Cette thèse aborde plusieurs problèmes fondamentaux des systèmes de communications sans fil avec des antennes multiples, dites systèmes MIMO (multiple input, multiple output). Les contributions se situent aussi bien au niveau des algorithmes de réception qu’au niveau de la génération du signal à l’émission.La plus grande partie de la thèse est dédiée à l’étude des algorithmes de réception. Les points abordés comprennent la modélisation et l’estimation du canal, la détection robuste des symboles, et la suppression des interférences. Un nouveau modèle de canal est proposé dans le chapitre 3 en exploitant les corrélations dans les domaines temporel, fréquentiel et spatial, et en réduisant l’espace des paramètres aux termes dominants. Ce modèle est utilisé pour proposer ensuite un estimateur de canal à faible complexité et aussi un sélecteur de mots de code pour envoyer vers l’émetteur les informations sur l’état du canal. Dans le chapitre 4, la réception robuste est étudiée pour les systèmes MIMO-OFDM sans une connaissance parfaite du canal. Des récepteurs robustes sont proposés pour les cas avec ou sans connaissance statistique du canal. La conception de récepteurs pour les systèmes MIMO-OFDM en présence d’interférence est étudiée dans le chapitre 5 et des récepteurs robustes sont proposés prenant en compte séparément l’interférence causée par les ondes pilotes et celle causée par les symboles d’une part et l’asynchronisme entre le signal et l’interférence d’autre part.Dans la deuxième partie de la thèse (chapitre 6), nous abordons les modulations spatiales qui sont particulièrement adaptées aux systèmes MIMO dans lesquels le nombre de chaines d’émission est inférieur aux nombre d’antennes. Remarquant que l’efficacité spectrale de ces systèmes reste très faible par rapport à la technique de multiplexage spatiale, nous avons développé des modulations spatiales améliorées (ESM, pour Enhanced Spatial Modulation) qui augmentent substantiellement l’efficacité spectrale. Ces modulations sont basées sur l’introduction de modulations secondaires, obtenues par interpolation. La technique ESM gagne plusieurs décibels en rapport signal à bruit lorsque les constellations du signal sont choisies de façon à avoir la même efficacité spectrale que dans les modulations spatiales conventionnelles. / The aim of this thesis is to investigate multiple input multiple output (MIMO) techniques from the reception algorithms, i.e., channel estimation, symbol detection, and interference suppression, to the advanced spatial modulation (SM) transmission schemes, i.e., the signal constellation design for high performance and energy efficiency. In the reception algorithms, the proposed schemes are derived based on the detection theory, i.e., maximum likelihood (ML), linear minimum mean square error (MMSE), successive interference cancellation (SIC), combining with the statistical analysis, i.e., Bayesian linear regression and Bayesian model comparison, in order to deal with the channel uncertainty, i.e., fading, correlations, thermal noise, multiple interference, and the impact of estimation errors.In the transmission schemes, the signal constellations are targeted to find a good trade off between the average transmit energy and the minimum Euclidean distance in the signal space. The proposed schemes, denoted by enhanced SM (ESM), introduce novel modulation/antenna combinations and use them as the information bits for transmission. The number of those combinations is the double or the quadruple of the number of active antenna indices (or index combinations) in conventional SM systems, and this increases the number of bits transmitted per channel use by one or two.The results of simulations show that good system performance can be achieved with the advanced MIMO techniques. Several examples are presented in this thesis to provide insights for the MIMO system designs.

This thesis explores and develops a simulation model for Line of Sight(LoS) Multiple-Input Multiple-Output (MIMO) systems in complex environments. The focus will be on implementing a 2 × 2-MIMO system in order to study phase differences of the received signals. The propagation of the electromagnetic waves is based on an existing wave propagation model that uses the parabolic equation approach. This work aims to deepen our understanding of a 2 × 2-MIMO systems’ behavior under various conditions, including free space propagation but also standard atmospheric and ducting environments. The results demonstrate that the parabolic equation method aligns well with theoretical expectations, validating its use for modeling MIMO systems.The findings have significant implications for optimizing the design and operation of wireless communication systems. The thesis also outlines potential future work, including empirical model verification, development of alternative models, and extension to more complex MIMO systems.

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This dissertation focuses on three major advances on multiple-input multiple-output (MIMO) systems. The first studies and compares decoding algorithms for multi-layered space time coded (MLSTC) systems. These are single user systems that combine spatial multiplexing and transmit diversity. Each layer consists of a space time code. The detection algorithms are based on multi-user detection theory. We consider joint, interference nulling and cancellation, and spatial sequence estimation algorithms. As part of joint detection algorithms, the sphere decoder is studied and its complexity is evaluated over MIMO channels. The second part contributes to the field of space frequency time (SFT) coding for MIMO-OFDM systems. It proposes a full spatial and frequency diversity codes at much lower number of trellis states. The third part proposes and compares uplink scheduling algorithms for multiuser systems with spatial multiplexing. Several scheduling criteria are examined and compared. The capacity and error rate study of MLSTBC reveals the performance of the detection algorithms and their advantage over other open loop MIMO schemes. The results show that the nulling and cancellation operations limit the diversity of the system to the first detected layer in serial algorithms. For parallel algorithms, the diversity of the system is dominated by the performance after parallel nulling. Theoretically, parallel cancellation should provide full receive diversity per layer but error propagations as a result of cancellation prevent the system from reaching this goal. However, parallel cancellation provides some gains but it doesn't increase the diversity. On the other hand, joint detection provides full receive diversity per layer. It could be practically implemented with sphere decoding which has a cubic complexity at high SNR. The results of the SFT coding show the superiority of the IQ-SFT codes over other codes at the same number of sates. The IQ-SFT codes achieve full spatial and frequency diversity at much lower number of trellis states compared to conventional codes. For V-BLAST scheduling, we propose V-BLAST capacity maximizing scheduler and we show that scheduling based on optimal MIMO capacity doesn't work well for V-BLAST. The results also show that maximum minimum singularvalue (MaxMinSV) scheduling performs very close to the V-BLAST capacity maximizing scheduler since it takes into account both the channel power and the orthogonality of the channel. / Ph. D.

Yes / The need to achieve high data rates in modern telecommunication systems, such as 5G standard, motivates the study and development of large antenna and multiple-input multiple-output (MIMO) systems. This study introduces a large antenna-order design of MIMO quasi-orthogonal space-time block code (QO-STBC) system that achieves better signal-to-noise ratio (SNR) and bit-error ratio (BER) performances than the conventional QO-STBCs with the potential for massive MIMO (mMIMO) configurations. Although some earlier MIMO standards were built on orthogonal space-time block codes (O-STBCs), which are limited to two transmit antennas and data rates, the need for higher data rates motivates the exploration of higher antenna configurations using different QO-STBC schemes. The standard QO-STBC offers a higher number of antennas than the O-STBC with the full spatial rate. Unfortunately, also, the standard QO-STBCs are not able to achieve full diversity due to self-interference within their detection matrices; this diminishes the BER performance of the QO-STBC scheme. The detection also involves nonlinear processing, which further complicates the system. To solve these problems, we propose a linear processing design technique (which eliminates the system complexity) for constructing interference-free QO-STBCs and that also achieves full diversity using Hadamard modal matrices with the potential for mMIMO design. Since the modal matrices that orthogonalize QO-STBC are not sparse, our proposal also supports O-STBCs with a well-behaved peak-to-average power ratio (PAPR) and better BER. The results of the proposed QO-STBC outperform other full diversity techniques including Givens-rotation and the eigenvalue decomposition (EVD) techniques by 15 dB for both MIMO and multiple-input single-output (MISO) antenna configurations at 10−3 BER. The proposed interference-free QO-STBC is also implemented for 16×NR and 32×NR MIMO systems, where NR≤2. We demonstrate 8 x 16 and 32 transmit antenna-enabled MIMO systems with the potential for mMIMO design applications with attractive BER and PAPR performance characteristics.

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.

The interest in wireless communications among consumers has exploded since the introduction of the "3G" cell phone standards. One reason for their success is the increasingly higher data rates achievable through the networks. A further increase in data rates is possible through the use of multiple antennas at either or both sides of the wireless links. Precoding and receive filtering using matrices obtained from a singular value decomposition (SVD) of the channel matrix is a transmission strategy for achieving the channel capacity of a deterministic narrowband multiple-input multiple-output (MIMO) communications channel. When signalling over wideband channels using orthogonal frequency-division multiplexing (OFDM), an SVD must be performed for every sub-carrier. As the number of sub-carriers of this traditional approach grow large, so does the computational load. It is therefore interesting to study alternate means for obtaining the decomposition. A wideband MIMO channel can be modeled as a matrix filter with a finite impulse response, represented by a polynomial matrix. This thesis is concerned with investigating algorithms which decompose the polynomial channel matrix directly. The resulting decomposition factors can then be used to obtain the sub-carrier based precoding and receive filtering matrices. Existing approximative polynomial matrix QR and singular value decomposition algorithms were modified, and studied in terms of decomposition quality and computational complexity. The decomposition algorithms were shown to give decompositions of good quality, but if the goal is to obtain precoding and receive filtering matrices, the computational load is prohibitive for channels with long impulse responses. Two algorithms for performing exact rational decompositions (QRD/SVD) of polynomial matrices were proposed and analyzed. Although they for simple cases resulted in excellent decompositions, issues with numerical stability of a spectral factorization step renders the algorithms in their current form purposeless. For a MIMO channel with exponentially decaying power-delay profile, the sum rates achieved by employing the filters given from the approximative polynomial SVD algorithm were compared to the channel capacity. It was shown that if the symbol streams were decoded independently, as done in the traditional approach, the sum rates were sensitive to errors in the decomposition. A receiver with a spatially joint detector achieved sum rates close to the channel capacity, but with such a receiver the low complexity detector set-up of the traditional approach is lost. Summarizing, this thesis has shown that a wideband MIMO channel can be diagonalized in space and frequency using OFDM in conjunction with an approximative polynomial SVD algorithm. In order to reach sum rates close to the capacity of a simple channel, the computational load becomes restraining compared to the traditional approach, for channels with long impulse responses.

While the capacity of multiple-input multiple-output (MIMO) systems has been explored in considerable detail, virtually all literature on this topic ignores electromagnetic considerations. This dissertation explores electromagnetic effects on the capacity performance of these multi-antenna architectures. Specifically, it examines the impact of superdirectivity for compact antenna arrays, the effect of antenna mutual coupling, and MIMO performance of multi-mode optical fiber with non-linear detection. Superdirectivity can lead to abnormally large capacity bounds in a MIMO communication system, especially when the antennas are placed close together. Because superdirective behavior is difficult to achieve in practice, this work formulates an approach for limiting the impact of superdirectivity by introducing finite ohmic loss into the capacity expressions. Results show that even a small amount of ohmic loss significantly affects the achievable system capacity and suppresses superdirective solutions. This formulation allows a more detailed examination of the capacity of MIMO systems for compact arrays. For channels which do not vary in time, placing antennas closer together generally reduces the system capacity. However, recent work has demonstrated that for a MIMO system operating in a fast fading environment where the transmitter and receiver know the channel covariance information, the capacity increases as antennas are placed near each other due to an increase in spatial correlation. Analysis of this behavior illustrates that when these capacity gains (due to closely spaced antennas) are observed the radiated power is also increased. Constraining the radiated power leads to superdirective solutions in which the ohmic loss constraint developed must be used to properly determine the capacity behavior of this system. Application of this constraint then leads to an optimum antenna spacing in contrast to the findings of previous research which indicate that antennas should be as close together as possible. Additionally, this section provides an analysis regarding the number of spatial modes that can be used for various system configurations. Recent research has shown that it is possible for MIMO communication techniques to be used with multimode optical fibers to increase the available distance-bandwidth. However, implementation of traditional MIMO schemes requires the use of coherent optical detection which can lead to high system complexity and cost. This dissertation proposes a multimode fiber MIMO system architecture which allows simultaneous transmission of unique streams to different users on the same fiber while using incoherent detection with amplitude and phase modulation at the transmitter. The resulting capacity scales nearly linearly with the number of transmitters and receivers. Because the architecture requires channel state information at the transmitter, a training scheme appropriate for use with optical intensity detection is also discussed.

ITC/USA 2006 Conference Proceedings / The Forty-Second Annual International Telemetering Conference and Technical Exhibition / October 23-26, 2006 / Town and Country Resort & Convention Center, San Diego, California / Spatial multiplexing (SM) systems have received significant attention because the architecture offers high spectral efficiency. However, relatively little research exists on optimization of SM systems in the presence of jamming. In a spatially uncoded SM system, such as V-BLAST, the channel state information is assumed to be unavailable a priori at both transmitter and receiver. Here, Kalman filtering is used to estimate the Rayleigh fading channel at the receiver. The spatial correlation of the jammer plus noise is also estimated, and spatial whitening to reject the jammers is employed in both the Kalman channel estimator and detector. To avoid the exponential complexity of maximum-likelihood (ML) detection, the QRD-M algorithm is employed. In contrast to sphere decoding, QRD-M has fixed decoding complexity of order O(M), and is thus attractive for hardware implementation. The performance of the joint Kalman filter channel estimator, spatial whitener and QRD-M detector is verfied by simulations.

ITC/USA 2005 Conference Proceedings / The Forty-First Annual International Telemetering Conference and Technical Exhibition / October 24-27, 2005 / Riviera Hotel & Convention Center, Las Vegas, Nevada / Multiple-input multiple output (MIMO) communication systems can have dramatically higher throughput than single-input, single-output systems. Unfortunately, it can be difficult to find the space-time codes these systems need to achieve their potential. Previously published results located good codes by minimizing the maximum correlation between transmitted signals. This paper shows how this min-max method may produce sub-optimal codes. A new method which sorts codes based on the union bound of pairwise error probabilities is presented. This new technique can identify superior MIMO codes, providing higher system throughput without increasing the transmitted power or bandwidth requirements.