Ce travail s’intéresse aux transmissions ultralarge bande (ULB) dans les réseaux sans fils. La diversité spatiale est introduite par l’utilisation du système multiple-input multiple-output (MIMO) comme une technique efficace pour lutter contre l’évanouissement dû aux trajets multiples dans les communications sans fils. Mais, souvent l’intégration d’antennes multiples au niveau de l’émetteur ou du récepteur est coûteuse. Comme alternative, nous proposons d’utiliser la diversité coopérative qui garantit des gains de diversité spatiale en exploitant les techniques MIMO traditionnelles sans avoir besoin d’antennes multiples. L’objectif est d’introduire la diversité coopérative aux systèmes de transmission ULB. Nous considérons deux techniques d’accès multiple avec des schémas de modulation différents (time hopping pulse position modulation TH-PPM et direct sequence binary phase shift keying DSBPSK) avec le protocole de coopération decode-and-forward (DF). Nous utilisons le récepteur Rake afin d’exploiter la diversité de trajet multiple et analysons les statistiques de variable de décision à la sortie de ce récepteur. Nous présentons des résultats de simulation de la performance en termes de taux d’erreur binaire (TER) du système étudié sous différents canaux UWB compte tenu de la norme IEEE 802.15.4a. Ces résultats montrent que la coopération avec des relais améliore significativement les performances de transmission ULB, et que le gain de diversité augmente proportionnellement avec le nombre de relais. En présence d’IAM, la performance du système se dégrade de manière significative, mais l’avantage de la coopération est encore modérément efficace. La performance dans ce cas est limitée en termes de diversité achevée parce que le canal entre la source et le relais en présence d’IAM devient moins favorable. C’est pourquoi nous proposons d’utiliser la technique de sélection d’antenne au relais afin d’améliorer la fiabilité du canal source-relais. Cette solution permet d’améliorer la performance grâce au gain de la diversité d’antennes multiples disponibles au relais toute en n’utilisant qu’une seule chaîne radiofréquence (RF), qui conduit à une réduction des coûts et de la complexité. / This work focuses on the ultra wideband (UWB) transmission in wireless networks. Spatial diversity is introduced by the use of multiple-input multiple-output (MIMO) system as an effective technique to overcome multipath fading in wireless communications. But the integration of multiple antennas at the transmitter or receiver is often costly. As an alternative, we propose to use the cooperative diversity that provides spatial diversity gains by exploiting the traditional MIMO techniques without the need for multiple antennas. The objective is to introduce cooperative diversity to UWB transmission systems. We consider two multiple access techniques with different modulation schemes (time hopping pulse position modulation TH-PPM and direct sequence binary Phase Shift Keying DS-BPSK) with the cooperation protocol decode-and-forward (DF). We use the Rake receiver to exploit multipath diversity and analyze the decision variable statistics at the output of the receiver. We present simulation results of the BER performance of the proposed system under different UWB channel given the IEEE 802.15.4a standard. Our results show that the cooperation with the relay significantly improves the performance of UWB transmission, and that the diversity gain increases with the number of relays. In the presence of MAI, the overall system performance degrades significantly, but the benefit of cooperation is still moderately effective. The performance in this case is limited in terms of attainable diversity that the source-relay link becomes worse when MAI is present. That is why we propose to use antenna selection at the relay receiver in order to improve the reliability of the source-relay link. This solution is shown to improve the performance by exploiting the diversity of the available antennas at the relay, while using a single Radio Frequency (RF) chains. This leads to reduced cost and complexity.

This thesis treats of channel models for polarized multi-antenna wireless systems. Polarized multi-antenna systems are systems that use perpendicularly polarized, co-located antennas at the base station and at the mobile terminal, in order to benefit from the so-called polarization diversity. Such systems benefit from the advantages of MIMO systems while still maintaining a compact equipment size. Two models will be presented in this thesis. The first one is the Polarized-Input Polarized-Output (PIPO) channel model, the second one is the Polarized-Diffuse-Directional channel model. The PIPO model is a statistical channel model for tri-polarized to tri-polarized communication systems. A tri-polarized antenna system is a tranceiver using three perpendicular antennas. The aim of the PIPO channel model is to have a model that has a simple mathematical structure, so it can be used for solving precoding equations or capacity calculations. Although the PIPO model has a very simple structure, it takes the following parameters into account: coherent channel component, cross-polar channel power imbalance, inter-channel correlation, short- and long-scale time variance. Experimental measurements are used to parameterize the model. It is shown how the model parameters are extracted from experimental measurements, and the results are analyzed to allow further simplification of the model. The PDD model, on the other hand, is a geometry-based stochastic channel model. It models the channel as a sum of clusters, where each cluster consists of groups of multipath components (MPCs). The PDD model includes two novelties that will be developed in detail in this thesis. - The model considers polarization on a per-cluster basis. This permits to have a more accurate description of the polar-angular spectrum. - The diffuse multipath component (DMC) is included by considering a diffuse component for each cluster. The diffuse cluster component is then modeled as the sum of a set of diffuse MPCs. The model is specified in detail, and it is shown how the model can be generated. Experimental measurements were carried out to parameterize the model. A new extraction technique for extracting the specular-diffuse clusters from the measurements is proposed. This technique is based on joint clustering of the specular MPCs and the bins of the diffuse component. The experimental results are analyzed, and superimposed with environment information to gain further insight into the physical aspects of clustered propagation. Finally, both models are validated. Several validation metrics are introduced, and their pertinence in the context of polarized MIMO systems is highlighted. Both models are successfully validated, and the advantages and limitations of each models are investigated. Cette thèse traite des modèles de canal pour systèmes sans-fils multi-antennes polarisés. Des systèmes multi-antennes polarisés sont des systèmes qui utilisent des antennes polarisées perpendiculairement co-localisées à la station de base et au terminal mobile, dans le but de bénéficier de la diversité de polarisation. De tels systèmes peuvent bénéficier des avantages des systèmes MIMO tout en diminuant l'encombrement des équipements. Deux modèles seront présentés dans cette thèse. Le premier est le modèle Polarized-Input Polarized-Output (PIPO), le second est le modèle Polarized-Diffuse-Directional (PDD). Le modèle PIPO est un modèle statistique pour des systèmes de communication tri-polaire à tri-polaire. Un système tri-polaire est un émetteur ou un récepteur qui utilise trois antennes perpendiculaires. Le but du modèle de canal PIPO est d'avoir un modèle qui a une structure mathématique simple, afin qu'il puisse être utilisé pour résoudre des équations de précodage ou des calculs de capacité. Malgré la structure simple du modèle PIPO, il tient compte des paramètres suivants: la composante cohérente du canal, les différences de puissance entre canaux cross-polaires, la corrélation entre canaux, les variations à courte et à longue échelle de temps. Des mesures expérimentales ont été réalisées afin de paramétriser le modèle. Les techniques pour extraire les paramètres du modèle des mesures expérimentales sont présentées, et les résultats sont analysés afin de permettre une simplification supplémentaire du modèle. Le modèle PDD, quant à lui, est un modèle de canal stochasique-géométrique. Il modélise le canal comme une somme de clusters, où chaque clusters est composé d'un groupe de chemins multi-trajets. Le modèle PDD inclut les deux nouveautés suivantes qui seront développées en détail dans cette thèse. - Le modèle considère une polarisation par cluster. Ceci permet d'avoir une description plus exacte du spectre angulaire-polaire. - La composante diffuse est prise en compte en incluant une composante diffuse pour chaque cluster. La composante diffuse d'un cluster est alors modelisée comme une somme de multi-trajets diffus. Le modèle est spécifié en détail, et il est présenté comment le modèle peut être généré. Des mesures expérimentales ont été faites afin de paramétriser le modèle. Une nouvelle technique d'extraction est proposée pour extraire les clusters spéculaires-diffus. Cette technique est basée sur le clustering conjoint des multi-trajets spéculaires et des "bins" de la composante diffuse. Les résultats expérimentaux sont analysés, et superposés avec l'information de l'environnement de mesure afin d'avoir une connaissance accrue des aspects physiques de la propagation par clusters. Finalement, les deux modèles sont validés. Plusieurs métriques de validations sont introduites, et leur pertinence dans le cadre des systèmes MIMO polarisés est mis en avant. Les deux modèles sont validés avec succès, et les avantages et limitations de chaque modèle sont investigués.

Employment of the multiple-antenna transmitters/receivers in communication systems is known as a promising solution to provide high-data-rate wireless links. In the multi-user environments, the problems of signaling and fairness for multi-antenna systems have emerged as challenging problems. This dissertation deals with these problems in several multi-antenna multi-user scenarios. In part one, a simple signaling method for the multi-antenna broadcast channels is proposed. This method reduces the MIMO broadcast system to a set of parallel channels. The proposed scheme has several desirable features in terms of: (i) accommodating users with different number of receive antennas, (ii) exploiting multi-user diversity, and (iii) requiring low feedback rate. The simulation results and analytical evaluations indicate that the achieved sum-rate is close to the sum-capacity of the underlying broadcast channel. In part two, for multiple-antenna systems with two transmitters and two receivers, a new non-cooperative scenario of data communication is studied in which each receiver receives data from both transmitters. For such a scenario, a signaling scheme is proposed which decomposes the system into two broadcast or two multi-access sub-channels. Using the decomposition scheme, it is shown that this signaling scenario outperforms the other known non-cooperative schemes in terms of the achievable multiplexing gain. In particular for some special cases, the achieved multiplexing gain is the same as the multiplexing gain of the system, where the full cooperation is provided between the transmitters and/or between the receivers. Part three investigates the problem of fairness for a class of systems for which a subset of the capacity region, which includes the sum-capacity facets, forms a polymatroid structure. The main purpose is to find a point on the sum-capacity facet which satisfies a notion of fairness among active users. This problem is addressed in the cases where the complexity of achieving interior points is not feasible, and where the complexity of achieving interior points is feasible. In part four, $K$-user memoryless interference channels are considered; where each receiver sequentially decodes the data of a subset of transmitters before it decodes the data of the designated transmitter. A greedy algorithm is developed to find the users which are decoded at each receiver and the corresponding decoding order such that the minimum rate of the users is maximized. It is proven that the proposed algorithm is optimal. The results of the parts three and four are presented for general channels which include the multiple-antenna systems as special cases.

Employment of the multiple-antenna transmitters/receivers in communication systems is known as a promising solution to provide high-data-rate wireless links. In the multi-user environments, the problems of signaling and fairness for multi-antenna systems have emerged as challenging problems. This dissertation deals with these problems in several multi-antenna multi-user scenarios. In part one, a simple signaling method for the multi-antenna broadcast channels is proposed. This method reduces the MIMO broadcast system to a set of parallel channels. The proposed scheme has several desirable features in terms of: (i) accommodating users with different number of receive antennas, (ii) exploiting multi-user diversity, and (iii) requiring low feedback rate. The simulation results and analytical evaluations indicate that the achieved sum-rate is close to the sum-capacity of the underlying broadcast channel. In part two, for multiple-antenna systems with two transmitters and two receivers, a new non-cooperative scenario of data communication is studied in which each receiver receives data from both transmitters. For such a scenario, a signaling scheme is proposed which decomposes the system into two broadcast or two multi-access sub-channels. Using the decomposition scheme, it is shown that this signaling scenario outperforms the other known non-cooperative schemes in terms of the achievable multiplexing gain. In particular for some special cases, the achieved multiplexing gain is the same as the multiplexing gain of the system, where the full cooperation is provided between the transmitters and/or between the receivers. Part three investigates the problem of fairness for a class of systems for which a subset of the capacity region, which includes the sum-capacity facets, forms a polymatroid structure. The main purpose is to find a point on the sum-capacity facet which satisfies a notion of fairness among active users. This problem is addressed in the cases where the complexity of achieving interior points is not feasible, and where the complexity of achieving interior points is feasible. In part four, $K$-user memoryless interference channels are considered; where each receiver sequentially decodes the data of a subset of transmitters before it decodes the data of the designated transmitter. A greedy algorithm is developed to find the users which are decoded at each receiver and the corresponding decoding order such that the minimum rate of the users is maximized. It is proven that the proposed algorithm is optimal. The results of the parts three and four are presented for general channels which include the multiple-antenna systems as special cases.

The theory of lattices --- a mathematical approach for representing infinite discrete points in Euclidean space, has become a powerful tool to analyze many point-to-point digital and wireless communication systems, particularly, communication systems that can be well-described by the linear Gaussian vector channel model. This is mainly due to the three facts about channel codes constructed using lattices: they have simple structure, their ability to achieve the fundamental limits (the capacity) of the channel, and most importantly, they can be decoded using efficient decoders called lattice decoders. Since its introduction to multiple-input multiple-output (MIMO) wireless communication systems, sphere decoders has become an attractive efficient implementation of lattice decoders, especially for small signal dimensions and/or moderate to large signal-to-noise ratios (SNRs). In the first part of this dissertation, we consider sphere decoding algorithms that describe lattice decoding. The exact complexity analysis of the basic sphere decoder for general space-time codes applied to MIMO wireless channel is known to be difficult. Characterizing and understanding the complexity distribution is important, especially when the sphere decoder is used under practically relevant runtime constraints. In this work, we shed the light on the (average) computational complexity of sphere decoding for the quasi-static, LAttice Space-Time (LAST) coded MIMO channel. Sphere decoders are only efficient in the high SNR regime and low signal dimensions, and exhibits exponential (average) complexity for low-to-moderate SNR and large signal dimensions. On the other extreme, linear and non-linear receivers such as minimum mean-square error (MMSE), and MMSE decision-feedback equalization (DFE) are considered attractive alternatives to sphere decoders in MIMO channels. Unfortunately, the very low decoding complexity advantage that these decoders can provide comes at the expense of poor performance, especially for large signal dimensions. The problem of designing low complexity receivers for the MIMO channel that achieve near-optimal performance is considered a challenging problem and has driven much research in the past years. The problem can solved through the use of lattice sequential decoding that is capable of bridging the gap between sphere decoders and low complexity linear decoders (e.g., MMSE-DFE decoder). In the second part of this thesis, the asymptotic performance of the lattice sequential decoder for LAST coded MIMO channel is analyzed. We determine the rates achievable by lattice coding and sequential decoding applied to such a channel. The diversity-multiplexing tradeoff under such a decoder is derived as a function of its parameter--- the bias term. In this work, we analyze both the computational complexity distribution and the average complexity of such a decoder in the high SNR regime. We show that there exists a cut-off multiplexing gain for which the average computational complexity of the decoder remains bounded. Our analysis reveals that there exists a finite probability that the number of computations performed by the decoder may become excessive, even at high SNR, during high channel noise. This probability is usually referred to as the probability of a decoding failure. Such probability limits the performance of the lattice sequential decoder, especially for a one-way communication system. For a two-way communication system, such as in MIMO Automatic Repeat reQuest (ARQ) system, the feedback channel can be used to eliminate the decoding failure probability. In this work, we modify the lattice sequential decoder for the MIMO ARQ channel, to predict in advance the occurrence of decoding failure to avoid wasting the time trying to decode the message. This would result in a huge saving in decoding complexity. In particular, we will study the throughput-performance-complexity tradeoffs in sequential decoding algorithms and the effect of preprocessing and termination strategies. We show, analytically and via simulation, that using the lattice sequential decoder that implements a simple yet efficient time-out algorithm for joint error detection and correction, the optimal tradeoff of the MIMO ARQ channel can be achieved with significant reduction in decoding complexity.

Multiple-Input Multiple-Output (MIMO) systems are a pivotal solution for the significant enhancement of the band-limited wireless channels’ communication capacity. MIMO system is essentially a wireless system with multiple antennas at both the transmitter and receiver ends. Compared to the conventional wireless systems, the main advantages of the MIMO systems are the higher system capacity, more bit rates, more link reliability, and wider coverage area. All of these features are currently considered as crucial performance requirements in wireless communications. Additionally, the emerging new services in wireless applications have created a great motivation to utilize the MIMO systems to fulfil the demands these applications create. The MIMO systems can be combined with other intelligent techniques to achieve these benefits by employing a higher spectral efficiency. The MIMO system design is a multifaceted problem which needs both antenna considerations and baseband signal processing. The performance of the MIMO systems depends on the cross-correlation coefficients between the transmitted/received signals by different antenna elements. Therefore, the Electromagnetic (EM) characteristics of the antenna elements and wireless environment can significantly affect the MIMO system performance. Hence, it is important to include the EM properties of the antenna elements and the physical environment in the MIMO system design and optimizations. In this research, the MIMO system model and system performance are introduced, and the optimum MIMO antenna system is investigated and developed by considering the electromagnetic aspects within three inter-related topics: 1) Fast Numerical Analysis and Optimization of the MIMO Antenna Structures: An efficient and fast optimization method is proposed based on the reciprocity theorem along with the method of moment analysis to minimize the correlation among the received/transmitted signals in MIMO systems. In this method, the effects of the radio package (enclosure) on the MIMO system performance are also included. The proposed optimization method is used in a few practical examples to find the optimal positions and orientations of the antenna elements on the system enclosure in order to minimize the cross-correlation coefficients, leading to an efficient MIMO operation. 2) Analytical Electromagnetic-Theoretic Model for the MIMO Antenna Design: The first requirement for the MIMO antennas is to obtain orthogonal radiation modes in order to achieve uncorrelated signals. Since the Spherical Vector Waves (SVW) form a complete set of orthogonal Eigen-vector functions for the radiated electromagnetic fields, an analytical method based on the SVW approach is developed to excite the orthogonal SVWs to be used as the various orthogonal modes of the MIMO antenna systems. The analytic SVW approach is used to design spherical antennas and to investigate the orthogonality of the radiation modes in the planar antenna structures. 3) Systematic SVW Methodology for the MIMO Antenna Design: Based on the spherical vector waves, a generalized systematic method is proposed for the MIMO antenna design and analysis. The newly developed methodology not only leads to a systematic approach for designing MIMO antennas, but can also be used to determine the fundamental limits and degrees of freedom for designing the optimal antenna elements in terms of the given practical restrictions. The proposed method includes the EM aspects of the antenna elements and the physical environment in the MIMO antenna system, which will provide a general guideline for obtaining the optimal current sources to achieve the orthogonal MIMO modes. The proposed methodology can be employed for any arbitrary physical environment and multi-antenna structures. Without the loss of generality, the SVW approach is employed to design and analyze a few practical examples to show how effective it can be used for MIMO applications. In conclusion, this research addresses the electromagnetic aspects of the antenna analysis, design, and optimization for MIMO applications in a rigorous and systematic manner. Developing such a design and analysis tool significantly contributes to the advancement of high-data-rate wireless communication and to the realistic evaluation of the MIMO antenna system performance by a robust scientifically-based design methodology.

The general objective of this proposed research is to design and develop signal acquisition and tracking algorithms for multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM) systems for fixed wireless access applications. The algorithms are specifically targeted for systems that work in time division multiple access and frequency division multiple access frame modes. In our research, we first develop a comprehensive system model for a MIMO-OFDM system under the influence of the radio frequency (RF) oscillator frequency offset, sampling frequency (SF) offset, RF oscillator phase noise, frequency selective channel impairments and finally the additive white Gaussian noise. We then develop the acquisition and tracking algorithms to estimate and track all these parameters. The acquisition and tracking algorithms are assisted by a preamble consisting of one or more training sequences and pilot symbol matrices. Along with the signal acquisition and tracking algorithms, we also consider design of the MIMO-OFDM preamble and pilot signals that enable the suggested algorithms to work efficiently. Signal acquisition as defined in our research consists of time and RF synchronization, SF offset estimation and correction, phase noise estimation and correction and finally channel estimation. Signal tracking consists of RF, SF, phase noise and channel tracking. Time synchronization, RF oscillator frequency offset, SF oscillator frequency offset, phase noise and channel estimation and tracking are all research topics by themselves. A large number of studies have addressed these issues, but usually individually and for single-input single-output (SISO) OFDM systems. In the proposed research we present a complete suite of signal acquisition and tracking algorithms for MIMO-OFDM systems along with Cramr-Rao bounds for the SISO-OFDM case. In addition, we also derive the Maximum Likelihood (ML) estimates of the parameters for the SISO-OFDM case. Our proposed research is unique from the existing literature in that it presents a complete receiver implementation for MIMO-OFDM systems and accounts for the cumulative effects of all possible acquisition and tracking errors on the bit error rate (BER) performance. The suggested algorithms and the pilot/training schemes may be applied to any MIMO OFDM system and are independent of the space-time coding techniques that are employed.

This thesis deals with dual-polarized multiple input multiple output (MIMO) channels, an important issue for the practical deployment of multiple antenna systems. The MIMO architecture has the potential to dramatically improve the performance of wireless systems. Much of the focus of research has been on uni-polarized spatial MIMO configurations, the performance of which, is a strong function of the inter-element spacing. Thus the current trend of miniaturization, seems to be at odds with the implementation of spatial configurations in portable handheld devices. In this regard, dual-polarized antennas present an attractive alternative for realizing higher order MIMO architectures in compact devices. Unlike spatial channels, in the presence of polarization diversity, the subchannels of the MIMO channel matrix are not identically distributed. They differ in terms of average received power, envelope distributions, and correlation properties. In this thesis, we report on an indoor channel measurement campaign conducted at 2.4 GHz, to measure the copolarized and cross-polarized subchannels, under line-of-sight (LOS) and non-line-of-sight (NLOS) channel conditions. The measured data is then analyzed, to draw a fair comparison between spatial and dual-polarized MIMO systems, in terms of channel characteristics and achievable capacity. The main drawback of the MIMO architecture is that the gain in capacity comes at a cost of increased hardware complexity. Antenna selection is a technique using which we can alleviate this cost. We emphasize that this strategy is all the more relevant for compact devices, which are often constrained by complexity, power and cost. Using theoretical analysis and measurement results, this thesis investigates the performance of antenna selection in dual-polarized MIMO channels. Our results indicate that, antenna selection when combined with dual-polarized antennas, is an effective, low-complexity solution to the problem of realizing higher order MIMO architectures in compact devices.

Technological progress in the field of wireless communications over the past few years has only been matched by the increasing demand for sophisticated services at lower costs. A significant breakthrough was achieved in the design of efficient wireless communication systems with the advent of the diversity concept. Spatial diversity exploits the availability of multiple spatial paths between the transmitter and receiver by placing antenna arrays at either end. In addition to improving the reliability of communication by creating redundant copies of the transmitted information at the receiver, wireless transceivers with multiple antennas exploit the spatial degrees of freedom to multiplex multiple streams of data and achieve significant gains in spectral efficiencies. In this thesis, we design spatial diversity techniques for slow-fading wireless channels. There are two parts to this thesis: In Part I we propose spatial diversity techniques for point-to-point single-user wireless systems, while in Part II we propose multiuser cooperative diversity techniques for multiuser wireless communication systems. In the first part, we propose a set of new wireless communication techniques for multiple-input, multiple-output (MIMO) channels over Rayleigh slow-fading wireless channels. We introduce MIMO transceivers that achieve high data rates and low error rates using a class of MIMO systems known as layered space-time (ST) architectures, which use low complexity, suboptimal decoders such as successive cancellation (SC) decoders. We propose a set of improved layered space-time architectures and show that it is possible to achieve near-optimal error performance over MIMO channels while requiring just SC decoding at the receiver. We show that these architectures achieve high rate and diversity gains. We also show that some of the proposed layered space-time architectures could find applications in multiple-access communications as low-complexity solutions for achieving near-optimum performance. In the second part of this thesis, we propose novel techniques for cooperative communication between terminals in multiuser wireless communication systems. Cooperative communication is a concept where neighboring terminals share their antennas and signal processing resources to create a virtual transmit array . In addition to transmitting their own information, users in a cooperative communication system listen to transmission from other users and relay this information to the destination, thus creating multiple paths between transmitter and receiver. This form of diversity, known as cooperative diversity, helps improve the overall reliability of all the users in a network. We start with a simple three node multiple-access system where two users are communicating with a common destination. We propose new high-rate cooperation strategies which achieve the full diversity gain offered by the cooperative channel for this simple system. We propose a new framework to address the tradeoff between cooperation and independent transmission over a multiple access channel and determine the conditions under which each idea is better than the other. Finally, we propose a high rate cooperation protocol which achieves the maximum diversity over a multiple access system with an arbitrary number of users and achieves high rates which scale favorably as the number of users increases.

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