45 research outputs found
Low-complexity soft-decision feedback turbo equalization for multilevel modulations
This dissertation proposes two new decision feedback equalization schemes suitable for multilevel modulation systems employing turbo equalization. One is soft-decision feedback equalization (SDFE) that takes into account the reliability of both soft a priori information and soft decisions of the data symbols. The proposed SDFE exhibits lower signal to noise ratio (SNR) threshold that is required for water fall bit error rate (BER) and much faster convergence than the near-optimal exact minimum mean square error linear equalizer (Exact-MMSE-LE) for high-order constellation modulations. The proposed SDFE also offers a low computational complexity compared to the Exact-MMSE-LE. The drawback of the SDFE is that its coefficients cannot reach the matched filter bound (MFB) and therefore after a large number of iterations (e.g. 10), its performance becomes inferior to that of the Exact-MMSE-LE. Therefore, soft feedback intersymbol interference (ISI) canceller-based (SIC) structure is investigated. The SIC structure not only exhibits the same low complexity, low SNR threshold and fast convergence as the SDFE but also reaches the MFB after a large number of iterations. Both theoretical analysis and numerical simulations demonstrate why the SIC achieves MFB while the SDFE cannot. These two turbo equalization structures are also extended from single-input single-output (SISO) systems to multiple-input multiple-output (MIMO) systems and applied in high data-rate underwater acoustic (UWA) communications --Abstract, page iv
Asymptotic Analysis and Design of Iterative Receivers for Non Linear ISI Channels
International audienceIn this paper, iterative receiver analysis and design for non linear satellite channels is investigated. To do so, an EXtrinsic Information Transfer (EXIT) chart-based optimization is applied using two major assumptions: the equalizer outputs follow a Gaussian Mixture distribution since we use non-binary modulations and partial interleavers are used between the Low Density Parity Check (LDPC) code and the mapper. Achievable rates, performance and thresholds of the optimized receiver are analysed. The objective in fine is to answer the question: Is it worth optimizing an iterative receiver for non linear satellite channels
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
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
Non-iterative joint decoding and signal processing: universal coding approach for channels with memory
A non-iterative receiver is proposed to achieve near capacity performance on intersymbol
interference (ISI) channels. There are two main ingredients in the proposed
design. i) The use of a novel BCJR-DFE equalizer which produces optimal soft
estimates of the inputs to the ISI channel given all the observations from the channel
and L past symbols exactly, where L is the memory of the ISI channel. ii) The
use of an encoder structure that ensures that L past symbols can be used in the
DFE in an error free manner through the use of a capacity achieving code for a
memoryless channel. Computational complexity of the proposed receiver structure
is less than that of one iteration of the turbo receiver. We also provide the proof
showing that the proposed receiver achieves the i.i.d. capacity of any constrained
input ISI channel. This DFE-based receiver has several advantages over an iterative
(turbo) receiver, such as low complexity, the fact that codes that are optimized for
memoryless channels can be used with channels with memory, and finally that the
channel does not need to be known at the transmitter. The proposed coding scheme
is universal in the sense that a single code of rate r; optimized for a memoryless
channel, provides small error probability uniformly across all AWGN-ISI channels of
i.i.d. capacity less than r:
This general principle of a proposed non-iterative receiver also applies to other
signal processing functions, such as timing recovery, pattern-dependent noise whiten ing, joint demodulation and decoding etc. This makes the proposed encoder and
receiver structure a viable alternative to iterative signal processing. The results show
significant complexity reduction and performance gain for the case of timing recovery
and patter-dependent noise whitening for magnetic recording channels
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
Reduced complexity detection for massive MIMO-OFDM wireless communication systems
PhD ThesisThe aim of this thesis is to analyze the uplink massive multiple-input multipleoutput
with orthogonal frequency-division multiplexing (MIMO-OFDM) communication
systems and to design a receiver that has improved performance
with reduced complexity. First, a novel receiver is proposed for coded massive
MIMO-OFDM systems utilizing log-likelihood ratios (LLRs) derived
from complex ratio distributions to model the approximate effective noise
(AEN) probability density function (PDF) at the output of a zero-forcing
equalizer (ZFE). These LLRs are subsequently used to improve the performance
of the decoding of low-density parity-check (LDPC) codes and turbo
codes. The Neumann large matrix approximation is employed to simplify the
matrix inversion in deriving the PDF.
To verify the PDF of the AEN, Monte-Carlo simulations are used to demonstrate
the close-match fitting between the derived PDF and the experimentally
obtained histogram of the noise in addition to the statistical tests and
the independence verification. In addition, complexity analysis of the LLR
obtained using the newly derived noise PDF is considered. The derived LLR
can be time consuming when the number of receive antennas is very large
in massive MIMO-OFDM systems. Thus, a reduced complexity approximation
is introduced to this LLR using Newton’s interpolation with different
orders and the results are compared to exact simulations. Further simulation
results over time-flat frequency selective multipath fading channels demonstrated
improved performance over equivalent systems using the Gaussian
approximation for the PDF of the noise.
By utilizing the PDF of the AEN, the PDF of the signal-to-noise ratio (SNR)
is obtained. Then, the outage probability, the closed-form capacity and three
approximate expressions for the channel capacity are derived based on that
PDF. The system performance is further investigated by exploiting the PDF
of the AEN to derive the bit error rate (BER) for the massive MIMO-OFDM
system with different M-ary modulations. Then, the pairwise error probability
(PEP) is derived to obtain the upper-bounds for the convolutionally coded
and turbo coded massive MIMO-OFDM systems for different code generators
and receive antennas.
Furthermore, the effect of the fixed point data representation on the performance
of the massive MIMO-OFDM systems is investigated using reduced
detection implementations for MIMO detectors. The motivation for the fixed
point analysis is the need for a reduced complexity detector to be implemented
as an optimum massive MIMO detector with low precision. Different
decomposition schemes are used to build the linear detector based on
the IEEE 754 standard in addition to a user-defined precision for selected
detectors. Simulations are used to demonstrate the behaviour of several matrix
inversion schemes under reduced bit resolution. The numerical results
demonstrate improved performance when using QR-factorization and pivoted
LDLT decomposition schemes at reduced precision.Iraqi Government and the Iraqi
Ministry of Higher Education and Scientific researc
Approximate inference in massive MIMO scenarios with moment matching techniques
Mención Internacional en el título de doctorThis Thesis explores low-complexity inference probabilistic algorithms in
high-dimensional Multiple-Input Multiple-Output (MIMO) systems and high order
M-Quadrature Amplitude Modulation (QAM) constellations. Several
modern communications systems are using more and more antennas to maximize
spectral efficiency, in a new phenomena call Massive MIMO. However,
as the number of antennas and/or the order of the constellation grow several
technical issues have to be tackled, one of them is that the symbol
detection complexity grows fast exponentially with the system dimension.
Nowadays the design of massive MIMO low-complexity receivers is one important
research line in MIMO because symbol detection can no longer rely
on conventional approaches such as Maximum a Posteriori (MAP) due to
its exponential computation complexity. This Thesis proposes two main results.
On one hand a hard decision low-complexity MIMO detector based on
Expectation Propagation (EP) algorithm which allows to iteratively approximate
within polynomial cost the posterior distribution of the transmitted
symbols. The receiver is named Expectation Propagation Detector (EPD)
and its solution evolves from Minimum Mean Square Error (MMSE) solution
and keeps per iteration the MMSE complexity which is dominated by
a matrix inversion. Hard decision Symbol Error Rate (SER) performance is
shown to remarkably improve state-of-the-art solutions of similar complexity.
On the other hand, a soft-inference algorithm, more suitable to modern
communication systems with channel codification techniques such as Low-
Density Parity-Check (LDPC) codes, is also presented. Modern channel
decoding techniques need as input Log-Likehood Ratio (LLR) information
for each coded bit. In order to obtain that information, firstly a soft bit
inference procedure must be performed. In low-dimensional scenarios, this
can be done by marginalization over the symbol posterior distribution. However,
this is not feasible at high-dimension. While EPD could provide this
probabilistic information, it is shown that its probabilistic estimates are in
general poor in the low Signal-to-Noise Ratio (SNR) regime. In order to
solve this inconvenience a new algorithm based on the Expectation Consistency
(EC) algorithm, which generalizes several algorithms such as Belief.
Propagation (BP) and EP itself, was proposed. The proposed algorithm
called Expectation Consistency Detector (ECD) maps the inference problem
as an optimization over a non convex function. This new approach
allows to find stationary points and tradeoffs between accuracy and convergence,
which leads to robust update rules. At the same complexity cost than
EPD, the new proposal achieves a performance closer to channel capacity at
moderate SNR. The result reveals that the probabilistic detection accuracy
has a relevant impact in the achievable rate of the overall system. Finally,
a modified ECD algorithm is presented, with a Turbo receiver structure
where the output of the decoder is fed back to ECD, achieving performance
gains in all block lengths simulated.
The document is structured as follows. In Chapter I an introduction
to the MIMO scenario is presented, the advantages and challenges are exposed
and the two main scenarios of this Thesis are set forth. Finally, the
motivation behind this work, and the contributions are revealed. In Chapters
II and III the state of the art and our proposal are presented for Hard
Detection, whereas in Chapters IV and V are exposed for Soft Inference Detection.
Eventually, a conclusion and future lines can be found in Chapter
VI.Esta Tesis aborda algoritmos de baja complejidad para la estimación probabilística en sistemas de Multiple-Input Multiple-Output (MIMO) de grandes
dimensiones con constelaciones M-Quadrature Amplitude Modulation (QAM)
de alta dimensionalidad. Son diversos los sistemas de comunicaciones que en
la actualidad están utilizando más y más antenas para maximizar la eficiencia
espectral, en un nuevo fenómeno denominado Massive MIMO. Sin embargo
los incrementos en el número de antenas y/o orden de la constelación
presentan ciertos desafíos tecnológicos que deben ser considerados. Uno de
ellos es la detección de los símbolos transmitidos en el sistema debido a que
la complejidad aumenta más rápido que las dimensiones del sistema. Por
tanto el diseño receptores para sistemas Massive MIMO de baja complejidad
es una de las importantes líneas de investigación en la actualidad en
MIMO, debido principalmente a que los métodos tradicionales no se pueden
implementar en sistemas con decenas de antenas, cuando lo deseable serían
centenas, debido a que su coste es exponencial.
Los principales resultados en esta Tesis pueden clasificarse en dos. En
primer lugar un receptor MIMO para decisión dura de baja complejidad
basado en el algoritmo Expectation Propagation (EP) que permite de manera
iterativa, con un coste computacional polinómico por iteración, aproximar
la distribución a posteriori de los símbolos transmitidos. El algoritmo,
denominado Expectation Propagation Detector (EPD), es inicializado con
la solución del algoritmo Minimum Mean Square Error (MMSE) y mantiene
el coste de este para todas las iteraciones, dominado por una inversión de
matriz. El rendimiento del decisor en probabilidad de error de símbolo muestra
ganancias remarcables con respecto a otros métodos en la literatura con
una complejidad similar. En segundo lugar, un algoritmo que provee una
estimación blanda, información que es más apropiada para los actuales sistemas
de comunicaciones que utilizan codificación de canal, como pueden
ser códigos Low-Density Parity-Check (LDPC). La información necesaria
para estos decodificadores de canal es Log-Likehood Ratio (LLR) para cada
uno de los bits codificados.
En escenarios de bajas dimensiones se pueden calcular las marginales de la distribución a posteriori, pero en escenarios de grandes dimensiones
no es viable, aunque EPD puede proporcionar este tipo de información a la
entrada del decodificador, dicha información no es la mejor al estar el algoritmo
pensado para detección dura, sobre todo se observa este fenómeno en
el rango de baja Signal-to-Noise Ratio (SNR). Para solucionar este problema
se propone un nuevo algoritmo basado en Expectation Consistency
(EC) que engloba diversos algoritmos como pueden ser Belief Propagation
(BP) y el algoritmo EP propuesto con anterioridad. El nuevo algoritmo
llamado Expectation Consistency Detector (ECD), trata el problema como
una optimización de una función no convexa. Esta aproximación permite
encontrar los puntos estacionarios y la relación entre precisión y convergencia,
que permitirán reglas de actualización más robustas y eficaces. Con
la misma compleja que el algoritmo propuesto inicialmente, ECD permite
rendimientos más próximos a la capacidad del canal en regímenes moderados
de SNR. Los resultados muestran que la precisión tiene un gran efecto
en la tasa que alcanza el sistema. Finalmente una versión modificada de
ECD es propuesta en una arquitectura típica de los Turbo receptores, en
la que la salida del decodificador es la entrada del receptor, y que permite
ganancias en el rendimiento en todas las longitudes de código simuladas.
El presente documento está estructurado de la siguiente manera. En el
primer Capítulo I, se realiza una introducción a los sistemas MIMO, presentando
sus ventajas, desventajas, problemas abiertos. Los modelos que se
utilizaran en la tesis y la motivación con la que se inició esta tesis son expuestos
en este primer capítulo. En los Capítulos II y III el estado del arte y
nuestra propuesta para detección dura son presentados, mientras que en los
Capítulos IV y V se presentan para detección suave. Finalmente las conclusiones
que pueden obtenerse de esta Tesis y futuras líneas de investigación
son expuestas en el Capítulo VI.Programa Oficial de Doctorado en Multimedia y ComunicacionesPresidente: Juan José Murillo Fuentes.- Secretario: Gonzalo Vázquez Vilar.- Vocal: María Isabel Valera Martíne
Investigation of non-binary trellis codes designed for impulsive noise environments
PhD ThesisIt is well known that binary codes with iterative decoders can achieve
near Shannon limit performance on the additive white Gaussian noise
(AWGN) channel, but their performance on more realistic wired or wireless
channels can become degraded due to the presence of burst errors
or impulsive noise. In such extreme environments, error correction alone
cannot combat the serious e ect of the channel and must be combined
with the signal processing techniques such as channel estimation, channel
equalisation and orthogonal frequency division multiplexing (OFDM).
However, even after the received signal has been processed, it can still
contain burst errors, or the noise present in the signal maybe non Gaussian.
In these cases, popular binary coding schemes such as Low-Density
Parity-Check (LDPC) or turbo codes may not perform optimally, resulting
in the degradation of performance. Nevertheless, there is still scope
for the design of new non-binary codes that are more suitable for these
environments, allowing us to achieve further gains in performance. In
this thesis, an investigation into good non-binary trellis error-correcting
codes and advanced noise reduction techniques has been carried out with
the aim of enhancing the performance of wired and wireless communication
networks in di erent extreme environments. These environments
include, urban, indoor, pedestrian, underwater, and powerline communication
(PLC). This work includes an examination of the performance
of non-binary trellis codes in harsh scenarios such as underwater communications
when the noise channel is additive S S noise. Similar work
was also conducted for single input single output (SISO) power line communication
systems for single carrier (SC) and multi carrier (MC) over
realistic multi-path frequency selective channels. A further examination
of multi-input multi-output (MIMO) wired and wireless systems on
Middleton class A noise channel was carried out. The main focus of the
project was non-binary coding schemes as it is well-known that they outperform
their binary counterparts when the channel is bursty. However,
few studies have investigated non-binary codes for other environments.
The major novelty of this work is the comparison of the performance
of non-binary trellis codes with binary trellis codes in various scenarios,
leading to the conclusion that non-binary codes are, in most cases,
superior in performance to binary codes. Furthermore, the theoretical
bounds of SISO and MIMO binary and non-binary convolutional coded
OFDM-PLC systems have been investigated for the rst time. In order
to validate our results, the implementation of simulated and theoretical
results have been obtained for di erent values of noise parameters and
on di erent PLC channels. The results show a strong agreement between
the simulated and theoretical analysis for all cases.University of
Thi-Qar for choosing me for their PhD scholarship and the Iraqi Ministry
of Higher Education and Scienti c Research (MOHESR) for granting me
the funds to study in UK. In addition, there was ample support towards
my stay in the UK from the Iraqi Cultural Attach e in Londo