52 research outputs found
Information Theory of underspread WSSUS channels
The chapter focuses on the ultimate limit on the rate of reliable communication through Rayleigh-fading channels that satisfy the wide-sense stationary (WSS) and uncorrelated scattering (US) assumptions and are underspread. Therefore, the natural setting is an information-theoretic one, and the performance metric is channel capacity. The family of Rayleigh-fading underspread WSSUS channels constitutes a good model for real-world wireless channels: their stochastic properties, like amplitude and phase distributions match channel measurement results. The Rayleigh-fading and the WSSUS assumptions imply that the stochastic properties of the channel are fully described by a two-dimensional power spectral density (PSD) function, often referred to as scattering function. The underspread assumption implies that the scattering function is highly concentrated in the delay-Doppler plane. Two important aspects need to be accounted for by a model that aims at being realistic: neither the transmitter nor the receiver knows the realization of the channel; and the peak power of the transmit signal is limited. Based on these two aspects the chapter provides an information-theoretic analysis of Rayleigh-fading underspread WSSUS channels in the noncoherent setting, under the additional assumption that the transmit signal is peak-constrained
Characterisation and Modelling of Indoor and Short-Range MIMO Communications
Over the last decade, we have witnessed the rapid evolution of Multiple-Input Multiple-Output
(MIMO) systems which promise to break the frontiers of conventional architectures and deliver
high throughput by employing more than one element at the transmitter (Tx) and receiver (Rx)
in order to exploit the spatial domain. This is achieved by transmitting simultaneous data
streams from different elements which impinge on the Rx with ideally unique spatial signatures
as a result of the propagation paths’ interactions with the surrounding environment. This thesis
is oriented to the statistical characterisation and modelling of MIMO systems and particularly
of indoor and short-range channels which lend themselves a plethora of modern applications,
such as wireless local networks (WLANs), peer-to-peer and vehicular communications.
The contributions of the thesis are detailed below. Firstly, an indoor channel model is proposed
which decorrelates the full spatial correlation matrix of a 5.2 GHzmeasuredMIMO channel and
thereafter assigns the Nakagami-m distribution on the resulting uncorrelated eigenmodes. The
choice of the flexible Nakagami-m density was found to better fit the measured data compared
to the commonly used Rayleigh and Ricean distributions. In fact, the proposed scheme captures
the spatial variations of the measured channel reasonably well and systematically outperforms
two known analytical models in terms of information theory and link-level performance.
The second contribution introduces an array processing scheme, namely the three-dimensional
(3D) frequency domain Space Alternating Generalised Expectation Maximisation (FD-SAGE)
algorithm for jointly extracting the dominant paths’ parameters. The scheme exhibits a satisfactory
robustness in a synthetic environment even for closely separated sources and is applicable
to any array geometry as long as its manifold is known. The algorithm is further applied to the
same set of raw data so that different global spatial parameters of interest are determined; these
are the multipath clustering, azimuth spreads and inter-dependency of the spatial domains.
The third contribution covers the case of short-range communications which have nowadays
emerged as a hot topic in the area of wireless networks. The main focus is on dual-branch
MIMO Ricean systems for which a design methodology to achieve maximum capacities in the
presence of Line-of-Sight (LoS) components is proposed. Moreover, a statistical eigenanalysis
of these configurations is performed and novel closed-formulae for the marginal eigenvalue
and condition number statistics are derived. These formulae are further used to develop an
adaptive detector (AD) whose aim is to reduce the feasibility cost and complexity of Maximum
Likelihood (ML)-based MIMO receivers.
Finally, a tractable novel upper bound on the ergodic capacity of the above mentioned MIMO
systems is presented which relies on a fundamental power constraint. The bound is sufficiently
tight and applicable for arbitrary rank of the mean channel matrix, Signal-to-Noise ratio (SNR)
and takes the effects of spatial correlation at both ends into account. More importantly, it
includes previously reported capacity bounds as special cases
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Adaptive Coded Modulation Classification and Spectrum Sensing for Cognitive Radio Systems. Adaptive Coded Modulation Techniques for Cognitive Radio Using Kalman Filter and Interacting Multiple Model Methods
The current and future trends of modern wireless communication systems place heavy demands on fast data transmissions in order to satisfy end users’ requirements anytime, anywhere. Such demands are obvious in recent applications such as smart phones, long term evolution (LTE), 4 & 5 Generations (4G & 5G), and worldwide interoperability for microwave access (WiMAX) platforms, where robust coding and modulations are essential especially in streaming on-line video material, social media and gaming. This eventually resulted in extreme exhaustion imposed on the frequency spectrum as a rare natural resource due to stagnation in current spectrum management policies. Since its advent in the late 1990s, cognitive radio (CR) has been conceived as an enabling technology aiming at the efficient utilisation of frequency spectrum that can lead to potential direct spectrum access (DSA) management. This is mainly attributed to its internal capabilities inherited from the concept of software defined radio (SDR) to sniff its surroundings, learn and adapt its operational parameters accordingly. CR systems (CRs) may commonly comprise one or all of the following core engines that characterise their architectures; namely, adaptive coded modulation (ACM), automatic modulation classification (AMC) and spectrum sensing (SS).
Motivated by the above challenges, this programme of research is primarily aimed at the design and development of new paradigms to help improve the adaptability of CRs and thereby achieve the desirable signal processing tasks at the physical layer of the above core engines. Approximate modelling of Rayleigh and finite state Markov channels (FSMC) with a new concept borrowed from econometric studies have been approached. Then insightful channel estimation by using Kalman filter (KF) augmented with interacting multiple model (IMM) has been examined for the purpose of robust adaptability, which is applied for the first time in wireless communication systems. Such new IMM-KF combination has been facilitated in the feedback channel between wireless transmitter and receiver to adjust the transmitted power, by using a water-filling (WF) technique, and constellation pattern and rate in the ACM algorithm. The AMC has also benefited from such IMM-KF integration to boost the performance against conventional parametric estimation methods such as maximum likelihood estimate (MLE) for channel interrogation and the estimated parameters of both inserted into the ML classification algorithm. Expectation-maximisation (EM) has been applied to examine unknown transmitted modulation sequences and channel parameters in tandem. Finally, the non-parametric multitaper method (MTM) has been thoroughly examined for spectrum estimation (SE) and SS, by relying on Neyman-Pearson (NP) detection principle for hypothesis test, to allow licensed primary users (PUs) to coexist with opportunistic unlicensed secondary users (SUs) in the same frequency bands of interest without harmful effects. The performance of the above newly suggested paradigms have been simulated and assessed under various transmission settings and revealed substantial improvements
MIMO transmission for 4G wireless communications
Tese de doutoramento. Engenharia Electrotécnica e de Computadores. Faculdade de Engenharia. Universidade do Porto. 200
Transmission strategies for broadband wireless systems with MMSE turbo equalization
This monograph details efficient transmission strategies for single-carrier wireless broadband communication systems employing iterative (turbo) equalization. In particular, the first part focuses on the design and analysis of low complexity and robust MMSE-based turbo equalizers operating in the frequency domain. Accordingly, several novel receiver schemes are presented which improve the convergence properties and error performance over the existing turbo equalizers. The second part discusses concepts and algorithms that aim to increase the power and spectral efficiency of the communication system by efficiently exploiting the available resources at the transmitter side based upon the channel conditions. The challenging issue encountered in this context is how the transmission rate and power can be optimized, while a specific convergence constraint of the turbo equalizer is guaranteed.Die vorliegende Arbeit beschäftigt sich mit dem Entwurf und der Analyse von
effizienten Übertragungs-konzepten für drahtlose, breitbandige
Einträger-Kommunikationssysteme mit iterativer (Turbo-) Entzerrung und
Kanaldekodierung. Dies beinhaltet einerseits die Entwicklung von
empfängerseitigen Frequenzbereichs-entzerrern mit geringer Komplexität
basierend auf dem Prinzip der Soft Interference Cancellation Minimum-Mean
Squared-Error (SC-MMSE) Filterung und andererseits den Entwurf von
senderseitigen Algorithmen, die durch Ausnutzung von
Kanalzustandsinformationen die Bandbreiten- und Leistungseffizienz in Ein-
und Mehrnutzersystemen mit Mehrfachantennen (sog. Multiple-Input
Multiple-Output (MIMO)) verbessern.
Im ersten Teil dieser Arbeit wird ein allgemeiner Ansatz für Verfahren zur
Turbo-Entzerrung nach dem Prinzip der linearen MMSE-Schätzung, der
nichtlinearen MMSE-Schätzung sowie der kombinierten MMSE- und
Maximum-a-Posteriori (MAP)-Schätzung vorgestellt. In diesem Zusammenhang
werden zwei neue Empfängerkonzepte, die eine Steigerung der
Leistungsfähigkeit und Verbesserung der Konvergenz in Bezug auf
existierende SC-MMSE Turbo-Entzerrer in verschiedenen Kanalumgebungen
erzielen, eingeführt. Der erste Empfänger - PDA SC-MMSE - stellt eine
Kombination aus dem Probabilistic-Data-Association (PDA) Ansatz und dem
bekannten SC-MMSE Entzerrer dar. Im Gegensatz zum SC-MMSE nutzt der PDA
SC-MMSE eine interne Entscheidungsrückführung, so dass zur Unterdrückung
von Interferenzen neben den a priori Informationen der Kanaldekodierung
auch weiche Entscheidungen der vorherigen Detektions-schritte
berücksichtigt werden. Durch die zusätzlich interne
Entscheidungsrückführung erzielt der PDA SC-MMSE einen wesentlichen Gewinn
an Performance in räumlich unkorrelierten MIMO-Kanälen gegenüber dem
SC-MMSE, ohne dabei die Komplexität des Entzerrers wesentlich zu erhöhen.
Der zweite Empfänger - hybrid SC-MMSE - bildet eine Verknüpfung von
gruppenbasierter SC-MMSE Frequenzbereichsfilterung und MAP-Detektion.
Dieser Empfänger besitzt eine skalierbare Berechnungskomplexität und weist
eine hohe Robustheit gegenüber räumlichen Korrelationen in MIMO-Kanälen
auf. Die numerischen Ergebnisse von Simulationen basierend auf Messungen
mit einem Channel-Sounder in Mehrnutzerkanälen mit starken räumlichen
Korrelationen zeigen eindrucksvoll die Überlegenheit des hybriden
SC-MMSE-Ansatzes gegenüber dem konventionellen SC-MMSE-basiertem Empfänger.
Im zweiten Teil wird der Einfluss von System- und Kanalmodellparametern auf
die Konvergenzeigenschaften der vorgestellten iterativen Empfänger mit
Hilfe sogenannter Korrelationsdiagramme untersucht. Durch semi-analytische
Berechnungen der Entzerrer- und Kanaldecoder-Korrelationsfunktionen wird
eine einfache Berechnungsvorschrift zur Vorhersage der
Bitfehlerwahrscheinlichkeit von SC-MMSE und PDA SC-MMSE Turbo Entzerrern
für MIMO-Fadingkanäle entwickelt. Des Weiteren werden zwei Fehlerschranken
für die Ausfallwahrscheinlichkeit der Empfänger vorgestellt. Die
semi-analytische Methode und die abgeleiteten Fehlerschranken ermöglichen
eine aufwandsgeringe Abschätzung sowie Optimierung der Leistungsfähigkeit
des iterativen Systems.
Im dritten und abschließenden Teil werden Strategien zur Raten- und
Leistungszuweisung in Kommunikationssystemen mit konventionellen iterativen
SC-MMSE Empfängern untersucht. Zunächst wird das Problem der Maximierung
der instantanen Summendatenrate unter der Berücksichtigung der Konvergenz
des iterativen Empfängers für einen Zweinutzerkanal mit fester
Leistungsallokation betrachtet. Mit Hilfe des Flächentheorems von
Extrinsic-Information-Transfer (EXIT)-Funktionen wird eine obere Schranke
für die erreichbare Ratenregion hergeleitet. Auf Grundlage dieser Schranke
wird ein einfacher Algorithmus entwickelt, der für jeden Nutzer aus einer
Menge von vorgegebenen Kanalcodes mit verschiedenen Codierraten denjenigen
auswählt, der den instantanen Datendurchsatz des Mehrnutzersystems
verbessert. Neben der instantanen Ratenzuweisung wird auch ein
ausfallbasierter Ansatz zur Ratenzuweisung entwickelt. Hierbei erfolgt die
Auswahl der Kanalcodes für die Nutzer unter Berücksichtigung der Einhaltung
einer bestimmten Ausfallwahrscheinlichkeit (outage probability) des
iterativen Empfängers. Des Weiteren wird ein neues Entwurfskriterium für
irreguläre Faltungscodes hergeleitet, das die Ausfallwahrscheinlichkeit von
Turbo SC-MMSE Systemen verringert und somit die Zuverlässigkeit der
Datenübertragung erhöht. Eine Reihe von Simulationsergebnissen von
Kapazitäts- und Durchsatzberechnungen werden vorgestellt, die die
Wirksamkeit der vorgeschlagenen Algorithmen und Optimierungsverfahren in
Mehrnutzerkanälen belegen. Abschließend werden außerdem verschiedene
Maßnahmen zur Minimierung der Sendeleistung in Einnutzersystemen mit
senderseitiger Singular-Value-Decomposition (SVD)-basierter Vorcodierung
untersucht. Es wird gezeigt, dass eine Methode, welche die Leistungspegel
des Senders hinsichtlich der Bitfehlerrate des iterativen Empfängers
optimiert, den konventionellen Verfahren zur Leistungszuweisung überlegen
ist
Capacity and performance analysis of advanced multiple antenna communication systems
Multiple-input multiple-output (MIMO) antenna systems have been shown to be able to substantially
increase date rate and improve reliability without extra spectrum and power resources. The increasing
popularity and enormous prospect of MIMO technology calls for a better understanding of the performance
of MIMO systems operating over practical environments. Motivated by this, this thesis provides
an analytical characterization of the capacity and performance of advanced MIMO antenna systems.
First, the ergodic capacity of MIMO Nakagami-m fading channels is investigated. A unified way of
deriving ergodic capacity bounds is developed under the majorization theory framework. The key idea is
to study the ergodic capacity through the distribution of the diagonal elements of the quadratic channel
HHy which is relatively easy to handle, avoiding the need of the eigenvalue distribution of the channel
matrix which is extremely difficult to obtain. The proposed method is first applied on the conventional
point-to-point MIMO systems under Nakagami-m fading, and later extended to the more general distributed
MIMO systems.
Second, the ergodic capacity of MIMO multi-keyhole and MIMO amplify-and-forward (AF) dual-hop
systems is studied. A set of new statistical properties involving product of random complex Gaussian
matrix, i.e., probability density function (p.d.f.) of an unordered eigenvalue, p.d.f. of the maximum
eigenvalue, expected determinant and log-determinant, is derived. Based on these, analytical closedform
expressions for the ergodic capacity of the systems are obtained and the connection between the
product channels and conventional point-to-point MIMO channels is also revealed.
Finally, the effect of co-channel interference is investigated. First, the performance of optimum combining
(OC) systems operating in Rayleigh-product channels is analyzed based on novel closed-form
expression of the cumulative distribution function (c.d.f.) of the maximum eigenvalue of the resultant
channel matrix. Then, for MIMO Rician channels and MIMO Rayleigh-product channels, the ergodic capacity
at low signal-to-noise ratio (SNR) regime is studied, and the impact of various system parameters,
such as transmit and receive antenna number, Rician factor, channel mean matrix and interference-tonoise-
ratio, is examined
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