20 research outputs found
Advanced receivers for distributed cooperation in mobile ad hoc networks
Mobile ad hoc networks (MANETs) are rapidly deployable wireless communications systems, operating with minimal coordination in order to avoid spectral efficiency losses caused by overhead. Cooperative transmission schemes are attractive for MANETs, but the distributed nature of such protocols comes with an increased level of interference, whose impact is further amplified by the need to push the limits of energy and spectral efficiency. Hence, the impact of interference has to be mitigated through with the use PHY layer signal processing algorithms with reasonable computational complexity. Recent advances in iterative digital receiver design techniques exploit approximate Bayesian inference and derivative message passing techniques to improve the capabilities of well-established turbo detectors. In particular, expectation propagation (EP) is a flexible technique which offers attractive complexity-performance trade-offs in situations where conventional belief propagation is limited by computational complexity. Moreover, thanks to emerging techniques in deep learning, such iterative structures are cast into deep detection networks, where learning the algorithmic hyper-parameters further improves receiver performance. In this thesis, EP-based finite-impulse response decision feedback equalizers are designed, and they achieve significant improvements, especially in high spectral efficiency applications, over more conventional turbo-equalization techniques, while having the advantage of being asymptotically predictable. A framework for designing frequency-domain EP-based receivers is proposed, in order to obtain detection architectures with low computational complexity. This framework is theoretically and numerically analysed with a focus on channel equalization, and then it is also extended to handle detection for time-varying channels and multiple-antenna systems. The design of multiple-user detectors and the impact of channel estimation are also explored to understand the capabilities and limits of this framework. Finally, a finite-length performance prediction method is presented for carrying out link abstraction for the EP-based frequency domain equalizer. The impact of accurate physical layer modelling is evaluated in the context of cooperative broadcasting in tactical MANETs, thanks to a flexible MAC-level simulato
Mobile and Wireless Communications
Mobile and Wireless Communications have been one of the major revolutions of the late twentieth century. We are witnessing a very fast growth in these technologies where mobile and wireless communications have become so ubiquitous in our society and indispensable for our daily lives. The relentless demand for higher data rates with better quality of services to comply with state-of-the art applications has revolutionized the wireless communication field and led to the emergence of new technologies such as Bluetooth, WiFi, Wimax, Ultra wideband, OFDMA. Moreover, the market tendency confirms that this revolution is not ready to stop in the foreseen future. Mobile and wireless communications applications cover diverse areas including entertainment, industrialist, biomedical, medicine, safety and security, and others, which definitely are improving our daily life. Wireless communication network is a multidisciplinary field addressing different aspects raging from theoretical analysis, system architecture design, and hardware and software implementations. While different new applications are requiring higher data rates and better quality of service and prolonging the mobile battery life, new development and advanced research studies and systems and circuits designs are necessary to keep pace with the market requirements. This book covers the most advanced research and development topics in mobile and wireless communication networks. It is divided into two parts with a total of thirty-four stand-alone chapters covering various areas of wireless communications of special topics including: physical layer and network layer, access methods and scheduling, techniques and technologies, antenna and amplifier design, integrated circuit design, applications and systems. These chapters present advanced novel and cutting-edge results and development related to wireless communication offering the readers the opportunity to enrich their knowledge in specific topics as well as to explore the whole field of rapidly emerging mobile and wireless networks. We hope that this book will be useful for students, researchers and practitioners in their research studies
Formes d'ondes avancées et traitements itératifs pour les canaux non linéaires satellites
L'augmentation de l'efficacité spectrale des transmissions mono-porteuses sur un lien de diffusion par satellite est devenu un défi d'envergure afin de pallier la demande croissante en débits de transmission. Si des techniques émergentes de transmissions encouragent l'utilisation de modulations à ordre élevé telles que les modulations de phase et d'amplitude (APSK), certaines dégradations sont encourues lors du traitement à bord du satellite. En effet, en raison de l'utilisation d'amplificateurs de puissance ainsi que de filtres à mémoires, les modulations d'ordre élevé subissent des distorsions non-linéaires dues à la fluctuation de leur enveloppe, ce qui nécessite des traitements au sein de l'émetteur ou bien au sein du récepteur. Dans cette thèse, nous nous intéressons au traitement de l'interférence non-linéaire au sein du récepteur, avec une attention particulière aux égaliseurs itératifs qui améliorent les performances du système au prix d'une complexité élevée. A partir du modèle temporel des interférences non-linéaires induites par l'amplificateur de puissance, des algorithmes de réception optimaux et sous optimaux sont dérivés, et leurs performances comparées. Des égaliseurs à complexité réduite sont aussi étudiés dans le but d'atteindre un compromis performances-complexité satisfaisant. Ensuite, un modèle des non-linéarités est dérivé dans le domaine fréquentiel, et les égaliseurs correspondants sont présentés. Dans un second temps, nous analysons et dérivons des récepteurs itératifs pour l'interférence entre symboles non linéaire. L'objectif est d'optimiser les polynômes de distributions d'un code externe basé sur les codes de contrôle de parité à faible densité (LDPC) afin de coller au mieux à la sortie de l'égaliseur. Le récepteur ainsi optimisé atteint de meilleures performances comparé à un récepteur non optimisé pour le canal non-linéaire. Finalement, nous nous intéressons à une classe spécifique de techniques de transmissions mono-porteuse basée sur le multiplexage par division de fréquence (SC-OFDM) pour les liens satellites. L'avantage de ces formes d'ondes réside dans l'efficacité de leur égaliseur dans le domaine fréquentiel. Des formules analytiques de la densité spectrale de puissance et du rapport signal sur bruit et interférence sont dérivées et utilisées afin de prédire les performances du système. ABSTRACT : Increasing both the data rate and power efficiency of single carrier transmissions over broadcast satellite links has become a challenging issue to comply with the urging demand of higher transmission rates. If emerging transmission techniques encourage the use of high order modulations such as Amplitude and Phase Shift Keying (APSK) and Quadrature Amplitude Modulation (QAM), some channel impairments arise due to onboard satellite processing. Indeed, due to satellite transponder Power Amplifiers (PA) as well as transmission filters, high order modulations incur non linear distortions due to their high envelope fluctuations which require specific processing either at the transmitter or at the receiver. In this thesis, we investigate on non linear interference mitigation at the receiver with a special focus on iterative equalizers which dramatically enhance the performance at the cost of additional complexity. Based on the time domain model of the non linear interference induced by the PA, optimal and sub-optimal receiving algorithms are proposed and their performance compared. Low complexity implementations are also investigated for the sake of a better complexity-performance trade-off. Then, a non linear frequency domain model is derived and the corresponding frequency equalizers are investigated. In the second part, we analyse and design an iterative receiver for the non linear Inter Symbol Interference (ISI) channel. The objective is to optimize an outer Low Density Parity Check (LDPC) code distribution polynomials so as to best fit the inner equalizer Extrinsic information. The optimized receiver is shown to achieve better performance compared to a code only optimized for linear ISI channel. Finally, we investigate on a specific class of single carrier transmissions relying on Single Carrier Orthogonal Frequency Division Multiplexing (SCO-FDM) for satellite downlink. The advantage of such waveforms lies in their practical receiver implementation in the frequency domain. General analytical formulas of the power spectral density and signal to noise and interference ratio are derived and used to predict the bit error rate for frequency selective multiplexers
Asymptotically optimal low-complexity SC-FDE with noise prediction in data-like improper-complex interference
In this paper, single-carrier (SC) block transmission of improper-complex data symbols is considered over a multiple-input multiple-output (MIMO) frequency-selective channel with data-like cochannel interference (CCI). To exploit the cyclostationarity and impropriety of the desired and the interfering signals, an equalizer is designed that oversamples the received signal and then processes the sampled block by using widely-linear (WL) feedforward (FF) and noise-predicting feedback (NP-FB) filters. For the given equalizer structure, the minimum mean-squared error (MMSE)-optimal WL FF and NP-FB filters have high computational complexity due to the augmented correlation matrix of the data-like CCI in the received signal. Motivated by the asymptotic property of the correlation matrix, we approximate in the frequency domain the matrix by a block matrix with diagonal blocks. This leads to the low-complexity WL design of a frequency-domain FF filter and a causally noise-predicting FB filter. It is shown that this MIMO SC frequency-domain equalizer with noise prediction is asymptotically optimal in the sense that the average mean-squared error converges to that of the MMSE-optimal equalizer as the block length tends to infinity. Numerical results show that the proposed equalizer performs well even with a moderate block length.114Nsciescopu
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
Radio Communications
In the last decades the restless evolution of information and communication technologies (ICT) brought to a deep transformation of our habits. The growth of the Internet and the advances in hardware and software implementations modified our way to communicate and to share information. In this book, an overview of the major issues faced today by researchers in the field of radio communications is given through 35 high quality chapters written by specialists working in universities and research centers all over the world. Various aspects will be deeply discussed: channel modeling, beamforming, multiple antennas, cooperative networks, opportunistic scheduling, advanced admission control, handover management, systems performance assessment, routing issues in mobility conditions, localization, web security. Advanced techniques for the radio resource management will be discussed both in single and multiple radio technologies; either in infrastructure, mesh or ad hoc networks
1999 Flight Mechanics Symposium
This conference publication includes papers and abstracts presented at the Flight Mechanics Symposium held on May 18-20, 1999. Sponsored by the Guidance, Navigation and Control Center of Goddard Space Flight Center, this symposium featured technical papers on a wide range of issues related to orbit-attitude prediction, determination, and control; attitude sensor calibration; attitude determination error analysis; attitude dynamics; and orbit decay and maneuver strategy. Government, industry, and the academic community participated in the preparation and presentation of these papers
Z-Numbers-Based Approach to Hotel Service Quality Assessment
In this study, we are analyzing the possibility of using Z-numbers for
measuring the service quality and decision-making for quality improvement in the
hotel industry. Techniques used for these purposes are based on consumer evalu-
ations - expectations and perceptions. As a rule, these evaluations are expressed
in crisp numbers (Likert scale) or fuzzy estimates. However, descriptions of the
respondent opinions based on crisp or fuzzy numbers formalism not in all cases
are relevant. The existing methods do not take into account the degree of con-
fidence of respondents in their assessments. A fuzzy approach better describes
the uncertainties associated with human perceptions and expectations. Linguis-
tic values are more acceptable than crisp numbers. To consider the subjective
natures of both service quality estimates and confidence degree in them, the two-
component Z-numbers Z = (A, B) were used. Z-numbers express more adequately
the opinion of consumers. The proposed and computationally efficient approach
(Z-SERVQUAL, Z-IPA) allows to determine the quality of services and iden-
tify the factors that required improvement and the areas for further development.
The suggested method was applied to evaluate the service quality in small and
medium-sized hotels in Turkey and Azerbaijan, illustrated by the example