Space time transceiver design over multipath fading channels

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On the application of massive mimo systems to machine type communications

This paper evaluates the feasibility of applying massive multiple-input multiple-output (MIMO) to tackle the uplink mixed-service communication problem. Under the assumption of an available physical narrowband shared channel, devised to exclusively consume data traffic from machine type communications (MTC) devices, the capacity (i.e., number of connected devices) of MTC networks and, in turn, that of the whole system, can be increased by clustering such devices and letting each cluster share the same time-frequency physical resource blocks. Following this research line, we study the possibility of employing sub-optimal linear detectors to the problem and present a simple and practical channel estimator that works without the previous knowledge of the large-scale channel coefficients. Our simulation results suggest that the proposed channel estimator performs asymptotically, as well as the MMSE estimator, with respect to the number of antennas and the uplink transmission power. Furthermore, the results also indicate that, as the number of antennas is made progressively larger, the performance of the sub-optimal linear detection methods approaches the perfect interference-cancellation bound. The findings presented in this paper shed light on and motivate for new and exciting research lines toward a better understanding of the use of massive MIMO in MTC networks

Systèmes MIMO : conception, estimation du canal, et détection

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.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

Adaptive and Iterative Multi-Branch MMSE Decision Feedback Detection Algorithms for MIMO Systems

In this work, decision feedback (DF) detection algorithms based on multiple processing branches for multi-input multi-output (MIMO) spatial multiplexing systems are proposed. The proposed detector employs multiple cancellation branches with receive filters that are obtained from a common matrix inverse and achieves a performance close to the maximum likelihood detector (MLD). Constrained minimum mean-squared error (MMSE) receive filters designed with constraints on the shape and magnitude of the feedback filters for the multi-branch MMSE DF (MB-MMSE-DF) receivers are presented. An adaptive implementation of the proposed MB-MMSE-DF detector is developed along with a recursive least squares-type algorithm for estimating the parameters of the receive filters when the channel is time-varying. A soft-output version of the MB-MMSE-DF detector is also proposed as a component of an iterative detection and decoding receiver structure. A computational complexity analysis shows that the MB-MMSE-DF detector does not require a significant additional complexity over the conventional MMSE-DF detector, whereas a diversity analysis discusses the diversity order achieved by the MB-MMSE-DF detector. Simulation results show that the MB-MMSE-DF detector achieves a performance superior to existing suboptimal detectors and close to the MLD, while requiring significantly lower complexity.Comment: 10 figures, 3 tables; IEEE Transactions on Wireless Communications, 201