933 research outputs found
Turbo Decoding and Detection for Wireless Applications
A historical perspective of turbo coding and turbo transceivers inspired by the generic turbo principles is provided, as it evolved from Shannonâs visionary predictions. More specifically, we commence by discussing the turbo principles, which have been shown to be capable of performing close to Shannonâs capacity limit. We continue by reviewing the classic maximum a posteriori probability decoder. These discussions are followed by studying the effect of a range of system parameters in a systematic fashion, in order to gauge their performance ramifications. In the second part of this treatise, we focus our attention on the family of iterative receivers designed for wireless communication systems, which were partly inspired by the invention of turbo codes. More specifically, the family of iteratively detected joint coding and modulation schemes, turbo equalization, concatenated spacetime and channel coding arrangements, as well as multi-user detection and three-stage multimedia systems are highlighted
On performance analysis and implementation issues of iterative decoding for graph based codes
There is no doubt that long random-like code has the potential to achieve good performance because of its excellent distance spectrum. However, these codes remain useless in practical applications due to the lack of decoders rendering good performance at an acceptable complexity. The invention of turbo code marks a milestone progress in channel coding theory in that it achieves near Shannon limit performance by using an elegant iterative decoding algorithm. This great success stimulated intensive research oil long compound codes sharing the same decoding mechanism. Among these long codes are low-density parity-check (LDPC) code and product code, which render brilliant performance. In this work, iterative decoding algorithms for LDPC code and product code are studied in the context of belief propagation.
A large part of this work concerns LDPC code. First the concept of iterative decoding capacity is established in the context of density evolution. Two simulation-based methods approximating decoding capacity are applied to LDPC code. Their effectiveness is evaluated. A suboptimal iterative decoder, Max-Log-MAP algorithm, is also investigated. It has been intensively studied in turbo code but seems to be neglected in LDPC code. The specific density evolution procedure for Max-Log-MAP decoding is developed. The performance of LDPC code with infinite block length is well-predicted using density evolution procedure.
Two implementation issues on iterative decoding of LDPC code are studied. One is the design of a quantized decoder. The other is the influence of mismatched signal-to-noise ratio (SNR) level on decoding performance. The theoretical capacities of the quantized LDPC decoder, under Log-MAP and Max-Log-MAP algorithms, are derived through discretized density evolution. It is indicated that the key point in designing a quantized decoder is to pick a proper dynamic range. Quantization loss in terms of bit error rate (BER) performance could be kept remarkably low, provided that the dynamic range is chosen wisely. The decoding capacity under fixed SNR offset is obtained. The robustness of LDPC code with practical length is evaluated through simulations. It is found that the amount of SNR offset that can be tolerated depends on the code length.
The remaining part of this dissertation deals with iterative decoding of product code. Two issues on iterative decoding of\u27 product code are investigated. One is, \u27improving BER performance by mitigating cycle effects. The other is, parallel decoding structure, which is conceptually better than serial decoding and yields lower decoding latency
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 Ăbertragungs-konzepten fĂźr 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 fĂźr 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, eingefßhrt. 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 EntscheidungsrĂźckfĂźhrung, so dass zur UnterdrĂźckung
von Interferenzen neben den a priori Informationen der Kanaldekodierung
auch weiche Entscheidungen der vorherigen Detektions-schritte
berßcksichtigt werden. Durch die zusätzlich interne
EntscheidungsrĂźckfĂźhrung erzielt der PDA SC-MMSE einen wesentlichen Gewinn
an Performance in räumlich unkorrelierten MIMO-Kanälen gegenßber dem
SC-MMSE, ohne dabei die Komplexität des Entzerrers wesentlich zu erhÜhen.
Der zweite Empfänger - hybrid SC-MMSE - bildet eine Verknßpfung von
gruppenbasierter SC-MMSE Frequenzbereichsfilterung und MAP-Detektion.
Dieser Empfänger besitzt eine skalierbare Berechnungskomplexität und weist
eine hohe Robustheit gegenßber 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 Ăberlegenheit des hybriden
SC-MMSE-Ansatzes gegenßber 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
fßr MIMO-Fadingkanäle entwickelt. Des Weiteren werden zwei Fehlerschranken
fßr die Ausfallwahrscheinlichkeit der Empfänger vorgestellt. Die
semi-analytische Methode und die abgeleiteten Fehlerschranken ermĂśglichen
eine aufwandsgeringe Abschätzung sowie Optimierung der Leistungsfähigkeit
des iterativen Systems.
Im dritten und abschlieĂenden 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 BerĂźcksichtigung der Konvergenz
des iterativen Empfängers fßr einen Zweinutzerkanal mit fester
Leistungsallokation betrachtet. Mit Hilfe des Flächentheorems von
Extrinsic-Information-Transfer (EXIT)-Funktionen wird eine obere Schranke
fĂźr die erreichbare Ratenregion hergeleitet. Auf Grundlage dieser Schranke
wird ein einfacher Algorithmus entwickelt, der fĂźr 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 fĂźr die Nutzer unter BerĂźcksichtigung der Einhaltung
einer bestimmten Ausfallwahrscheinlichkeit (outage probability) des
iterativen Empfängers. Des Weiteren wird ein neues Entwurfskriterium fßr
irreguläre Faltungscodes hergeleitet, das die Ausfallwahrscheinlichkeit von
Turbo SC-MMSE Systemen verringert und somit die Zuverlässigkeit der
DatenĂźbertragung erhĂśht. Eine Reihe von Simulationsergebnissen von
Kapazitäts- und Durchsatzberechnungen werden vorgestellt, die die
Wirksamkeit der vorgeschlagenen Algorithmen und Optimierungsverfahren in
Mehrnutzerkanälen belegen. AbschlieĂend werden auĂerdem verschiedene
MaĂnahmen 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 Ăźberlegen
ist
Minimum mean-squared error iterative successive parallel arbitrated decision feedback detectors for DS-CDMA systems
In this paper we propose minimum mean squared error (MMSE) iterative successive parallel arbitrated decision feedback (DF) receivers for direct sequence code division multiple access (DS-CDMA) systems. We describe the MMSE design criterion for DF multiuser detectors along with successive, parallel and iterative interference cancellation structures. A novel efficient DF structure that employs successive cancellation with parallel arbitrated branches and a near-optimal low complexity user ordering algorithm are presented. The proposed DF receiver structure and the ordering algorithm are then combined with iterative cascaded DF stages for mitigating the deleterious effects of error propagation for convolutionally encoded systems with both Viterbi and turbo decoding as well as for uncoded schemes. We mathematically study the relations between the MMSE achieved by the analyzed DF structures, including the novel scheme, with imperfect and perfect feedback. Simulation results for an uplink scenario assess the new iterative DF detectors against linear receivers and evaluate the effects of error propagation of the new cancellation methods against existing ones
CONVERGENCE IMPROVEMENT OF ITERATIVE DECODERS
Iterative decoding techniques shaked the waters of the error correction and communications
field in general. Their amazing compromise between complexity and performance
offered much more freedom in code design and made highly complex codes, that were
being considered undecodable until recently, part of almost any communication system.
Nevertheless, iterative decoding is a sub-optimum decoding method and as such, it has
attracted huge research interest. But the iterative decoder still hides many of its secrets,
as it has not been possible yet to fully describe its behaviour and its cost function.
This work presents the convergence problem of iterative decoding from various angles
and explores methods for reducing any sub-optimalities on its operation. The decoding
algorithms for both LDPC and turbo codes were investigated and aspects that contribute
to convergence problems were identified. A new algorithm was proposed, capable of providing
considerable coding gain in any iterative scheme. Moreover, it was shown that
for some codes the proposed algorithm is sufficient to eliminate any sub-optimality and
perform maximum likelihood decoding. Its performance and efficiency was compared to
that of other convergence improvement schemes.
Various conditions that can be considered critical to the outcome of the iterative decoder
were also investigated and the decoding algorithm of LDPC codes was followed
analytically to verify the experimental results
Synchronization in digital communication systems: performance bounds and practical algorithms
Communication channels often transfer signals from different transmitters. To avoid interference the available frequency spectrum is divided into non-overlapping frequency bands (bandpass channels) and each transmitter is assigned to a different bandpass channel. The transmission of a signal over a bandpass channel requires a shift of its frequency-content to a frequency range that is compatible with the designated frequency band (modulation). At the receiver, the modulated signal is demodulated (frequency shifted back to the original frequency band) in order to recover the original signal. The modulation/demodulation process requires the presence of a locally generated sinusoidal signal at both the transmitter and the receiver. To enable a reliable information transfer, it is imperative that these two sinusoids are accurately synchronized.
Recently, several powerful channel codes have been developed which enable reliable communication at a very low signal-to-noise ratio (SNR). A by-product of these developments is that synchronization must now be performed at a SNR that is lower than ever before. Of course, this imposes high requirements on the synchronizer design.
This doctoral thesis investigates to what extent (performance bounds) and in what way (practical algorithms) the structure that the channel code enforces upon the transmitted signal can be exploited to improve the synchronization accuracy at low SNR
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