Timing estimation and resynchronization for amplify-and-forward communication systems

This paper proposes a general framework to effectively estimate the unknown timing and channel parameters, as well as design efficient timing resynchronization algorithms for asynchronous amplify-and-forward (AF) cooperative communication systems. In order to obtain reliable timing and channel parameters, a least squares (LS) estimator is proposed for initial estimation and an iterative maximum-likelihood (ML) estimator is derived to refine the LS estimates. Furthermore, a timing and channel uncertainty analysis based on the CramrRao bounds (CRB) is presented to provide insights into the system uncertainties resulted from estimation. Using the parameter estimates and uncertainty information in our analysis, timing resynchronization algorithms that are robust to estimation errors are designed jointly at the relays and the destination. The proposed framework is developed for different AF systems with varying degrees of timing misalignment and channel uncertainties and is numerically shown to provide excellent performances that approach the synchronized case with perfect channel information. © 2006 IEEE.published_or_final_versio

Channel estimation and parameters acquisition systems employing cooperative diversity

Doutoramento em Engenharia Eletrotécnica e TelecomunicaçõesThis work investigates new channel estimation schemes for the forthcoming and future generation of cellular systems for which cooperative techniques are regarded. The studied cooperative systems are designed to re-transmit the received information to the user terminal via the relay nodes, in order to make use of benefits such as high throughput, fairness in access and extra coverage. The cooperative scenarios rely on OFDM-based systems employing classical and pilot-based channel estimators, which were originally designed to pointto-point links. The analytical studies consider two relaying protocols, namely, the Amplifyand-Forward and the Equalise-and-Forward, both for the downlink case. The relaying channels statistics show that such channels entail specific characteristics that comply to a proper filter and equalisation designs. Therefore, adjustments in the estimation process are needed in order to obtain the relay channel estimates, refine these initial estimates via iterative processing and obtain others system parameters that are required in the equalisation. The system performance is evaluated considering standardised specifications and the International Telecommunication Union multipath channel models.Este trabalho tem por objetivo o estudo de novos esquemas de estimação de canal para sistemas de comunicação móvel das próximas gerações, para os quais técnicas cooperativa são consideradas. Os sistemas cooperativos investigados neste trabalho estão projetados para fazerem uso de terminais adicionais a fim de retransmitir a informação recebida para o utilizador final. Desta forma, pode-se usurfruir de benefícios relacionados às comunicações cooperativas tais como o aumento do rendimento do sistema, fiabilidade e extra cobertura. Os cenários são basedos em sistemas OFDM que empregam estimadores de canal que fazem uso de sinais piloto e que originalmente foram projetados para ligações ponto a ponto. Os estudos analíticos consideram dois protocolos de encaminhamento, nomeadamente, Amplify-and-Forward e Equalise-and-Forward, ambos para o caso downlink. As estatísticas dos canais em estudo mostram que tais canais ocasionam características específicas para as quais o filtro do estimador e a equalisação devem ser apropridamente projetados. Estas características requerem ajustes que são necessários no processo de estimação a fim de estimar os canais, refinar as estimativas iniciais através de processos iterativos e ainda obter outros parâmetros do sistema que são necessários na equalização. O desempenho dos esquemas propostos são avaliados tendo em consideração especificações padronizadas e modelos de canal descritos na International Telecommunication Union

Secrecy Enhancement in Cooperative Relaying Systems

Cooperative communications is obviously an evolution in wireless networks due to its noticeable advantages such as increasing the coverage as well as combating fading and shadowing effects. However, the broadcast characteristic of a wireless medium which is exploited in cooperative communications leads to a variety of security vulnerabilities. As cooperative communication networks are globally expanded, they expose to security attacks and threats more than ever. Primarily, researchers have focused on upper layers of network architectures to meet the requirements for secure cooperative transmission while the upper-layer security solutions are incapable of combating a number of security threats, e.g., jamming attacks. To address this issue, physical-layer security has been recommended as a complementary solution in the literature. In this thesis, physical layer attacks of the cooperative communication systems are studied, and corresponding security techniques including cooperative jamming, beamforming and diversity approaches are investigated. In addition, a novel security solution for a two-hop decode-and-forward relaying system is presented where the transmitters insert a random phase shift to the modulated data of each hop. The random phase shift is created based on a shared secret among communicating entities. Thus, the injected phase shift confuses the eavesdropper and secrecy capacity improves. Furthermore, a cooperative jamming strategy for multi-hop decode-and-forward relaying systems is presented where multiple non-colluding illegitimate nodes can overhear the communication. The jamming signal is created by the transmitter of each hop while being sent with the primary signal. The jamming signal is known at the intended receiver as it is according to a secret common knowledge between the communicating entities. Hence, artificial noise misleads the eavesdroppers, and decreases their signal-to-noise-ratio. As a result, secrecy capacity of the system is improved. Finally, power allocation among friendly jamming and main signal is proposed to ensure that suggested scheme enhances secrecy

Distributed space-time coding including the golden code with application in cooperative networks

This thesis presents new methodologies to improve performance of wireless cooperative networks using the Golden Code. As a form of space-time coding, the Golden Code can achieve diversity-multiplexing tradeoff and the data rate can be twice that of the Alamouti code. In practice, however, asynchronism between relay nodes may reduce performance and channel quality can be degraded from certain antennas. Firstly, a simple offset transmission scheme, which employs full interference cancellation (FIC) and orthogonal frequency division multiplexing (OFDM), is enhanced through the use of four relay nodes and receiver processing to mitigate asynchronism. Then, the potential reduction in diversity gain due to the dependent channel matrix elements in the distributed Golden Code transmission, and the rate penalty of multihop transmission, are mitigated by relay selection based on two-way transmission. The Golden Code is also implemented in an asynchronous one-way relay network over frequency flat and selective channels, and a simple approach to overcome asynchronism is proposed. In one-way communication with computationally efficient sphere decoding, the maximum of the channel parameter means is shown to achieve the best performance for the relay selection through bit error rate simulations. Secondly, to reduce the cost of hardware when multiple antennas are available in a cooperative network, multi-antenna selection is exploited. In this context, maximum-sum transmit antenna selection is proposed. End-to-end signal-to-noise ratio (SNR) is calculated and outage probability analysis is performed when the links are modelled as Rayleigh fading frequency flat channels. The numerical results support the analysis and for a MIMO system maximum-sum selection is shown to outperform maximum-minimum selection. Additionally, pairwise error probability (PEP) analysis is performed for maximum-sum transmit antenna selection with the Golden Code and the diversity order is obtained. Finally, with the assumption of fibre-connected multiple antennas with finite buffers, multiple-antenna selection is implemented on the basis of maximum-sum antenna selection. Frequency flat Rayleigh fading channels are assumed together with a decode and forward transmission scheme. Outage probability analysis is performed by exploiting the steady-state stationarity of a Markov Chain model

Advanced Algebraic Concepts for Efficient Multi-Channel Signal Processing

Unsere moderne Gesellschaft ist Zeuge eines fundamentalen Wandels in der Art und Weise wie wir mit Technologie interagieren. Geräte werden zunehmend intelligenter - sie verfügen über mehr und mehr Rechenleistung und häufiger über eigene Kommunikationsschnittstellen. Das beginnt bei einfachen Haushaltsgeräten und reicht über Transportmittel bis zu großen überregionalen Systemen wie etwa dem Stromnetz. Die Erfassung, die Verarbeitung und der Austausch digitaler Informationen gewinnt daher immer mehr an Bedeutung. Die Tatsache, dass ein wachsender Anteil der Geräte heutzutage mobil und deshalb batteriebetrieben ist, begründet den Anspruch, digitale Signalverarbeitungsalgorithmen besonders effizient zu gestalten. Dies kommt auch dem Wunsch nach einer Echtzeitverarbeitung der großen anfallenden Datenmengen zugute. Die vorliegende Arbeit demonstriert Methoden zum Finden effizienter algebraischer Lösungen für eine Vielzahl von Anwendungen mehrkanaliger digitaler Signalverarbeitung. Solche Ansätze liefern nicht immer unbedingt die bestmögliche Lösung, kommen dieser jedoch häufig recht nahe und sind gleichzeitig bedeutend einfacher zu beschreiben und umzusetzen. Die einfache Beschreibungsform ermöglicht eine tiefgehende Analyse ihrer Leistungsfähigkeit, was für den Entwurf eines robusten und zuverlässigen Systems unabdingbar ist. Die Tatsache, dass sie nur gebräuchliche algebraische Hilfsmittel benötigen, erlaubt ihre direkte und zügige Umsetzung und den Test unter realen Bedingungen. Diese Grundidee wird anhand von drei verschiedenen Anwendungsgebieten demonstriert. Zunächst wird ein semi-algebraisches Framework zur Berechnung der kanonisch polyadischen (CP) Zerlegung mehrdimensionaler Signale vorgestellt. Dabei handelt es sich um ein sehr grundlegendes Werkzeug der multilinearen Algebra mit einem breiten Anwendungsspektrum von Mobilkommunikation über Chemie bis zur Bildverarbeitung. Verglichen mit existierenden iterativen Lösungsverfahren bietet das neue Framework die Möglichkeit, den Rechenaufwand und damit die Güte der erzielten Lösung zu steuern. Es ist außerdem weniger anfällig gegen eine schlechte Konditionierung der Ausgangsdaten. Das zweite Gebiet, das in der Arbeit besprochen wird, ist die unterraumbasierte hochauflösende Parameterschätzung für mehrdimensionale Signale, mit Anwendungsgebieten im RADAR, der Modellierung von Wellenausbreitung, oder bildgebenden Verfahren in der Medizin. Es wird gezeigt, dass sich derartige mehrdimensionale Signale mit Tensoren darstellen lassen. Dies erlaubt eine natürlichere Beschreibung und eine bessere Ausnutzung ihrer Struktur als das mit Matrizen möglich ist. Basierend auf dieser Idee entwickeln wir eine tensor-basierte Schätzung des Signalraums, welche genutzt werden kann um beliebige existierende Matrix-basierte Verfahren zu verbessern. Dies wird im Anschluss exemplarisch am Beispiel der ESPRIT-artigen Verfahren gezeigt, für die verbesserte Versionen vorgeschlagen werden, die die mehrdimensionale Struktur der Daten (Tensor-ESPRIT), nichzirkuläre Quellsymbole (NC ESPRIT), sowie beides gleichzeitig (NC Tensor-ESPRIT) ausnutzen. Um die endgültige Schätzgenauigkeit objektiv einschätzen zu können wird dann ein Framework für die analytische Beschreibung der Leistungsfähigkeit beliebiger ESPRIT-artiger Algorithmen diskutiert. Verglichen mit existierenden analytischen Ausdrücken ist unser Ansatz allgemeiner, da keine Annahmen über die statistische Verteilung von Nutzsignal und Rauschen benötigt werden und die Anzahl der zur Verfügung stehenden Schnappschüsse beliebig klein sein kann. Dies führt auf vereinfachte Ausdrücke für den mittleren quadratischen Schätzfehler, die Schlussfolgerungen über die Effizienz der Verfahren unter verschiedenen Bedingungen zulassen. Das dritte Anwendungsgebiet ist der bidirektionale Datenaustausch mit Hilfe von Relay-Stationen. Insbesondere liegt hier der Fokus auf Zwei-Wege-Relaying mit Hilfe von Amplify-and-Forward-Relays mit mehreren Antennen, da dieser Ansatz ein besonders gutes Kosten-Nutzen-Verhältnis verspricht. Es wird gezeigt, dass sich die nötige Kanalkenntnis mit einem einfachen algebraischen Tensor-basierten Schätzverfahren gewinnen lässt. Außerdem werden Verfahren zum Finden einer günstigen Relay-Verstärkungs-Strategie diskutiert. Bestehende Ansätze basieren entweder auf komplexen numerischen Optimierungsverfahren oder auf Ad-Hoc-Ansätzen die keine zufriedenstellende Bitfehlerrate oder Summenrate liefern. Deshalb schlagen wir algebraische Ansätze zum Finden der Relayverstärkungsmatrix vor, die von relevanten Systemmetriken inspiriert sind und doch einfach zu berechnen sind. Wir zeigen das algebraische ANOMAX-Verfahren zum Erreichen einer niedrigen Bitfehlerrate und seine Modifikation RR-ANOMAX zum Erreichen einer hohen Summenrate. Für den Spezialfall, in dem die Endgeräte nur eine Antenne verwenden, leiten wir eine semi-algebraische Lösung zum Finden der Summenraten-optimalen Strategie (RAGES) her. Anhand von numerischen Simulationen wird die Leistungsfähigkeit dieser Verfahren bezüglich Bitfehlerrate und erreichbarer Datenrate bewertet und ihre Effektivität gezeigt.Modern society is undergoing a fundamental change in the way we interact with technology. More and more devices are becoming "smart" by gaining advanced computation capabilities and communication interfaces, from household appliances over transportation systems to large-scale networks like the power grid. Recording, processing, and exchanging digital information is thus becoming increasingly important. As a growing share of devices is nowadays mobile and hence battery-powered, a particular interest in efficient digital signal processing techniques emerges. This thesis contributes to this goal by demonstrating methods for finding efficient algebraic solutions to various applications of multi-channel digital signal processing. These may not always result in the best possible system performance. However, they often come close while being significantly simpler to describe and to implement. The simpler description facilitates a thorough analysis of their performance which is crucial to design robust and reliable systems. The fact that they rely on standard algebraic methods only allows their rapid implementation and test under real-world conditions. We demonstrate this concept in three different application areas. First, we present a semi-algebraic framework to compute the Canonical Polyadic (CP) decompositions of multidimensional signals, a very fundamental tool in multilinear algebra with applications ranging from chemistry over communications to image compression. Compared to state-of-the art iterative solutions, our framework offers a flexible control of the complexity-accuracy trade-off and is less sensitive to badly conditioned data. The second application area is multidimensional subspace-based high-resolution parameter estimation with applications in RADAR, wave propagation modeling, or biomedical imaging. We demonstrate that multidimensional signals can be represented by tensors, providing a convenient description and allowing to exploit the multidimensional structure in a better way than using matrices only. Based on this idea, we introduce the tensor-based subspace estimate which can be applied to enhance existing matrix-based parameter estimation schemes significantly. We demonstrate the enhancements by choosing the family of ESPRIT-type algorithms as an example and introducing enhanced versions that exploit the multidimensional structure (Tensor-ESPRIT), non-circular source amplitudes (NC ESPRIT), and both jointly (NC Tensor-ESPRIT). To objectively judge the resulting estimation accuracy, we derive a framework for the analytical performance assessment of arbitrary ESPRIT-type algorithms by virtue of an asymptotical first order perturbation expansion. Our results are more general than existing analytical results since we do not need any assumptions about the distribution of the desired signal and the noise and we do not require the number of samples to be large. At the end, we obtain simplified expressions for the mean square estimation error that provide insights into efficiency of the methods under various conditions. The third application area is bidirectional relay-assisted communications. Due to its particularly low complexity and its efficient use of the radio resources we choose two-way relaying with a MIMO amplify and forward relay. We demonstrate that the required channel knowledge can be obtained by a simple algebraic tensor-based channel estimation scheme. We also discuss the design of the relay amplification matrix in such a setting. Existing approaches are either based on complicated numerical optimization procedures or on ad-hoc solutions that to not perform well in terms of the bit error rate or the sum-rate. Therefore, we propose algebraic solutions that are inspired by these performance metrics and therefore perform well while being easy to compute. For the MIMO case, we introduce the algebraic norm maximizing (ANOMAX) scheme, which achieves a very low bit error rate, and its extension Rank-Restored ANOMAX (RR-ANOMAX) that achieves a sum-rate close to an upper bound. Moreover, for the special case of single antenna terminals we derive the semi-algebraic RAGES scheme which finds the sum-rate optimal relay amplification matrix based on generalized eigenvectors. Numerical simulations evaluate the resulting system performance in terms of bit error rate and system sum rate which demonstrates the effectiveness of the proposed algebraic solutions