Precoding-based blind separation of MIMO FIR mixtures

This paper focuses on the problem of blind separation of sources mixed by multi-input multi-output finite impulse response channels, which is also called convolutive blind source separation (BSS) in short. This problem has been intensively studied in the context that the sources possess certain favourable properties, such as independence and sparsity. However, these properties may not exist in some practical applications. In this paper, we propose a precoding-based convolutive BSS method, which can deal with mutually correlated sources without requiring the sources to be sparse. It is also applicable to mutually independent sources. In the proposed method, the sources are preprocessed in transmitters prior to transmission by order-one precoders. At the receiving side, the second-order statistics of the sources and the Z -domain features of the precoders are exploited to estimate the coded signals, from which the sources are recovered. Simulation results demonstrate the effectiveness of the new convolutive BSS method

Blind channel estimation for MIMO OFDM communication systems

Ph.DDOCTOR OF PHILOSOPH

Linear Transmit-Receive Strategies for Multi-user MIMO Wireless Communications

Die Notwendigkeit zur Unterdrueckung von Interferenzen auf der einen Seite und zur Ausnutzung der durch Mehrfachzugriffsverfahren erzielbaren Gewinne auf der anderen Seite rueckte die raeumlichen Mehrfachzugriffsverfahren (Space Division Multiple Access, SDMA) in den Fokus der Forschung. Ein Vertreter der raeumlichen Mehrfachzugriffsverfahren, die lineare Vorkodierung, fand aufgrund steigender Anzahl an Nutzern und Antennen in heutigen und zukuenftigen Mobilkommunikationssystemen besondere Beachtung, da diese Verfahren das Design von Algorithmen zur Vorcodierung vereinfachen. Aus diesem Grund leistet diese Dissertation einen Beitrag zur Entwicklung linearer Sende- und Empfangstechniken fuer MIMO-Technologie mit mehreren Nutzern. Zunaechst stellen wir ein Framework zur Approximation des Datendurchsatzes in Broadcast-MIMO-Kanaelen mit mehreren Nutzern vor. In diesem Framework nehmen wir das lineare Vorkodierverfahren regularisierte Blockdiagonalisierung (RBD) an. Durch den Vergleich von Dirty Paper Coding (DPC) und linearen Vorkodieralgorithmen (z.B. Zero Forcing (ZF) und Blockdiagonalisierung (BD)) ist es uns moeglich, untere und obere Schranken fuer den Unterschied bezueglich Datenraten und bezueglich Leistung zwischen beiden anzugeben. Im Weiteren entwickeln wir einen Algorithmus fuer koordiniertes Beamforming (Coordinated Beamforming, CBF), dessen Loesung sich in geschlossener Form angeben laesst. Dieser CBF-Algorithmus basiert auf der SeDJoCo-Transformation und loest bisher vorhandene Probleme im Bereich CBF. Im Anschluss schlagen wir einen iterativen CBF-Algorithmus namens FlexCoBF (flexible coordinated beamforming) fuer MIMO-Broadcast-Kanaele mit mehreren Nutzern vor. Im Vergleich mit bis dato existierenden iterativen CBF-Algorithmen kann als vielversprechendster Vorteil die freie Wahl der linearen Sende- und Empfangsstrategie herausgestellt werden. Das heisst, jede existierende Methode der linearen Vorkodierung kann als Sendestrategie genutzt werden, waehrend die Strategie zum Empfangsbeamforming frei aus MRC oder MMSE gewaehlt werden darf. Im Hinblick auf Szenarien, in denen Mobilfunkzellen in Clustern zusammengefasst sind, erweitern wir FlexCoBF noch weiter. Hier wurde das Konzept der koordinierten Mehrpunktverbindung (Coordinated Multipoint (CoMP) transmission) integriert. Zuletzt stellen wir drei Moeglichkeiten vor, Kanalzustandsinformationen (Channel State Information, CSI) unter verschiedenen Kanalumstaenden zu erlangen. Die Qualitaet der Kanalzustandsinformationen hat einen starken Einfluss auf die Guete des Uebertragungssystems. Die durch unsere neuen Algorithmen erzielten Verbesserungen haben wir mittels numerischer Simulationen von Summenraten und Bitfehlerraten belegt.In order to combat interference and exploit large multiplexing gains of the multi-antenna systems, a particular interest in spatial division multiple access (SDMA) techniques has emerged. Linear precoding techniques, as one of the SDMA strategies, have obtained more attention due to the fact that an increasing number of users and antennas involved into the existing and future mobile communication systems requires a simplification of the precoding design. Therefore, this thesis contributes to the design of linear transmit and receive strategies for multi-user MIMO broadcast channels in a single cell and clustered multiple cells. First, we present a throughput approximation framework for multi-user MIMO broadcast channels employing regularized block diagonalization (RBD) linear precoding. Comparing dirty paper coding (DPC) and linear precoding algorithms (e.g., zero forcing (ZF) and block diagonalization (BD)), we further quantify lower and upper bounds of the rate and power offset between them as a function of the system parameters such as the number of users and antennas. Next, we develop a novel closed-form coordinated beamforming (CBF) algorithm (i.e., SeDJoCo based closed-form CBF) to solve the existing open problem of CBF. Our new algorithm can support a MIMO system with an arbitrary number of users and transmit antennas. Moreover, the application of our new algorithm is not only for CBF, but also for blind source separation (BSS), since the same mathematical model has been used in BSS application.Then, we further propose a new iterative CBF algorithm (i.e., flexible coordinated beamforming (FlexCoBF)) for multi-user MIMO broadcast channels. Compared to the existing iterative CBF algorithms, the most promising advantage of our new algorithm is that it provides freedom in the choice of the linear transmit and receive beamforming strategies, i.e., any existing linear precoding method can be chosen as the transmit strategy and the receive beamforming strategy can be flexibly chosen from MRC or MMSE receivers. Considering clustered multiple cell scenarios, we extend the FlexCoBF algorithm further and introduce the concept of the coordinated multipoint (CoMP) transmission. Finally, we present three strategies for channel state information (CSI) acquisition regarding various channel conditions and channel estimation strategies. The CSI knowledge is required at the base station in order to implement SDMA techniques. The quality of the obtained CSI heavily affects the system performance. The performance enhancement achieved by our new strategies has been demonstrated by numerical simulation results in terms of the system sum rate and the bit error rate

Multiple shift second order sequential best rotation algorithm for polynomial matrix EVD

In this paper, we present an improved version of the second order sequential best rotation algorithm (SBR2) for polynomial matrix eigenvalue decomposition of para-Hermitian matrices. The improved algorithmis entitledmultiple shift SBR2 (MS-SBR2) which is developed based on the original SBR2 algorithm. It can achieve faster convergence than the original SBR2 algorithm by means of transferring more off-diagonal energy onto the diagonal at each iteration. Its convergence is proved and also demonstrated by means of a numerical example. Furthermore, simulation results are included to compare its convergence characteristics and computational complexity with the original SBR2, sequential matrix diagonalization (SMD) and multiple shift maximum element SMD algorithms

Réduction d'interférence dans les systèmes de transmission sans fil

Wireless communications have known an exponential growth and a fast progress over the past few decades. Nowadays, wireless mobile communications have evolved over time starting with the first generation primarily developed for voice communications, and reaching the fourth generation referred to as long term evolution (LTE) that offers an increasing capacity and speed using a different radio interface together with core network improvements. Overall throughput and transmission reliability are among the essential measures of service quality in a wireless system. Such measures are mainly subjected to interference management constraint in a multi-user network. The interference management is at the heart of wireless regulation and is essential for maintaining a desirable throughput while avoiding the detrimental impact of interference at the undesired receivers. Our work is incorporated within the framework of interference network where each user is equipped with single or multiple antennas. The goal is to resolve the challenges that the communications face taking into account the achievable rate and the complexity cost. We propose several solutions for the precoding and decoding designs when transmitters have limited cooperation based on a technique called Interference Alignment. We also address the detection scheme in the absence of any precoding design and we introduce a low complexity detection scheme based on the sparse decomposition.Les communications mobiles sans fil ont connu un formidable essor au cours des dernières décennies. Tout a commencé avec les services vocaux offerts par les systèmes de la première génération en 1980, jusqu¿aux systèmes de la quatrième génération aujourd¿hui avec des services internet haut débit et un accroissement du nombre d¿utilisateurs. En effet, les caractéristiques essentielles qui définissent les services et la qualité de ces services dans les systèmes de communication sans fil sont: le débit, la fiabilité de transmission et le nombre d¿utilisateurs. Ces caractéristiques sont fortement liées entre elles et sont dépendantes de la gestion des interférences entre les différents utilisateurs. Les interférences entre-utilisateurs se produisent lorsque plusieurs émetteurs, dans une même zone, transmettent simultanément en utilisant la même bande de fréquence. Dans cette thèse, nous nous intéressons à la gestion d¿interférence entre utilisateurs par le biais de l¿approche d¿alignement d¿interférences où la coopération entre utilisateurs est réduite. Aussi, nous nous sommes intéressés au design d¿un récepteur où l¿alignement d¿interférences n¿est pas utilisé et où la gestion des interférences est réalisée par des techniques de décodage basées sur les décompositions parcimonieuses des signaux de communications. Ces approches ont conduit à des méthodes performantes et peu couteuses, exploitables dans les liens montant ou descendant

Blind channel estimation for space-time block codes : novel methods and performance Studies

[abstract] This work is based on a study of blind source separation techniques in order to estimate coe cients in transmission systems using Alamouti codi cation with two transmit antennas and one receive antenna. Most of present standards include pilot symbols to estimate the channel in reception. Since these symbols do not deliver user's data, their use decrease transferring quantity and also the system capacity. On the other hand, algorithms of blind separation are less precise when estimating channel coe cients than those supervised, but achieving a higher transferring rate. In this work we will deal with Alamouti codi cation system as a typical problem of blind sources separation where the signals transmitted and the channel coe cients must be estimated according to lineal and instantaneous mixtures (observations). Orthogonal structure required by Alamouti codi cation allows us to solve this problem by decomposing eigenvalues and eigenvectors of matrices calculated from di erent statistics of the observations. These algorithms could be classi ed as those using second order statistics and those using higher order statistics. Algorithms based on second order statistics work with correlation matrix of observations. They are computationally less expensive, but require a lineal precoder in order to balance the power of the signals transmitted. One of our contributions is being able to determine in an empirical way how the power decompensation should be done in order to reduce the proabibility of error in the system. On the other hand, algorithms dealing with high level statistics are based on diagonalize one or several high level cumulant matrices deriving into a major computational cost in the receiver. As an advantage we must point out that they do not require to include a lineal precoder to do the power decompensation. In this work we will prove that the output of these techniques depends on the level of eigenvalue of the diagonalized matrix spreading. This idea will be used by us in order to achieve the optimal cumulant matrix and also to propose a new algorithm that increases the output in relation to those already proposed by other authors. Another important contribution of this present study is to propose a detailed comparison between channel estimation techniques in simulated scenarios, considering channels with Rayleigh and Rice distribution, and in real scenarios in ISM of 2.4 GHz band, by using a MIMO testbed developed in Universidade da Coruña. [Resumen] En este trabajo se realiza un estudio de técnicas de separación ciega de fuentes para la estimación de los coeficientes en sistemas de transmisión que emplean la codificación de Alamouti con 2 antenas transmisoras y 1 antena receptora. La mayoría de los estándares actuales incluyen símbolos piloto para estimar el canal en recepción. Dado que estos símbolos no transportan datos del usuario, su utilización decrementa la tasa de transferencia y degrada el rendimiento del sistema. Por otro lado, los algoritmos de separación ciega son menos precisos en la estimación de los coeficientes de canal que los supervisados pero consiguen una tasa de transferencia mayor. En el presente trabajo, modelaremos el sistema de codificación de Alamouti como un problema típico de separación ciega de fuentes donde las se~nales transmitidas y los coeficientes del canal deben ser estimados a partir de mezclas lineales e instantáneas (observaciones). La estructura ortogonal impuesta por la codificación de Alamouti permite resolver este problema mediante la descomposición de autovalores y autovectores de matrices calculadas a partir de diferentes estadísticos de las observaciones. Estos algoritmos pueden ser clasificados en aquellos que utilizan estadísticos de segundo orden y aquellos que emplean estadísticos de orden superior. Los algoritmos que emplean estadísticos de segundo orden trabajan con la matriz de correlación de las observaciones, son computacionalmente poco costosos pero requieren de un precodificador lineal para descompensar la potencia de las se~nales transmitidas. Una de nuestras aportaciones es la de determinar de forma empírica cómo debe realizarse la descompesación de potencia de cara a reducir la probabilidad de error del sistema. Por otro lado, los algoritmos que trabajan con estadísticos de orden superior se basan en diagonalizar una o varias matrices de cumulantes de orden superior, lo que conlleva un mayor coste computacional en el receptor. Como ventaja debe resaltarse que no requieren incluir un precodificador lineal que realice la descompensación de potencia. En este trabajo mostraremos que el rendimiento de estas técnicas depende del grado de dispersión de los autovalores de la matriz que se diagonaliza. Utilizaremos esta idea para obtener la matriz de cumulantes óptima y para formular un nuevo algoritmo que supera en rendimiento a los propuestos previamente por otros autores. Otra aportación relevante del presente trabajo es presentar una detallada comparación de las técnicas de estimación de canal en entornos simulados, considerando canales con ditribución Rayleigh y Rice, y en entornos reales en la banda ISM de 2.4 GHz mediante el empleo de una plataforma de transmisión MIMO desarrollada en la Universidade da Coruña