La coopération des transmetteurs dans les système multi-antennes a été reconnue comme un outil prometteur pour éviter ou aligner les interférences résultant d’une réutilisation agressive de la bande spectrale. Il est usuellement supposé que les estimées de canal sont parfaitement partagées entre tous les transmetteurs entrant en coopération, ce qui n’est pas adapté à de nombreuses situations où des émetteurs éloignés visent à coopérer. C’est pourquoi nous étudions le cas de réseaux sans-fil où des transmetteurs émettent d’une manière coopérative bien qu’ils ne puissent échanger que d’une manière imparfaite l’information de canal obtenue localement. Ce partage imparfait de l’information de canal donne lieu à une configuration d’information de canal, dénotée comme « distribuée », où chaque transmetteur reçoit une estimée du canal multi-utilisateurs qui lui est propre, à partir de laquelle il détermine ses paramètres de transmission. Nous étudions tout d’abord les conséquences de la configuration à information de canal distribuée sur le précodage. En particulier, nous mettons en évidence l’inefficacité des méthodes conventionnelles de précodage lorsque confrontées à une configuration à information de canal distribuée. Nous étudions ensuite une autre facette de ce scenario, qui est la détermination de « qui doit savoir quoi », lorsqu’il s’agit de l’information de canal disponible aux transmetteurs engagés dans la coopération. Il est démontré comment une allocation non-uniforme de l’information de canal aux transmetteurs peut donner lieu à des gains importants, en fonction de la géométrie du réseau considéré. / Multiple-antenna based transmitter cooperation has been established as a promising tool towards avoiding, aligning, or shaping the interference resulting from aggressive spectral reuse. Although the impact of imperfect knowledge of the channel state information (CSI) is often investigated, it is usually assumed that the channel estimates are perfectly shared between all the transmitters. This assumption is however not adapted to many practical cases of transmitter cooperation between distant transmitters. Therefore, we focus in this thesis on the network scenario where the transmitters would like to cooperate in their transmission but can only imperfectly exchange on CSI which is acquired locally. This imperfect CSI sharing step gives rise to a CSI configuration, denoted as “distributed CSI”, where each transmitter has its own imperfect estimate of the global multi-user channel based on which it determines its transmit parameters. We study first the impact of having distributed CSI over the precoder design. Specifically, we show that conventional precoding schemes are not adapted to the distributed CSI configuration and lead to poor performance. We then turn to another aspect of this CSI configuration which is to determine “Who needs to know what", when it comes to CSI at cooperating transmitters. In contrast to the resource-hungry solution consisting in providing the same CSI to all transmitters, it is shown how a non-uniform spatial allocation of the CSI to the transmitters can provide strong gains depending on the networks topology.

Orientador: Gustavo Fraidenraich / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação / Made available in DSpace on 2018-08-19T21:07:30Z (GMT). No. of bitstreams: 1 Lessa_CarmenLuciaAvelar_M.pdf: 2504273 bytes, checksum: 47a502a9d17e8b31113225b0cb9926c3 (MD5) Previous issue date: 2011 / Resumo: Neste trabalho é proposta uma estratégia para transmissão digital utilizando cooperação de usuários em conjunto com a tecnologia de múltiplas antenas (MIMO - do inglês. Multiple Input Multiple Output). Em um primeiro modelo de sistema foi utilizada a tecnologia CDMA (do inglês, Code Division Multiple Access) para distinção entre as mensagens dos usuários. Já em um segundo modelo sugerido foram utilizadas as técnicas do Descorrelacionador e a Decomposição em Valores Singulares (SVD - do inglês, Singular Value Decomposition) para permitir a cooperação entre os usuários sem a necessidade de multiplexação por código. Neste trabalho é apresentado como a cooperação entre os usuários pode ser feita utilizando várias antenas. Como exemplo foi considerado um regime de cooperação para o canal MIMO com dois usuários com uma única antena e o receptor com duas antenas. O cálculo da probabilidade de erro para este caso foi desenvolvido / Abstract: This work proposes user cooperation strategy using multiple antennas technology (MIMO). In a first model it was used a Code Division Multiple Access (CDMA) system and in a second model was applied the techniqucs of the Decorrclator and Singular Value Decomposition (SVD) to allow cooperation of users. It is show how cooperation using different numbers of antennas can be accomplished. It was considered a cooperation scheme for MIMO MAC channel with two users having single antenna and the reciver with two antennas. The results show that user cooperation with multiple antennas reduces the bit error probability / Mestrado / Telecomunicações e Telemática / Mestre em Engenharia Elétrica

L’évolution des communications sans fil doit répondre à la croissance exponentielle de la consommation de données. On prévoit une augmentation du débit allant jusqu’à 1000 d’ici 2020. Cependant, pour atteindre ce but, plusieurs ingrédients sont essentiels. La limitation majeure des systèmes sans fil est l’interférence à cause de la réutilisation des fréquences. C'est un problème qui existait depuis toujours et notamment à partir de la 3G. On croit que ce problème sera notamment plus grave dans la 5G, et cela à cause de la densification prévue des réseaux. L’utilisation de l’OFDM en 4G a mené à la gestion de l’interférence par coordination dynamique des blocs de ressources. Or, cela n’a permis qu’une augmentation modeste du débit. Une nouvelle technique de gestion de l’interférence fut née il y a 5 années. Cette technique s’appelle l’alignement d’interférence (IA). L’IA permet d’avoir une capacité égale à la moitié de la capacité d’un système sans interférences. Cette technique suppose que chaque transmetteur (TX) connait les canaux non seulement envers les récepteurs (RX)s mais les canaux de tous les TXs vers tous les RXs. Une technique d’interférence plus récente qui améliore l’IA, c’est le massive MIMO, ou les TXs sont équipés d’antennes à grande échelle. l’idée est motivée par plusieurs simplifications qui apparaissent en régime asymptotique ou les stations de base ont un trés grand nombre d’antennes. Le but de cette thèse est d’introduire des solutions complètes et réalistes pour la gestion d’interférence en utilisant le massive MIMO dans un scénario multi-cellules multi-utilisateurs. Notre travail traite surtout le problème de la connaissance imparfaite des canaux. / The evolution of wireless communication must meet the increasingly high demand in mobile data. It is expected to increase the maximum rates of wireless by a factor of 1000 by 2020. Meanwhile, it is clear that to reach this goal, a combination of different ingredients is necessary. The major limitation of wireless systems is the interference due to frequency reuse. This has been a long-standing impairment in cellular networks of all generations that will be further exacerbated in 5G networks, due to the expected dense cell deployment. The use of orthogonal frequency-division multiplexing (OFDM) in 4G leaded to an interference management by dynamic coordination of resource blocks. However, this allowed only modest gains in rates. A new technique of interference management was born 5 years ago, the interference alignment (IA). the IA permits to have a capacity with equals the half of the capacity of an interference-free system. This technique supposes that each transmitter (TX) knows the channels not only towards its receivers (RX)s, but the channels from all TXs to all receivers RXs. A more recent interference technique that boosts IA is massive multiple input multiple output (MIMO), where TXs use antennas at a very large scale. The idea is motivated by many simplifications, which appear in an asymptotic regime where base stations are endowed with large numbers of antennas. This thesis treats the problem of interference cancellation and capacity maximization in massive MIMO. In this context, the thesis proposes new interference management alternatives for the massive MIMO antenna regime, taking into account also the practical challenges of massive antenna arrays.

Half-Duplex Multiuser Multiple-Input Multiple-Output (HD MU-MIMO) systemscurrently employed in communication systems are not experiencing the selfinterference(SI) problem but they are not optimal in terms of efficiency and interms of resources used (time and frequency resources). Ignoring the effect of largescalefading, we start by explaining the uplink (UL) and downlink (DL) parts ofthe MU-MIMO system and how the sum-rate is calculated. We also introduce thethree linear receivers/precoders, Maximum-Ratio Combining (MRC)/Maximum-Ratio Transmission (MRT), Zero-Forcing (ZF), and Minimum Mean-Square Error(MMSE) and which of the three types is going to be used in the study of Full-Duplex Multiuser Multiple-input Multiple-output (FD MU-MIMO) system. Thenwe introduce FD MU-MIMO system, and how the equation used to calculate thesum-rate of the UL part changes when the SI occurs, and why SI problem is notpresent in the DL part. Next, we introduce the spectral efficiency (SE), and howto calculate it and why it is taken as a parameter to compare HD and FD systems.Also the effect of SI on FD MU-MIMO system is presented through simulationgraphs, then we move to show how to reduce SI effect by increasing the number ofantennas in the base-station (BS). Lastly, we take the effect of large scale fading inorder to reach a simple statistical model in the form cumulative distribution function(CDF) graph for different values of SI and compare those of FD MU-MIMOsystem to HD MU-MIMO. The results show that FD MU-MIMO together withmassive MIMO technology is very promising and would save time and frequencyresources which means an increase in the SE but SI must be below a certain level.

To meet the very high data rate requirements for wireless Internet and multimedia services, cooperative systems with multiple antennas have been proposed for future generation wireless systems. In this thesis, we focus on multiple antennas at the source, relay and destination. We study both downlink and uplink cooperative systems with single antenna relays. For downlink systems, the optimal precoder to minimize the sum transmit power subject to quality of service (QoS) constraints with fixed relay weights is derived. We also study the optimization of relay weights with a fixed precoder. An iterative algorithm is developed to jointly optimize the precoder and relay weights. The performance of the downlink system with imperfect CSI as well as multiple receive antennas is also studied. For the uplink system, we similarly derive the optimum receiver as in the downlink with fixed relay weights. The optimization of relay weights for a fixed receiver is then studied. An iterative algorithm is developed to jointly optimize the receiver and relay weights in the uplink. Systems with imperfect channel estimation are also considered. The study of cooperative MIMO systems is then extended to a multi-cell scenario. In particular, two scenarios are studied. In the first, the cells coordinate their beamformers to find the most suitable cell to serve a specific user. In the second, each base station selectively transmits to a fixed group of users, and the cells coordinate to suppress mutual interference. Finally, our investigation culminates with a study of an uplink cooperative system equipped with multi-antenna relays under a capacity maximization criterion. The specific scheme that users access the base station through a single multi-antenna relay are studied. Iterative capacity maximization algorithm are proposed and shown to converge to local maxima. Numerical results are presented to highlight that the algorithms are able to come close to these bounds after only a few iterations. / Thesis (Ph.D, Electrical & Computer Engineering) -- Queen's University, 2013-06-25 15:43:23.343

Thesis (Ph.D.)--University of Delaware, 2006. / Principal faculty advisor: Xiang-Gen Xia, Dept. of Electrical and Computer Engineering. Includes bibliographical references.

Thesis (Ph.D.)--University of Delaware, 2006. / Principal faculty advisor: Xiang-Gen Xia, Dept. of Electrical and Computer Engineering. Includes bibliographical references.

Thesis (Ph.D.)--University of Delaware, 2006. / Principal faculty advisor: Xiang-Gen Xia, Dept. of Electrical and Computer Engineering. Includes bibliographical references.

Thesis (M.S.)--University of Hawaii at Manoa, 2005. / Includes bibliographical references (leaves 74-75). / xi, 75 leaves, bound ill. 29 cm

Thesis (M.Phil.)--Hong Kong University of Science and Technology, 2007. / Includes bibliographical references (leaves 57-59). Also available in electronic version.