5G est prévu pour s'attaquer, en plus d'une augmentation considérable du volume de trafic, la tâche de connecter des milliards d'appareils avec des exigences de service hétérogènes. Afin de relever les défis de la 5G, nous préconisons une utilisation plus efficace des informations disponibles, avec plus de sensibilisation par rapport aux services et aux utilisateurs, et une expansion de l'intelligence du RAN. En particulier, nous nous concentrons sur deux activateurs clés de la 5G, à savoir le MIMO massif et la mise en cache proactive. Dans le troisième chapitre, nous nous concentrons sur la problématique de l'acquisition de CSI dans MIMO massif en TDD. Pour ce faire, nous proposons de nouveaux schémas de regroupement spatial tels que, dans chaque groupe, une couverture maximale de la base spatiale du signal avec un chevauchement minimal entre les signatures spatiales des utilisateurs est obtenue. Ce dernier permet d'augmenter la densité de connexion tout en améliorant l'efficacité spectrale. MIMO massif en TDD est également au centre du quatrième chapitre. Dans ce cas, en se basant sur les différents taux de vieillissement des canaux sans fil, la périodicité d'estimation de CSI est supplémentaire. Nous le faisons en proposant un exploité comme un degré de liberté supplémentaire. Nous le faisons en proposant une adaptation dynamique de la trame TDD en fonction des temps de cohérence des canaux hétérogènes. Les stations de bases MIMO massif sont capables d'apprendre la meilleure politique d’estimation sur le uplink pour de longues périodes. Comme les changements de canaux résultent principalement de la mobilité de l'appareil, la connaissance de l'emplacement est également incluse dans le processus d'apprentissage. Le problème de planification qui en a résulté a été modélisé comme un POMDP à deux échelles temporelles et des algorithmes efficaces à faible complexité ont été fournis pour le résoudre. Le cinquième chapitre met l'accent sur la mise en cache proactive. Nous nous concentrons sur l'amélioration de l'efficacité énergétique des réseaux dotes de mise en cache en exploitant la corrélation dans les modèles de trafic en plus de la répartition spatiale des demandes. Nous proposons un cadre qui établit un compromis optimal entre la complexité et la véracité dans la modélisation du comportement des utilisateurs grâce à la classification adaptative basée sur la popularité du contenu. Il simplifie également le problème du placement de contenu, ce qui se traduit par un cadre d'allocation de contenu rapidement adaptable et économe en énergie. / 5G is envisioned to tackle, in addition to a considerable increase in traffic volume, the task of connecting billions of devices with heterogeneous service requirements. In order to address the challenges of 5G, we advocate a more efficient use of the available information, with more service and user awareness, and an expansion of the RAN intelligence. In particular, we focus on two key enablers of 5G, namely massive MIMO and proactive caching. In the third chapter, we focus on addressing the bottleneck of CSI acquisition in TDD Massive MIMO. In order to do so, we propose novel spatial grouping schemes such that, in each group, maximum coverage of the signal’s spatial basis with minimum overlapping between user spatial signatures is achieved. The latter enables to increase connection density while improving spectral efficiency. TDD Massive MIMO is also the focus of the fourth chapter. Therein, based on the different rates of wireless channels aging, CSI estimation periodicity is exploited as an additional DoF. We do so by proposing a dynamic adaptation of the TDD frame based on the heterogeneous channels coherence times. The Massive MIMO BSs are enabled to learn the best uplink training policy for long periods. Since channel changes result primarily from device mobility, location awareness is also included in the learning process. The resulting planning problem was modeled as a two-time scale POMDP and efficient low complexity algorithms were provided to solve it. The fifth chapter focuses on proactive caching. We focus on improving the energy efficiency of cache-enabled networks by exploiting the correlation in traffic patterns in addition to the spatial repartition of requests. We propose a framework that strikes the optimal trade-off between complexity and truthfulness in user behavior modeling through adaptive content popularity-based clustering. It also simplifies the problem of content placement, which results in a rapidly adaptable and energy efficient content allocation framework.

As the world becomes more globalised, user equipment such as smartphones and Internet of Things devices require increasingly more data, which increases the demand for wireless data traffic. Hence, the acceleration of next-generational networks (5G and beyond) focuses mainly on increasing the bitrate and decreasing the latency. A crucial technology for 5G and beyond is the massive MIMO. In a massive MIMO system, a detector processes the received signals from multiple antennas to decode the transmitted data and extract useful information. This has been implemented in many ways, and one of the most used algorithms is the Zero Forcing (ZF) algorithm. This thesis presents a novel parallel design to accelerate the ZF algorithm using the Cholesky decomposition. This is implemented on a GPU, written in the CUDA programming language, and compared to the existing state-of-the-art implementations regarding latency and throughput. The implementation is also validated from a MATLAB implementation. This research demonstrates promising performance using GPUs for massive MIMO detection algorithms. Our approach achieves a significant speedup factor of 350 in comparison to a serial version of the implementation. The throughput achieved is 160 times greater than a comparable GPU-based approach. Despite this, our approach reaches a 2.4 times lower throughput than a solution that employed application-specific hardware. Given the promising results, we advocate for continued research in this area to further optimise detection algorithms and enhance their performance on GPUs, to potentially achieve even higher throughput and lower latency. / <p>Our examiner Mahdi wants to wait six months before the thesis is published. </p>

Les futurs systèmes de communication mobile sont caractérisés par un déploiement de plus en plus dense de différents types de points d'accès sans fil. Afin d’atténuer les interférences dans ces systèmes, les techniques aux entrées multiples-sorties multiples (MIMO) ainsi que la coopération entre les émetteurs et/ou les récepteurs sont nécessaires. Les systèmes de communication mobile en deviennent plus complexes, ce qui impose une évolution des outils mathématiques permettant leur analyse. Ceux-ci doivent être capables de prendre en compte les caractéristiques les plus importantes du système, telles que l'affaiblissement de propagation, les interférences et l'information imparfaite d'état du canal. Le but de cette thèse est de développer de tels outils basés sur la théorie des grandes matrices aléatoires et de démontrer leur utilité à l'aide de plusieurs applications pratiques, telles que l'analyse des performances des systèmes « network MIMO » et des systèmes MIMO à grande échelle, la conception de détecteurs de faible complexité à expansion polynomiale, l'étude des techniques de précodage unitaire aléatoire, ainsi que l'analyse de canaux à relais multiples et de canaux à double diffusion. En résumé, les méthodes développées dans ce travail fournissent des approximations déterministes de la performance du système qui deviennent exactes en régime asymptotique avec un nombre illimité d'émetteurs et de récepteurs. Cette approche conduit souvent à des approximations de la performance du système étonnamment simples et précises et permet de tirer d’importantes conclusions sur les paramètres les plus pertinents. / Advanced mobile communication systems are characterized by a dense deployment of different types of wireless access points. Since these systems are primarily limited by interference, multiple-input multiple-output (MIMO) techniques as well as coordinated transmission and detection schemes are necessary to mitigate this limitation. Thus, mobile communication systems become more complex which requires that also the mathematical tools for their theoretical analysis must evolve. These must be able to take the most important system characteristics into account, such as fading, path loss, and interference. The aim of this thesis is to develop such tools based on large random matrix theory and to demonstrate their usefulness with the help of several practical applications, such as the performance analysis of network MIMO and large-scale MIMO systems, the design of low-complexity polynomial expansion detectors, and the study of random beamforming techniques as well as multi-hop relay and double-scattering channels. The methods developed in this work provide deterministic approximations of the system performance which become arbitrarily tight in the large system regime with an unlimited number of transmitting and receiving devices. This leads in many cases to simple and close approximations of the finite-size system performance and allows one to draw relevant conclusions about the most significant parameters. One can think of these methods as a way to provide a deterministic abstraction of the physical layer which substantially reduces the system complexity. Due to this complexity reduction, it is possible to carry out a system optimization which would be otherwise intractable.

This work deals with the design of MT transmit, MR receive antenna MIMO (Multiple Input Multiple Output) communication system where the transmitter performs a linear operation on data. This linear precoding model includes systems which involve signal shaping for achieving higher data rates, uncoded MIMO Multicarrier and Single-Carrier systems and, the more recent, MIMO-OFDM (Orthogonal Frequency Division Multiplexing) systems employing full diversity Space-Frequency codes. The objective of this work is to design diversity centric and rate centric linear precoded MIMO systems whose performance is better than the existing designs. In particular, we consider MIMO-OFDM systems, Zero Padded MIMO systems and MIMO systems with limited rate feedback. Design of full diversity MIMO-OFDM systems of rate symbol per channel use (1 s/ pcu) : In literature, MIMO-OFDM systems exploiting full diversity at a rate of 1 s/ pcu are based on a few specific Space-Frequency (SF)/ Space-Time-Frequency (STF) codes. In this work, we devise a general parameterized framework for the design of MIMO-OFDM systems employing full diversity STF codes of rate 1 s/ pcu. This framework unifies all existing designs and provides tools for the design of new systems with interesting properties and superior performance. Apart from rate and diversity, the parameters of the framework are designed for a low complexity receiver. The parameters of the framework usually depend on the channel characteristics (number of multipath, Delay Profile (DP)). When channel characteristics are available at the transmitter, a procedure to optimize the performance of STF codes is provided. The resulting codes are termed as DP optimized codes. Designs obtained using the optimization are illustrated and their performance is shown to be better than the existing ones. To cater to the scenarios where channel characteristics are not available at the transmitter, a complete characterization of a class of full diversity DP Independent (DPI) STF codes is provided. These codes exploit full diversity on channels with a given number of multipath irrespective of their characteristics. Design of DP optimized STF codes and DPI codes from the same framework highlights the flexibility of the framework. Design of Zero Padded (ZP) MIMO systems : While the MIMO-OFDM transmitter needs to precode data for exploiting channel induced multipath diversity, ZP MIMO systems with ML receivers are shown to exploit multipath diversity without any precoding. However, the receiver complexity of such systems is enormous and hence a study ZP MIMO system with linear receivers is undertaken. Central to this study involves devising low complexity receivers and deriving the diversity gain of linear receivers. Reduced complexity receiver implementations are presented for two classes of precoding schemes. An upper bound on the diversity gain of linear receivers is evaluated for certain precoding schemes. For uncoded systems operating on a channel of length L, this bound is shown to be MRL_MT +1 for uncoded transmissions, i.e, such systems tend to exploit receiver and multipath diversities. On the other hand, MIMO-OFDM systems designed earlier have to trade diversity with receiver complexity. These observations motivate us to use ZP MIMO systems with linear receivers for channels with large delay spread when receiver complexity is at a premium. Design examples highlighting the attractiveness of ZP systems when employed on channels with large delay spread are also presented. Efficient design of MIMO systems with limited feedback : Literature presents a number of works that consider the design of MIMO systems with partial feedback. The works that consider feedback of complete CSI, however, do not provide for an efficient system design. In this work, we consider two schemes, Correlation matrix feedback and Channel information feedback that convey complete CSI to the transmitter. This CSI is perturbed due to various impairments. A perturbation analysis is carried out to study the variations in mutual information for each of the proposed schemes. For ergodic channels, this analysis is used to design a MIMO system with a limited rate feedback. Using a codebook based approach, vector quantizers are designed to minimize the loss in ergodic capacity for each of the proposed schemes. The efficiency of the design stems from the ability to obtain closed-form expression for centroids during the iterative vector quantizer design. The performance of designed vector quantizers compare favorably with the existing designs. The vector quantizer design for channel information feedback is robust in the sense that the same codebook can be used across all operating SNR. Use of vector quantizers for improving the outage performance is also presented.

[EN] Multiple-Input Multiple-Output (MIMO) technology in Digital Terrestrial Television (DTT) networks has the potential to increase the spectral efficiency and improve network coverage to cope with the competition of limited spectrum use (e.g., assignment of digital dividend and spectrum demands of mobile broadband), the appearance of new high data rate services (e.g., ultra-high definition TV - UHDTV), and the ubiquity of the content (e.g., fixed, portable, and mobile). It is widely recognised that MIMO can provide multiple benefits such as additional receive power due to array gain, higher resilience against signal outages due to spatial diversity, and higher data rates due to the spatial multiplexing gain of the MIMO channel. These benefits can be achieved without additional transmit power nor additional bandwidth, but normally come at the expense of a higher system complexity at the transmitter and receiver ends. The final system performance gains due to the use of MIMO directly depend on physical characteristics of the propagation environment such as spatial correlation, antenna orientation, and/or power imbalances experienced at the transmit aerials. Additionally, due to complexity constraints and finite-precision arithmetic at the receivers, it is crucial for the overall system performance to carefully design specific signal processing algorithms. This dissertation focuses on transmit and received signal processing for DTT systems using MIMO-BICM (Bit-Interleaved Coded Modulation) without feedback channel to the transmitter from the receiver terminals. At the transmitter side, this thesis presents investigations on MIMO precoding in DTT systems to overcome system degradations due to different channel conditions. At the receiver side, the focus is given on design and evaluation of practical MIMO-BICM receivers based on quantized information and its impact in both the in-chip memory size and system performance. These investigations are carried within the standardization process of DVB-NGH (Digital Video Broadcasting - Next Generation Handheld) the handheld evolution of DVB-T2 (Terrestrial - Second Generation), and ATSC 3.0 (Advanced Television Systems Committee - Third Generation), which incorporate MIMO-BICM as key technology to overcome the Shannon limit of single antenna communications. Nonetheless, this dissertation employs a generic approach in the design, analysis and evaluations, hence, the results and ideas can be applied to other wireless broadcast communication systems using MIMO-BICM. / [ES] La tecnología de múltiples entradas y múltiples salidas (MIMO) en redes de Televisión Digital Terrestre (TDT) tiene el potencial de incrementar la eficiencia espectral y mejorar la cobertura de red para afrontar las demandas de uso del escaso espectro electromagnético (e.g., designación del dividendo digital y la demanda de espectro por parte de las redes de comunicaciones móviles), la aparición de nuevos contenidos de alta tasa de datos (e.g., ultra-high definition TV - UHDTV) y la ubicuidad del contenido (e.g., fijo, portable y móvil). Es ampliamente reconocido que MIMO puede proporcionar múltiples beneficios como: potencia recibida adicional gracias a las ganancias de array, mayor robustez contra desvanecimientos de la señal gracias a la diversidad espacial y mayores tasas de transmisión gracias a la ganancia por multiplexado del canal MIMO. Estos beneficios se pueden conseguir sin incrementar la potencia transmitida ni el ancho de banda, pero normalmente se obtienen a expensas de una mayor complejidad del sistema tanto en el transmisor como en el receptor. Las ganancias de rendimiento finales debido al uso de MIMO dependen directamente de las características físicas del entorno de propagación como: la correlación entre los canales espaciales, la orientación de las antenas y/o los desbalances de potencia sufridos en las antenas transmisoras. Adicionalmente, debido a restricciones en la complejidad y aritmética de precisión finita en los receptores, es fundamental para el rendimiento global del sistema un diseño cuidadoso de algoritmos específicos de procesado de señal. Esta tesis doctoral se centra en el procesado de señal, tanto en el transmisor como en el receptor, para sistemas TDT que implementan MIMO-BICM (Bit-Interleaved Coded Modulation) sin canal de retorno hacia el transmisor desde los receptores. En el transmisor esta tesis presenta investigaciones en precoding MIMO en sistemas TDT para superar las degradaciones del sistema debidas a diferentes condiciones del canal. En el receptor se presta especial atención al diseño y evaluación de receptores prácticos MIMO-BICM basados en información cuantificada y a su impacto tanto en la memoria del chip como en el rendimiento del sistema. Estas investigaciones se llevan a cabo en el contexto de estandarización de DVB-NGH (Digital Video Broadcasting - Next Generation Handheld), la evolución portátil de DVB-T2 (Second Generation Terrestrial), y ATSC 3.0 (Advanced Television Systems Commitee - Third Generation) que incorporan MIMO-BICM como clave tecnológica para superar el límite de Shannon para comunicaciones con una única antena. No obstante, esta tesis doctoral emplea un método genérico tanto para el diseño, análisis y evaluación, por lo que los resultados e ideas pueden ser aplicados a otros sistemas de comunicación inalámbricos que empleen MIMO-BICM. / [CA] La tecnologia de múltiples entrades i múltiples eixides (MIMO) en xarxes de Televisió Digital Terrestre (TDT) té el potencial d'incrementar l'eficiència espectral i millorar la cobertura de xarxa per a afrontar les demandes d'ús de l'escàs espectre electromagnètic (e.g., designació del dividend digital i la demanda d'espectre per part de les xarxes de comunicacions mòbils), l'aparició de nous continguts d'alta taxa de dades (e.g., ultra-high deffinition TV - UHDTV) i la ubiqüitat del contingut (e.g., fix, portàtil i mòbil). És àmpliament reconegut que MIMO pot proporcionar múltiples beneficis com: potència rebuda addicional gràcies als guanys de array, major robustesa contra esvaïments del senyal gràcies a la diversitat espacial i majors taxes de transmissió gràcies al guany per multiplexat del canal MIMO. Aquests beneficis es poden aconseguir sense incrementar la potència transmesa ni l'ample de banda, però normalment s'obtenen a costa d'una major complexitat del sistema tant en el transmissor com en el receptor. Els guanys de rendiment finals a causa de l'ús de MIMO depenen directament de les característiques físiques de l'entorn de propagació com: la correlació entre els canals espacials, l'orientació de les antenes, i/o els desequilibris de potència patits en les antenes transmissores. Addicionalment, a causa de restriccions en la complexitat i aritmètica de precisió finita en els receptors, és fonamental per al rendiment global del sistema un disseny acurat d'algorismes específics de processament de senyal. Aquesta tesi doctoral se centra en el processament de senyal tant en el transmissor com en el receptor per a sistemes TDT que implementen MIMO-BICM (Bit-Interleaved Coded Modulation) sense canal de tornada cap al transmissor des dels receptors. En el transmissor aquesta tesi presenta recerques en precoding MIMO en sistemes TDT per a superar les degradacions del sistema degudes a diferents condicions del canal. En el receptor es presta especial atenció al disseny i avaluació de receptors pràctics MIMO-BICM basats en informació quantificada i al seu impacte tant en la memòria del xip com en el rendiment del sistema. Aquestes recerques es duen a terme en el context d'estandardització de DVB-NGH (Digital Video Broadcasting - Next Generation Handheld), l'evolució portàtil de DVB-T2 (Second Generation Terrestrial), i ATSC 3.0 (Advanced Television Systems Commitee - Third Generation) que incorporen MIMO-BICM com a clau tecnològica per a superar el límit de Shannon per a comunicacions amb una única antena. No obstant açò, aquesta tesi doctoral empra un mètode genèric tant per al disseny, anàlisi i avaluació, per la qual cosa els resultats i idees poden ser aplicats a altres sistemes de comunicació sense fils que empren MIMO-BICM. / Vargas Paredero, DE. (2016). Transmit and Receive Signal Processing for MIMO Terrestrial Broadcast Systems [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/66081 / Premios Extraordinarios de tesis doctorales

Approved for public release, distribution is unlimited / This thesis investigates the simulation performance of multiple-input multiple-output (MIMO) systems utilizing Alamoutibased space-time block coding (STBC) technique. The MIMO communication systems using STBC technique employing both single- carrier modulation and orthogonal frequency division multiplexing (OFDM) are simulated in Matlab. The physical layer part of the IEEE 802.16a standard is used in constructing the simulated OFDM schemes. Stanford University Interim (SUI) channel models are selected for the wireless channel in the simulation process. The performance results of the simulated MIMO systems are compared to those of conventional single antenna systems. / Lieutenant Junior Grade, Turkish Navy

The integration of Multiple Input Multiple Output (MIMO) and Orthogonal Frequency Division Multiplexing (OFDM) techniques has become a preferred solution for the high rate wireless technologies due to its high spectral efficiency, robustness to frequency selective fading, increased diversity gain, and enhanced system capacity. The main drawback of OFDM-based systems is their susceptibility to impairments such as Carrier Frequency Offset (CFO), Sampling Frequency Offset (SFO), Symbol Timing Error (STE), Phase Noise (PHN), and fading channel. These impairments, if not properly estimated and compensated, degrade the performance of the OFDM-based systems In this thesis, a system model for MIMO-OFDM that takes into account the effects of all these impairments is formulated. Using this system model, we de-rive Cramer-Rao Lower Bounds (CRLBs) for the joint estimation of deterministic impairments in MIMO-OFDM system, which show the coupling effect among different impairments and the significance of the joint estimation. Also, Bayesian CRLBs for the joint estimation of random impairments in OFDM system are derived. Similarly, we derive Hybrid CRLBs for the joint estimation of random and deterministic impairments in OFDM system, which show the significance of using Bayesian approach in estimation. Further, we investigate different algorithms for the joint estimation of all impairments in OFDM-based system. Maximum Likelihood (ML) algorithms and its low complexity variants, for the joint estimation of CFO, SFO, STE, and channel in MIMO-OFDM system, are proposed. We propose a low complexity ML algorithm which uses Compressed Sensing (CS) based channel estimation method in a sparse fading sce-nario, where the received samples used for estimation are less than that required for a Least Squares (LS) or Maximum a posteriori (MAP) based estimation. Also, we propose MAP algorithms for the joint estimation of the random impairments, PHN and channel, utilizing their statistical knowledge which is known a priori. Joint estimation algorithms for SFO and channel in OFDM system, using Bayesian framework, are also proposed in this thesis. The performance of the estimation methods is studied through simulations and numerical results show that the performance of the proposed algorithms is better than existing algorithms and is closer to the derived CRLBs.

In wireless communication systems, the use of multiple antennas, also known as Multiple-Input Multiple-Output(MIMO) communications, is now a widely accepted and important technology for improving their reliability and throughput performance. However, in order to achieve the performance gains predicted by the theory, the transmitter and receiver need to have accurate and up-to-date Channel State Information(CSI) to overcome the vagaries of the fading environment. Traditionally, the CSI is obtained at the receiver by sending a known training sequence in the forward-link direction. This CSI has to be conveyed to the transmitter via a low-rate, low latency and noisy feedback channel in the reverse-link direction. This thesis addresses three key challenges in sending the CSI to the transmitter of a MIMO communication system over the reverse-link channel, and provides novel solutions to them. The first issue is that the available CSI at the receiver has to be quantized to a finite number of bits, sent over a noisy feedback channel, reconstructed at the transmitter, and used by the transmitter for precoding its data symbols. In particular, the CSI quantization technique has to be resilient to errors introduced by the noisy reverse-link channel, and it is of interest to design computationally simple, linear filters to mitigate these errors. The second issue addressed is the design of low latency and low decoding complexity error correction codes to provide protection against fading conditions and noise in the reverse-link channel. The third issue is to improve the resilience of the reverse-link channel to fading. The solution to the first problem is obtained by proposing two classes of receive filtering techniques, where the output of the source decoder is passed through a filter designed to reduce the overall distortion including the effect of the channel noise. This work combines the high resolution quantization theory and the optimal Minimum Mean Square Error(MMSE) filtering formulation to analyze, and optimize, the total end-to-end distortion. As a result, analytical expressions for the linear receive filters are obtained that minimize the total end-to-end distortion, given the quantization scheme and source(channel state) distribution. The solution to the second problem is obtained by proposing a new family of error correction codes, termed trellis coded block codes, where a trellis code and block code are concatenated in order to provide good coding gain as well as low latency and low complexity decoding. This code construction is made possible due to the existence of a uniform partitioning of linear block codes. The solution to the third problem is obtained by proposing three novel transmit precoding methods that are applicable to time-division-duplex systems, where the channel reciprocity can be exploited in designing the precoding scheme. The proposed precoding methods convert the Rayleigh fading MIMO channel into parallel Additive White Gaussian Noise(AWGN) channels with fixed gain, while satisfying an average transmit power constraint. Moreover, the receiver does not need to have knowledge of the CSI in order to decode the received data. These precoding methods are also extended to Rayleigh fading multi-user MIMO channels. Finally, all the above methods are applied to the problem of designing a low-rate, low-latency code for the noisy and fading reverse-link channel that is used for sending the CSI. Simulation results are provided to demonstrate the improvement in the forward-link data rate due to the proposed methods. Note that, although the three solutions are presented in the context of CSI feedback in MIMO communications, their development is fairly general in nature, and, consequently, the solutions are potentially applicable in other communication systems also.

Cette thèse concerne les codes utilisés pour les télécommunications sans-fil multi-antennes. Les résultats portent notamment sur des constructions explicites ainsi que sur des bornes numériques et théoriques pour les cardinaux de ces codes. Le premier chapitre introduit brièvement les différents contextes multi-antennes et les modélisations qui leur sont associées. Les chapitres 2,3 et 4 traitent respectivement des codes dans les espaces grassmanniens, des codes dans les matrices unitaires et des codes dans les algèbres à division. / This thesis deals with codes used for multi-antennas wireless telecommunications. The results concern explicit constructions and bounds on the cardinalities of such codes (analytical and numerical bounds) . The first chapter introduce various modelisations of the multi-antennas wireless system and the related mathematical problems. Chapters 2,3,4 deal respectively with codes in Grassmannian spaces, code in unitary matrices and code in division algebras.

La synchronisation temporelle des systèmes MIMO a été abondamment étudiée dans les quinze dernières années, mais la plupart des techniques existantes supposent que le bruit est blanc temporellement et spatialement, ce qui ne permet pas de modéliser la présence d'interférence. Nous considérons donc le cas de bruits blancs temporellement mais pas spatialement, dont la matrice de covariance spatiale est inconnue. En formulant le problème de l'estimation de l'instant de synchronisation comme un test d'hypothèses, nous aboutissons au test du rapport de vraisemblance généralisé (GLRT) qui donne lieu à la comparaison avec un seuil d'une statistique de test eta_GLRT. Cependant, pour des raisons de complexité, l'utilisation de cette statistique n'est pas toujours considérée comme réaliste. La première partie de ce travail a donc été consacrée à mettre en évidence des tests alternatifs moins complexes à mettre en œuvre, tout en ayant des performances similaires. Une analyse comparative exhaustive, prenant en considération le bruit et l'interférence, le type de canal, le nombre d'antennes en émission et en réception, et l'orthogonalité de la séquence de synchronisation est réalisée. Enfin, nous étudions le problème de l'optimisation du nombre d'antennes en émission K pour la synchronisation temporelle, montrant que pour un RSB élevé, les performances augmentent avec K dès que le produit de K avec le nombre d'antennes de réception M n'est pas supérieur à 8.Le deuxième aspect de ce travail est une analyse statistique de eta_GLRT dans le cas où la taille de la séquence d'apprentissage N est du même ordre de grandeur que M, ce qui conduit naturellement à étudier le comportement de eta_GLRT dans le régime asymptotique des grands systèmes M tend vers l'infini, N tend l'infini de telle sorte que M/N tende vers une constante non nulle. Nous considérons le cadre applicatif d'un système muni d'une unique antenne d'émission et d'un canal à trajets multiples, qui est formellement identique à celui d'un système MIMO dont le nombre d'antennes d'émissions correspondrait au nombre de trajets. Lorsque le nombre de trajets L est beaucoup plus faible que N et M, nous établissons que eta_GLRT a un comportement gaussien avec l'espérance asymptotique L log (1 / (1-M/N)) et la variance (L/N)*(M/N)/(1-M/N). Ceci est en contraste avec le régime asymptotique standard quand N tend vers l'infini et M et L fixe où eta_GLRT a un comportement chi2. Sous l'hypothèse H_1, eta_GLRT a aussi un comportement gaussien. Nous considérons également le cas où le nombre de trajets L tend vers l'infini à la même vitesse que M et N. Nous utilisons des résultats connus concernant le comportement des statistiques linéaires des valeurs propres des grandes F matrices, et déduisons que dans le régime où L,M,N tendent vers l'infini à la même vitesse, eta_GLRT a encore un comportement gaussien sous H_0, mais avec une espérance et variance différentes. L'analyse de eta_GLRT sous H_1 lorsque L,M,L convergent vers l'infini nécessite l'établissement d'un théorème central limite pour les statistiques linéaires des valeurs propres de matrices F de moyennes non-nulles, une tâche difficile. Motivé par les résultats obtenus dans le cas où L reste fini, nous proposons d'approximer la distribution asymptotique par une distribution gaussienne dont l'espérance et la variance sont la somme de l'espérance et la variance asymptotique sous H_0quand L tend vers l'infini avec l'espérance et la variance asymptotique sous H_1 dans le régime classique N tend vers l'infini et M fixé. Des simulations numériques permettent de comparer les courbes ROC des différents approximant avec des courbes ROC empiriques. Les résultats montrent que nos approximant de grandes dimensions fournissent de meilleurs résultats quand M/N augmente, tout en permettant de capturer la performance réelle pour les petites valeurs de M/N / Time synchronization of MIMO systems have been strongly studied in the last fifteen years, but most of the existing techniques assume a spatially and temporally white noise, which does not allow modeling the presence of interference. We consider thus a temporally white but spatially colored noise, with an unknown covariance matrix. Formulating the estimation problem as a hypothesis testing problem, we obtain a Generalized likelihood ratio test (GLRT), which gives us a synchronization statistics eta_GLRT. However, for complexity reasons, it is not always considered realistic for practical situations. A part of this work has thus been devoted to showing that there exist non-GLRT statistics that are less complex to implement than theet a_GLRT, while having similar performance. Furthermore, we perform a comparative parameter analysis, taking into consideration the noise type, channel type, the number of transmit and receive antennas, and the orthogonality of the synchronization sequence. Lastly, the problem of optimization of the number of transmit antennas K for time synchronization has been investigated. showing, for high SNR, increasing performance with K as long as the product KM is not larger than 8, where M is the number of receive antennas. The second aspect of MIMO synchronization studied in thesis is asymptotic analysis of the same GLRT, but for large M. In this context, the synchronization sequence length N is the same order of magnitude as M, and this leads us naturally to the study of the the behavior of eta_GLRT in the asymptotic regime where M,N go towards infinity such that M/N go towards a non-zero constant. We consider the case of a single transmit antenna in a multi-path channel, which formally is equivalent to the MIMO system where the transmit antennas correspond to the number of paths. We address the case When the number of paths L does not scale with M and N, we establish that eta_GLRT has a Gaussian behavior with asymptotic mean L log (1/ (1 - M/N))and variance (L/N)*(M/N)/(1-M/N).This is in contrast with the standard asymptotic regime N goes to infinity and M fixed where eta_GLRT has a chi^2 behaviour. Under hypothesis H_1, eta_GLRT still has a Gaussian behaviour. The corresponding asymptotic mean and variance are obtained as the sum of the asymptotic mean and variance in the standard regime N goes to infinity and M fixed, and L log(1/(1-/M/N))L log (1 / (1-M/N)) and (L/N)*(M/N)/(1-M/N)respectively, i.e. the asymptotic mean and variance under H_0.We also consider the case where the number of paths L converges towards infinity at the same rate as M and N. Using known results of concerning the behaviour of linear statistics of the eigenvalues of large F-matrices, we deduce that in the regime where L,M,N converge to infinity at the same rate, eta_GLRT still has a Gaussian behaviour under H_0, but with a different mean and variance. The analysis of eta_GLRT under H_1 whenL,M,N converge to infinity needs to establish a central limit theorem for linear statistics of the eigenvalues of large non zero-mean F-matrices, a difficult ask. Motivated by the results obtained in the case where L remains finite, we propose to approximate the asymptotic distribution of eta_GLRT by a Gaussian distribution whose mean and variance are the sum of the asymptotic mean and variance under H_0when L goes to infinity with the asymptotic mean and variance under H_1 in the standard regime N goes to infinity and M fixed. Numerical simulations allow to compare the ROC curves obtained with the different approximations with the empirical ROC curves. The results show that the large-system approximations provide better results when M/N increases, while also allowing to capture the actual performance for small values of M/N