d’impulsions pilotes émises.Cette même approche permet aussi la réduction de la fréquence d’échantillonnage associée au schéma MCMW. Un autre objectif important de la thèse est constitué par l’optimisation des performances des approches proposées. Ainsi, bien que l’acquisition des coefficients spectraux consécutifs permette une mise en oeuvre simple des schémas multivoie, nous montrons que les coefficients ainsi choisis, ne donnent pas les performances optimales des algorithmes de reconstruction. Ainsi, nous proposons une méthode basée sur la cohérence des matrices de mesure qui permet de trouver l’ensemble optimal des coefficients spectraux, ainsi qu’un ensemble sous-optimal contraint où les positions des coefficients spectraux sont structurées de façon à faciliter la conception du schéma MCMW. Enfin, les approches proposées dans le cadre de cette thèse sont validées expérimentalement à l’aide d’une plateforme expérimentale UWB du laboratoire Lab-STICC CNRS UMR 6285. / Ultra-wideband impulse radio (IR-UWB) is a relatively new communication technology that provides an interesting solution to the problem of RF spectrum scarcity and meets the high data rate and precise localization requirements of an increasing number of applications, such as indoor communications, personal and body sensor networks, IoT, etc. Its unique characteristics are obtained by transmitting pulses of very short duration (less than 1 ns), occupying a bandwidth up to 7.5 GHz, and having an extremely low power spectral density (less than -43 dBm / MHz). The best performances of an IR-UWB system are obtained with Rake coherent receivers, at the expense of increased complexity, mainly due to the estimation of UWB channel, which is characterized by a large number of multipath components. This processing step requires the estimation of a set of spectral components for the received signal, without being able to adopt usual sampling techniques, because of the extremely high Nyquist limit (several GHz).In this thesis, we propose new low-complexity approaches for the UWB channel estimation, relying on the sparse representation of the received signal, the compressed sampling theory, and the reconstruction of the signals with finite rate of innovation. The complexity reduction thus obtained makes it possible to significantly reduce the IR-UWB receiver cost and consumption. First, two existent compressed sampling schemes, single-channel (SoS) and multi-channel (MCMW), are extended to the case of UWB signals having a bandpass spectrum, by taking into account realistic implementation constraints. These schemes allow the acquisition of the spectral coefficients of the received signal at very low sampling frequencies, which are not related anymore to the signal bandwidth, but only to the number of UWB channel multipath components. The efficiency of the proposed approaches is demonstrated through two applications: UWB channel estimation for low complexity coherent Rake receivers, and precise indoor localization for personal assistance and home care.Furthermore, in order to reduce the complexity of the MCMW approach in terms of the number of channels required for UWB channel estimation, we propose a reduced number of channel architecture by increasing the number of transmitted pilot pulses. The same approach is proven to be also useful for reducing the sampling frequency associated to the MCMW scheme.Another important objective of this thesis is the performance optimization for the proposed approaches. Although the acquisition of consecutive spectral coefficients allows a simple implementation of the MCMW scheme, we demonstrate that it not results in the best performance of the reconstruction algorithms. We then propose to rely on the coherence of the measurement matrix to find the optimal set of spectral coefficients maximizing the signal reconstruction performance, as well as a constrained suboptimal set, where the positions of the spectral coefficients are structured so as to facilitate the design of the MCMW scheme. Finally, the approaches proposed in this thesis are experimentally validated using the UWB equipment of Lab-STICC CNRS UMR 6285.

Pour permettre l’accroissement de débit et de robustesse dans les futurs systèmes de communication sans fil, les processus itératifs sont de plus considérés dans les récepteurs. Cependant, l’adoption d’un traitement itératif pose des défis importants dans la conception du récepteur. Dans cette thèse, un récepteur itératif combinant les techniques de détection multi-antennes avec le décodage de canal est étudié. Trois aspects sont considérés dans un contexte MIMOOFDM: la convergence, la performance et la complexité du récepteur. Dans un premier temps, nous étudions les différents algorithmes de détection MIMO à décision dure et souple basés sur l’égalisation, le décodage sphérique, le décodage K-Best et l’annulation d’interférence. Un décodeur K-best de faible complexité (LC-K-Best) est proposé pour réduire la complexité sans dégradation significative des performances. Nous analysons ensuite la convergence de la combinaison de ces algorithmes de détection avec différentes techniques de codage de canal, notamment le décodeur turbo et le décodeur LDPC en utilisant le diagramme EXIT. En se basant sur cette analyse, un nouvel ordonnancement des itérations internes et externes nécessaires est proposé. Les performances du récepteur ainsi proposé sont évaluées dans différents modèles de canal LTE, et comparées avec différentes techniques de détection MIMO. Ensuite, la complexité des récepteurs itératifs avec différentes techniques de codage de canal est étudiée et comparée pour différents modulations et rendement de code. Les résultats de simulation montrent que les approches proposées offrent un bon compromis entre performance et complexité. D’un point de vue implémentation, la représentation en virgule fixe est généralement utilisée afin de réduire les coûts en termes de surface, de consommation d’énergie et de temps d’exécution. Nous présentons ainsi une représentation en virgule fixe du récepteur itératif proposé basé sur le décodeur LC K-Best. En outre, nous étudions l’impact de l’estimation de canal sur la performance du système. Finalement, le récepteur MIMOOFDM itératif est testé sur la plateforme matérielle WARP, validant le schéma proposé. / Recently, iterative processing has been widely considered to achieve near-capacity performance and reliable high data rate transmission, for future wireless communication systems. However, such an iterative processing poses significant challenges for efficient receiver design. In this thesis, iterative receiver combining multiple-input multiple-output (MIMO) detection with channel decoding is investigated for high data rate transmission. The convergence, the performance and the computational complexity of the iterative receiver for MIMO-OFDM system are considered. First, we review the most relevant hard-output and soft-output MIMO detection algorithms based on sphere decoding, K-Best decoding, and interference cancellation. Consequently, a low-complexity K-best (LCK- Best) based decoder is proposed in order to substantially reduce the computational complexity without significant performance degradation. We then analyze the convergence behaviors of combining these detection algorithms with various forward error correction codes, namely LTE turbo decoder and LDPC decoder with the help of Extrinsic Information Transfer (EXIT) charts. Based on this analysis, a new scheduling order of the required inner and outer iterations is suggested. The performance of the proposed receiver is evaluated in various LTE channel environments, and compared with other MIMO detection schemes. Secondly, the computational complexity of the iterative receiver with different channel coding techniques is evaluated and compared for different modulation orders and coding rates. Simulation results show that our proposed approaches achieve near optimal performance but more importantly it can substantially reduce the computational complexity of the system. From a practical point of view, fixed-point representation is usually used in order to reduce the hardware costs in terms of area, power consumption and execution time. Therefore, we present efficient fixed point arithmetic of the proposed iterative receiver based on LC-KBest decoder. Additionally, the impact of the channel estimation on the system performance is studied. The proposed iterative receiver is tested in a real-time environment using the MIMO WARP platform.

[pt] Este trabalho tem como finalidade o estudo das possibilidade do sistema GFDM (Generalized Frequency Division Multiplexing). Para o estudo feito foi apresentado um modelo matricial para representar os sinais gerados no sistema GFDM, a semelhança do modelo de sinal do sistema OFDM (Orthogonal Frequency Division Multiplexing). Tal modelo permitiu a obtenção de expressões analíticas para a Densidade Espectral de Potência (DEP, Spectral Power Density) dos sinais e sua comparação com a DEP dos sinais transmitidos em sistemas OFDM. A partir do modelo matricial apresentado são estudados o desempenho de diferentes tipos de equalizadores/detectores lineares clássicos passíveis de utilização neste sistema de comunicações digitais, tais como Zero Forcing, Minimum Mean Square Error e Matched Filter. Além disso o trabalho propõe e analisa o desempenho resultante da aplicação de técnicas de supressão de interferência PIC (Parallel Interference Cancellation) em conjunto com os detectores lineares mencionados e dos detectores LAS (Likelihood Ascent Search) precedidos por equalizadores Matched Filter (MF-LAS). O número de estágios PIC realizados em cada detecção é controlado por uma estratégia de parada baseada na métrica de distância. Diferentes esquemas de detecção MF-LAS em conjunto com PIC são também propostos e examinadas. Finalmente, partindo do modelo matricial desenvolvido neste trabalho é realizada a estimação de canal empregando a estratégia de símbolos pilotos ortogonais. As diferentes estratégias de detecção examinadas para o sistemas GFDM são comparadas em termos de desempenho BER (Bit Error Rate) e da complexidade computacional associada aos respectivos detectores. Comparações entre os sistemas GFDM e OFDM com destaque na complexidade na geração de sinais, eficiência espectral e desempenho estão também incluídos nesta dissertação. / [en] The main goal of the presented work is to study the possibilities of the GFDM system (Generalized Frequency Division Multiplexing). For achieving this purpose, a matrix model is presented which represents the signals generated in the GFDM system, similar to the signal model of the OFDM (Orthogonal Frequency Division Multiplexing) system. This model allows the obtainment analytical expressions for the Spectral Power Density (DEP) of the signals and their comparison with the DEP of the signals transmitted in OFDM systems. Furthermore, we study the performance of different types of classical linear equalizers/detectors that can be used in the digital communications systems, such as Zero Forcing, Minimum Mean Square Error and Matched Filter. In addition, we propose and analyze the performance resulting from the application of PIC (Parallel Interference Cancellation) interference suppression techniques together with the linear detectors mentioned and LAS (Likelihood Ascent Search) detectors preceded by Matched Filter (MF-LAS) equalizers. The number of PIC stages performed at each detection is controlled by a stop strategy based on the distance metric. Different MF-LAS detection schemes together with PIC are also proposed and examined. Finally, the channel estimation is performing based on the matrix model developed in this work and using orthogonal pilots symbols. The differents strategies of detection examined for GFDM systems are compared in terms of BER performance (Bit Error Rate) and the computational complexity associated with the respective detectors. Comparisons between GFDM and OFDM systems based on criterions as the complexity of the signal generation, spectral efficiency and performance are also included in this dissertation.

This thesis aims to contribute to the developments of wireless communication systems. The work generally consists of three parts: the first part is a discussion on general digital communication systems, the second part focuses on wireless channel modelling and fading mitigation techniques, and in the third part we discuss the possible application of advanced digital signal processing, especially time-frequency representation and blind source separation, to wireless communication systems. The first part considers general digital communication systems which will be incorporated in later parts. Today's wireless communication system is a subbranch of a general digital communication system that employs various techniques of A/D (Analog to Digital) conversion, source coding, error correction, coding, modulation, and synchronization, signal detection in noise, channel estimation, and equalization. We study and develop the digital communication algorithms to enhance the performance of wireless communication systems. In the Second Part we focus on wireless channel modelling and fading mitigation techniques. A modified Jakes' method is developed for Rayleigh fading channels. We investigate the level-crossing rate (LCR), the average duration of fades (ADF), the probability density function (PDF), the cumulative distribution function (CDF) and the autocorrelation functions (ACF) of this model. The simulated results are verified against the analytical Clarke's channel model. We also construct frequency-selective geometrical-based hyperbolically distributed scatterers (GBHDS) for a macro-cell mobile environment with the proper statistical characteristics. The modified Clarke's model and the GBHDS model may be readily expanded to a MIMO channel model thus we study the MIMO fading channel, specifically we model the MIMO channel in the angular domain. A detailed analysis of Gauss-Markov approximation of the fading channel is also given. Two fading mitigation techniques are investigated: Orthogonal Frequency Division Multiplexing (OFDM) and spatial diversity. In the Third Part, we devote ourselves to the exciting fields of Time-Frequency Analysis and Blind Source Separation and investigate the application of these powerful Digital Signal Processing (DSP) tools to improve the performance of wireless communication systems.

Cette thèse traite de l'estimation d'un canal de communication radio-mobile multi-bond. La communication entre l'émetteur et le récepteur est ainsi faite par l'intermédiaire de relais (de type « Amplify and-Forward ») en série. Les différents éléments (émetteurs, relais, récepteurs) peuvent être fixes ou mobiles. Chaque lien de communication (chaque bond) est modélisé par un canal de Rayleigh à évanouissements plats, avec un spectre Doppler issu de deux environnements possibles de diffusion : en deux dimensions (2D, amenant le spectre en U de Jakes), ou en trois dimensions (3D, amenant un spectre Doppler plat). L'objectif majeur de la thèse est l'estimation dynamique du canal global issue de la cascade des différents liens. A cette fin, la cascade de canaux est approchée par une modèle auto-régressif du premier ordre (AR (1)), et l'estimation est réalisée à l'aide d'un algorithme standard, le filtre de Kalman. La méthode couramment utilisée dans la littérature pour fixer le paramètre du modèle AR(1) est basée sur un critère de « corrélation matching » (CM). Cependant, nous montrons que pour des canaux à variations lentes, un autre critère basé sur la minimisation de la variance asymptotique (MAV) de la sortie du filtre de Kalman est plus approprié. Pour les deux critères, CM et MAV, cette thèse donne une justification analytique en fournissant des formules approchées de la variance d'estimation par le filtre de Kalman, ainsi que du réglage optimal du paramètre du modèle AR(1). Ces formules analytiques sont données en fonctions des fréquences Doppler et du rapport signal sur bruit, pour les environnements de diffusion 2D et 3D, quel que soit le nombre et le type de bonds (fixe-mobile ou mobile-mobile). Les résultats de simulations montrent un gain considérable en termes de l'erreur quadratique moyenne (MSE) de l'estimateur de canal bien réglé, en particulier pour le scénario le plus courant de canal à évanouissements lents. / This thesis deals with the estimation of the multihop Amplify-and-Forward relay communications. The various objects (transmitter, relays, receivers) can be fixed or mobile. Each link is modeled by a flat fading Rayleigh channel, with a Doppler spectrum resulting from two-dimensional (2D, leading to the U-shape Dopller spectrum) or three-dimensional (3D, leading to a flat Doppler spectrum) scattering environments. The cascade of channel hops is approximated by a first-order autoregressive (AR(1)) model and is tracked by a standard estimation algorithm, the Kalman Filter (KF). The common method used in the literature to tune the parameter of the AR(1) model is based on a Correlation Matching (CM) criterion. However, for slow fading variations, another criterion based on the off-line Minimization of the Asymptotic Variance (MAV) of the KF is shown to be more appropriate. For both the CM and MAV criteria, this thesis gives analytic justification by providing approximated closed-form expressions of the estimation variance in output of the Kalman filter, and of the optimal AR(1) parameter. The analytical results are calculated for given Doppler frequencies and Signal-to-Noise Ratio for both scattering environments, whatever the number and type of transmission hops (Fixed-to-Mobile or Mobile-to-Mobile). The simulation results show a considerable gain in terms of the Mean Square Error (MSE) of the well tuned Kalman-based channel estimator, especially for the most common scenario of slow-fading channel.

Compressed sensing has been proposed as a computationally efficient method to estimate the finite-dimensional signals. The idea is to develop an undersampling operator that can sample the large but finite-dimensional sparse signals with a rate much below the required Nyquist rate. In other words, considering the sparsity level of the signal, the compressed sensing samples the signal with a rate proportional to the amount of information hidden in the signal. In this dissertation, first, we employ compressed sensing for physical layer signal processing of directional millimeter-wave communication. Second, we go through the theoretical aspect of compressed sensing by running a comprehensive theoretical analysis of compressed sensing to address two main unsolved problems, (1) continuous-extension compressed sensing in locally convex space and (2) computing the optimum subspace and its dimension using the idea of equivalent topologies using Köthe sequence. In the first part of this thesis, we employ compressed sensing to address various problems in directional millimeter-wave communication. In particular, we are focusing on stochastic characteristics of the underlying channel to characterize, detect, estimate, and track angular parameters of doubly directional millimeter-wave communication. For this purpose, we employ compressed sensing in combination with other stochastic methods such as Correlation Matrix Distance (CMD), spectral overlap, autoregressive process, and Fuzzy entropy to (1) study the (non) stationary behavior of the channel and (2) estimate and track channel parameters. This class of applications is finite-dimensional signals. Compressed sensing demonstrates great capability in sampling finite-dimensional signals. Nevertheless, it does not show the same performance sampling the semi-infinite and infinite-dimensional signals. The second part of the thesis is more theoretical works on compressed sensing toward application. In chapter 4, we leverage the group Fourier theory and the stochastical nature of the directional communication to introduce families of the linear and quadratic family of displacement operators that track the join-distribution signals by mapping the old coordinates to the predicted new coordinates. We have shown that the continuous linear time-variant millimeter-wave channel can be represented as the product of channel Wigner distribution and doubly directional channel. We notice that the localization operators in the given model are non-associative structures. The structure of the linear and quadratic localization operator considering group and quasi-group are studied thoroughly. In the last two chapters, we propose continuous compressed sensing to address infinite-dimensional signals and apply the developed methods to a variety of applications. In chapter 5, we extend Hilbert-Schmidt integral operator to the Compressed Sensing Hilbert-Schmidt integral operator through the Kolmogorov conditional extension theorem. Two solutions for the Compressed Sensing Hilbert Schmidt integral operator have been proposed, (1) through Mercer's theorem and (2) through Green's theorem. We call the solution space the Compressed Sensing Karhunen-Loéve Expansion (CS-KLE) because of its deep relation to the conventional Karhunen-Loéve Expansion (KLE). The closed relation between CS-KLE and KLE is studied in the Hilbert space, with some additional structures inherited from the Banach space. We examine CS-KLE through a variety of finite-dimensional and infinite-dimensional compressible vector spaces. Chapter 6 proposes a theoretical framework to study the uniform convergence of a compressible vector space by formulating the compressed sensing in locally convex Hausdorff space, also known as Fréchet space. We examine the existence of an optimum subspace comprehensively and propose a method to compute the optimum subspace of both finite-dimensional and infinite-dimensional compressible topological vector spaces. To the author's best knowledge, we are the first group that proposes continuous compressed sensing that does not require any information about the local infinite-dimensional fluctuations of the signal.