Parallel concatenated convolutional codes (PCCCs), called "turbo codes" by their discoverers, have been shown to perform close to the Shannon bound at bit error rates (BERs) between 1e-4 and 1e-6. Serial concatenated convolutional codes (SCCCs), which perform better than PCCCs at BERs lower than 1e-6, were developed borrowing the same principles as PCCCs, including code concatenation, pseudorandom interleaving and iterative decoding. The first part of this dissertation introduces the fundamentals of concatenated convolutional codes. The theoretical and simulated BER performance of PCCC and SCCC are discussed. Encoding and decoding structures are explained, with emphasis on the Log-MAP decoding algorithm and the general soft-input soft-output (SISO) decoding module. Sliding window techniques, which can be employed to reduce memory requirements, are also briefly discussed. The second part of this dissertation presents four major contributions to the field of concatenated convolutional coding developed through this research. First, the effects of quantization and fixed point arithmetic on the decoding performance are studied. Analytic bounds and modular renormalization techniques are developed to improve the efficiency of SISO module implementation without compromising the performance. Second, a new stopping criterion, SDR, is discovered. It is found to perform well with lowest cost when evaluating its complexity and performance in comparison with existing criteria. Third, a new type-II code combining automatic repeat request (ARQ) technique is introduced which makes use of the related PCCC and SCCC. Fourth, a new code-assisted synchronization technique is presented, which uses a list approach to leverage the simplicity of the correlation technique and the soft information of the decoder. In particular, the variant that uses SDR criterion achieves superb performance with low complexity. Finally, the third part of this dissertation discusses the FPGA-based implementation of the turbo decoder, which is the fruit of cooperation with fellow researchers. / Ph. D.

Error Correction and Concealment of Block Based, Motion-Compensated Temporal Prediction, Transform Coded Video David L. Robie 133 Pages Directed by Dr. Russell M. Mersereau The use of the Internet and wireless networks to bring multimedia to the consumer continues to expand. The transmission of these products is always subject to corruption due to errors such as bit errors or lost and ill-timed packets; however, in many cases, such as real time video transmission, retransmission request (ARQ) is not practical. Therefore receivers must be capable of recovering from corrupted data. Errors can be mitigated using forward error correction in the encoder or error concealment techniques in the decoder. This thesis investigates the use of forward error correction (FEC) techniques in the encoder and error concealment in the decoder in block-based, motion-compensated, temporal prediction, transform codecs. It will show improvement over standard FEC applications and improvements in error concealment relative to the Motion Picture Experts Group (MPEG) standard. To this end, this dissertation will describe the following contributions and proofs-of-concept in the area of error concealment and correction in block-based video transmission. A temporal error concealment algorithm which uses motion-compensated macroblocks from previous frames. A spatial error concealment algorithm which uses the Hough transform to detect edges in both foreground and background colors and using directional interpolation or directional filtering to provide improved edge reproduction. A codec which uses data hiding to transmit error correction information. An enhanced codec which builds upon the last by improving the performance of the codec in the error-free environment while maintaining excellent error recovery capabilities. A method to allocate Reed-Solomon (R-S) packet-based forward error correction that will decrease distortion (using a PSNR metric) at the receiver compared to standard FEC techniques. Finally, under the constraints of a constant bit rate, the tradeoff between traditional R-S FEC and alternate forward concealment information (FCI) is evaluated. Each of these developments is compared and contrasted to state of the art techniques and are able to show improvements using widely accepted metrics. The dissertation concludes with a discussion of future work.

Source coding and channel coding are two important problems in communications. Although side information exists in everyday scenario, the effect of side information is not taken into account in the conventional setups. In this thesis, we focus on the practical designs of two interesting coding problems with side information: Wyner-Ziv coding (source coding with side information at the decoder) and Gel??fand-Pinsker coding (channel coding with side information at the encoder). For WZC, we split the design problem into the two cases when the distortion of the reconstructed source is zero and when it is not. We review that the first case, which is commonly called Slepian-Wolf coding (SWC), can be implemented using conventional channel coding. Then, we detail the SWC design using the low-density parity-check (LDPC) code. To facilitate SWC design, we justify a necessary requirement that the SWC performance should be independent of the input source. We show that a sufficient condition of this requirement is that the hypothetical channel between the source and the side information satisfies a symmetry condition dubbed dual symmetry. Furthermore, under that dual symmetry condition, SWC design problem can be simply treated as LDPC coding design over the hypothetical channel. When the distortion of the reconstructed source is non-zero, we propose a practical WZC paradigm called Slepian-Wolf coded quantization (SWCQ) by combining SWC and nested lattice quantization. We point out an interesting analogy between SWCQ and entropy coded quantization in classic source coding. Furthermore, a practical scheme of SWCQ using 1-D nested lattice quantization and LDPC is implemented. For GPC, since the actual design procedure relies on the more precise setting of the problem, we choose to investigate the design of GPC as the form of a digital watermarking problem as digital watermarking is the precise dual of WZC. We then introduce an enhanced version of the well-known spread spectrum watermarking technique. Two applications related to digital watermarking are presented.

Linear programming (LP) decoding of low-density parity-check codes was introduced by Feldman et al. in [1]. In his formulation it is assumed that communication takes place over a memoryless channel and that the source is uniform. Here, we extend the LP decoding paradigm by studying its application to scenarios with source non-uniformity and to decoding over channels with memory. We develop two decoders for the scenario of non-uniform memoryless sources transmitted over memoryless channels. The first decoder uses a modified linear cost function which incorporates the a-priori source information and works with systematic codes. The second decoder differs by using non-systematic codes obtained by puncturing lower rate systematic codes and using an “extended decoding polytope.” Simulations show that the modified decoders yield gains over the standard LP decoder. Next, LP decoding is considered for two channels with memory: the binary additive Markov noise channel and the infinite-memory non-ergodic Polya-contagion channel. For the Markov channel, no linear cost function corresponding to maximum likelihood (ML) decoding could be obtained and hence it is unclear how to proceed. For the Polya channel, two LP-based decoders are developed. The first is derived in a straightforward manner from the ML decoding rule of [2]. The second decoder relies on a simplification of the same ML decoding rule which holds for codes containing the all-ones codeword. Simulations are performed for both decoders with regular and irregular LDPC codes and demonstrate relatively good performance with respect to the channel epsilon-capacity. / Thesis (Master, Mathematics & Statistics) -- Queen's University, 2008-12-08 16:24:43.358

This thesis studies cooperative sensing and transmission in the context ofwireless sensor networks (WSNs). We especially focus on two means of cooperative sensing and transmission, namely, distributed source coding and relaying. We consider systems where the usefulness of the measured data is dependent on how old the data is and we therefore need low-delay transmission schemes. At first sight, the low-delay criterion may seem to be of little relevance, but it is this aspect in particular that distinguishes this thesis from many of the existing communication theoretic results, which often are asymptotic in the block lengths. The thesis is composed of an introductory part, discussing the fundamentals of communication theory and how these are related to the requirements of WSNs, followed by a part where the results of the thesis are reported in Papers A-H. Papers A-D study different scenarios for distributed source-channel coding. In Paper A, we consider transmission of correlated continuous sources and propose an iterative algorithm for designing simple and energy-efficient sensor nodes. In particular the cases of the binary symmetric channel as well as the additive white Gaussian noise channel are studied. In Paper B, the work is extended to channels with interference and it is shown that also in this case there can be significant power savings by performing a joint optimization of the system.Papers C and D use a more structured approach and propose side-information-aware source-channel coding strategies using lattices and sinusoids. In Paper E, we apply the methods we have used in joint source-channel coding to the famous Witsenhausen counterexample. By using a relatively simple iterative algorithm, we are able to demonstrate the best numerical performance known to date. For the case of systems with relays, we study the transmission of a continuous Gaussian source and the transmission of an uniformly distributed discrete source. In both situations, we propose algorithms to design low-delay source-channel and relay mappings. By studying the structure of the optimized source-channel and relay mappings, we provide useful insights into how the optimized systems work. These results are reported in Papers F and G. In Paper H, we finally consider sum-MSE minimization for the Gaussian multiple-input, multiple-output broadcast channel. By using recently discovered properties of this problem, we derive a closed-form expression for the optimal power allocation in the two-user scenario and propose a conceptually simple and efficient algorithm that handles an arbitrary number of users. Throughout the thesis we show that there are significant gains if the parts of the system are jointly optimized for the source and channel statistics. All methods that are considered in this thesis yield very low coding and decoding delays. In general, nonlinear mappings outperform linear mappings for problems where there is side-information available. Another contribution of this thesis is visualization of numerically optimized systems that can be used as inspiration when structured low-delay systems are designed. / The author changed name from Johannes Karlsson to Johannes Kron in January 2011. QC 20110512

Dans le contexte de l'Internet des Objets (IoT), on estime à plus de 10% la proportion de connections réalisées via les réseaux longue portée bas débit, représentant ainsi plusieurs milliards d’objet connectés. Afin de satisfaire les exigences en termes de sensibilité et de réduction du débit, deux approches sont généralement envisagées : l’approche bande étroite, et l’approche faible efficacité spectrale. En comparant les performances des systèmes existants à la limite théorique issue de la théorie de l'information et démontrée par Shannon, on constate qu’un gain en performance est atteignable, tout en travaillant toujours à de faibles niveaux de sensibilité. La théorie de l'information permet d'affirmer qu'un compromis entre l'efficacité spectrale et l'efficacité énergétique doit toujours être fait. Ainsi, une haute efficacité énergétique s'obtiendra au détriment d'une efficacité spectrale faible. A l'inverse, un système fonctionnant à une haute efficacité spectrale devra utiliser plus d'énergie pour transmettre le même nombre de bits et atteindre le même taux d'erreur.Ce travail s’intéresse à l’approche faible efficacité spectrale. En partant des modulations orthogonales, qui permettent d’atteindre la limite théorique de Shannon à des efficacités spectrales très faibles, et des processus turbo, qui atteignent d’excellentes performances à des efficacités spectrales élevées, l’utilisation conjointe d’une modulation orthogonale et d'un code correcteur associés à un récepteur itératif dans une technique dénommée Turbo-FSK est étudiée. Les différents paramètres de la technique sont optimisés en utilisant un outil classique des processus itératifs, l’Extrinsic Information Transfer (EXIT) chart. Les performances mesurées démontrent que la technique permet bien d’atteindre de très faibles niveaux de sensibilité et répond aux critères des réseaux longue portée bas débit. Cependant, la technique ne dispose de point de fonctionnement qu’à de très faibles valeurs d’efficacité spectrale : pour certaines applications ou si la portée nécessaire est réduite, il peut être bénéfique pour le système d’augmenter son efficacité spectrale. Ceci est rendu possible grâce à l’introduction d’une composante linéaire dans l’alphabet de modulation et d’un mécanisme de poinçonnage spécifique à la technique dans une version flexible appelée Coplanar Turbo-FSK. L’étude de l’influence des paramètres et des performances sur un canal à bruit blanc additif gaussien permet en effet de conclure sur la flexibilité de l’efficacité spectrale du système, tout en fonctionnant proche de la limite théorique. Finalement, l’étude jusqu’ici théorique est étendue à un contexte plus pratique, où des canaux sélectifs en fréquences sont considérés. Une encapsulation du système utilisant une architecture OFDM est considérée, et différentes mesures caractéristiques des systèmes de télécommunication sont évaluées. Les résultats sont confrontés à la solution Narrow-Band IoT proposée par l’organisme 3GPP et démontrent ici encore le potentiel de la solution Turbo-FSK pour les réseaux longue portée bas débit. / More than 10% of the Internet-of-Things (IoT) connections are expected to be realized through Low Power Wide Area (LPWA) networks, representing several billions of connected devices. Several industrial solutions have been developed and a standardization process is ongoing. The low levels of sensitivity and low data rate required for the long range communication are achieved by the means of two strategies: a narrow-band strategy and a low spectral efficiency strategy. Considering the limits of the information theory, additional gains in the communication's energy efficiency can be achieved. Nonetheless, a trade-off between spectral efficiency and energy efficiency should always be made. Reliable transmission with high energy efficiency will necessarily result in poor spectral efficiency, and in comparison, a system with a higher spectral efficiency has to consume more energy to transmit the same amount of bits with the same arbitrary level of error.This work considers the low spectral efficiency strategy. The combination of orthogonal modulations and a powerful channel code is studied. The scheme, so-called Turbo-FSK, associates the low spectral efficiency of Frequency Shift Keying (FSK) with the energy efficiency gain of a turbo receiver. Low levels of spectral efficiency can be achieved while optimizing the use of the available resource. The parameters of the scheme are optimized using a classic tool for iterative receivers, the Extrinsic Information Transfer (EXIT) chart. Performance of Turbo-FSK compared to existing LPWA solutions demonstrates the potential of the proposed solution to achieve low levels of sensitivity and to outperform existing schemes. However, the restrictions on low levels of spectral efficiency reduces the number of possible applications for the scheme. By introducing a linear component in the alphabet and a puncturing procedure, flexibility in spectral efficiency is achieved. A large range of spectral efficiencies can be obtained while maintaining performance close to the channel capacity theoretical limit. Eventually, more practical scenarios are considered for evaluating the performance of the scheme. Frequency selective channels are considered and an encapsulation in a Fast Fourier Transform (FFT) based system is implemented. Various indicators are studied and the Turbo-FSK scheme is compared to well-known technologies, such as schemes using Orthogonal Frequency Division Multiplexing (OFDM) associated with a powerful Forward Error Correction (FEC) scheme, namely Turbo Code (TC).

Les systèmes de navigation par satellites sont de plus en plus présents dans notre vie quotidienne. De nouveaux besoins émergent, majoritairement en environnement urbain. Dans ce type d'environnement très obstrué, le signal reçu par l'utilisateur a subit des atténuations ainsi que des réfractions/diffractions, ce qui rend difficile la démodulation des données et le calcul de position de l'utilisateur. Les signaux de navigation par satellites étant initialement conçus dans un contexte d'environnement dégagé, leurs performances de démodulation sont donc généralement étudiées dans le modèle de canal de propagation AWGN associé. Or aujourd'hui ils sont utilisés aussi en environnements dégradés. Il est donc indispensable de fournir et d'étudier leurs performances de démodulation dans des modèles de canal de propagation urbain. C'est dans ce contexte que s'inscrit cette thèse, le but final étant d'améliorer les performances de démodulation des signaux GNSS en milieux urbains, en proposant un nouveau signal. Afin de pouvoir fournir et analyser les performances de démodulation des signaux de navigation par satellite en milieux urbains, un outil de simulation a été développé dans le cadre de cette thèse : SiGMeP pour « Simulator for GNSS Message Performance ». Il permet de simuler la chaine entière d'émission/réception d'un signal de navigation par satellites et de calculer ses performances de démodulation en milieu urbain. Les performances de démodulation des signaux existants et modernisés ont donc été calculées avec SiGMeP en environnement urbain. Afin de représenter au mieux ces performances pour qu'elles soient le plus réalistes possibles, une nouvelle méthode adaptée au cas urbain est proposée dans ce manuscrit. Ensuite, pour améliorer ces performances de démodulation, l'axe de recherche s'est essentiellement porté sur le « codage canal ». Pour décoder l'information utile transmise, le récepteur calcule une fonction de détection à l'entrée du décodeur. Or la fonction de détection utilisée dans les récepteurs classiques correspond à un modèle de canal AWGN. Ce manuscrit propose donc une fonction de détection avancée, qui s'adapte au canal de propagation dans lequel l'utilisateur évolue, ce qui améliore considérablement les performances de démodulation, en ne modifiant que la partie récepteur du système. Enfin, dans le but de concevoir un nouveau signal avec de meilleures performances de démodulation en environnement urbain que celles des signaux existants ou futurs, un nouveau codage canal de type LDPC a été optimisé pour une modulation CSK. En effet, la modulation CSK est une modulation prometteuse dans le monde des signaux de type spectre étalé, qui permet de se débarrasser des limitations en termes de débit de données qu'impliquent les modulations actuelles des signaux de navigation par satellites. / Global Navigation Satellite Systems (GNSS) are increasingly present in our everyday life. Further operational needs are emerging, mainly in urban environments. In these obstructed environments, the signal emitted by the satellite is severely degraded due to the many obstacles. Consequently, the data demodulation and the user position calculation are difficult. GNSS signals being initially designed in an open environment context, their demodulation performance is thus generally studied in the associated AWGN propagation channel model. But nowadays, GNSS signals are also used in degraded environments. It is thus essential to provide and study their demodulation performance in urban propagation channel models. It is in this context that this PhD thesis is related, the final goal being to improve GNSS signals demodulation performance in urban areas, proposing a new signal. In order to be able to provide and study GNSS signals demodulation performance in urban environments, a simulation tool has been developed in this PhD thesis context: SiGMeP for ‘Simulator for GNSS Message Performance'. It allows simulating the entire emission/reception GNSS signal chain in urban environment. Existing and modernized signals demodulation performance has thus been computed with SiGMeP in urban environments. In order to represent this demodulation performance faithfully to reality, a new methodology adapted to urban channels is proposed in this dissertation. Then, to improve GNSS signals demodulation performance in urban environments, the research axis of this thesis has focused on the ‘Channel Coding' aspect. In order to decode the transmitted useful information, the receiver computes a detection function at the decoder input. But the detection function used in classic receivers corresponds to an AWGN propagation channel. This dissertation thus proposes an advanced detection function which is adapting to the propagation channel where the user is moving. This advanced detection function computation considerably improves demodulation performance, just in modifying the receiver part of the system. Finally, in order to design a new signal with better demodulation performance in urban environments than one of existing and future signals, a new LDPC channel code has been optimized for a CSK modulation. Indeed, the CSK modulation is a promising modulation in the spread spectrum signals world, which permits to free from limitation sin terms of data rate implied by current GNSS signals modulations.

The availability of feedback from the receiver to the transmitter in a communication system can play a significant role. In this dissertation, our focus is specifically on binary or one-bit feedback. First, we study the problem of successive beam alignment for millimeter-wave channels where the receiver sends back only one-bit of information per beam sounding. The sparse nature of the channel allows us to interpret channel sounding as a form of questioning. By posing the alignment problem as a questioning strategy, we describe adaptive (closed-loop) and non-adaptive (open-loop) channel sounding techniques which are robust to erroneous feedback signals caused by noisy quantization. In the second part, we tightly characterize the capacity for two binary stochastic-adversarial mixed noise channels. Specifically, the transmitter (Alice) intends to convey a message to the receiver (Bob) over a binary symmetric channel (BSC) or a binary erasure channel (BEC) in the presence of an adversary (Calvin) who injects additional noise at the channel's input subject to a budget constraint. Calvin is online or causal in that at any point during the transmission, he can infer the bits being sent by Alice and those being received by Bob via a feedback link. Finally in the third part, we study the applicability of binary feedback for encoding and propose the framework of linearly adapting block feedback codes. We also prove a new result for Reed-Muller (RM) codes to demonstrate how an uncoded system can mimic a RM code under this framework, against remarkably large feedback delays.

La détection cohérente combinée avec le traitement du signal s’est imposée comme le standard pour les systèmes de communications optiques longue distance à 100 Gb/s (mono-porteuse) et au-delà. Avec l'avènement des convertisseurs numérique-analogique à haute vitesse et haute résolution, la génération de formats de modulation d'ordre supérieure avec filtrage numérique est devenue possible, favorisant l’émergence de transmissions à forte densité spectrale. En outre, la généralisation des liaisons non gérées en dispersion permet une modélisation analytique du canal optique et favorise l'utilisation d’outils puissants de la théorie de l'information et du traitement du signal. En se fondant sur ces outils, de nouveaux formats de modulation à entrelacement temporel dits hybrides et formats multidimensionnels sont étudiés et mise en oeuvre expérimentalement. Leur impact sur les algorithmes de traitement du signal et sur le débit d'information atteignable est analysé en détail. La conception de transpondeurs de prochaine génération à 400 Gb/ s et 1 Tb/s reposant sur des signaux à débit-symbole élevé est également étudiée. Ces systèmes sont intéressants pour réduire le coût par bit en augmentant la capacité émise par transpondeur. L'élaboration d'algorithmes de traitement du signal avancés associés à l’utilisation de composants optoélectroniques à l'état de l'art ont permis la démonstration d’expériences records: d’une part la première transmission mono-porteuse à 400 Gb/s sur une distance transatlantique (pour une efficacité spectrale de 6 b/s/Hz) d’autre part la première transmission à 1 Tb/s basée sur la synthèse en parallèle de plusieurs tranches spectrales (8 b/s/Hz) / Coherent detection in combination with digital signal processing is now the de facto standard for long-haul high capacity optical communications systems operating at 100 Gb/s per channel and beyond. With the advent of high-speed high-resolution digital-to-analog converters, generation of high order modulation formats with digital pulse shaping has become possible allowing the increase of system spectral efficiency. Furthermore, the widespread use of transmission links without in-line dispersion compensation enables elegant analytical optical channel modeling which facilitates the use of powerful tools from information theory and digital signal processing. Relying on these aforementioned tools, the introduction of time-interleaved hybrid modulation formats, multi-dimensional modulation formats, and alternative quadrature amplitude modulation formats is investigated in high-speed optical transmission systems. Their impact on signal processing algorithms and achievable information rate over optical links is studied in detail. Next, the design of next generation transponders based on high symbol rate signals operating at 400 Gb/s and 1 Tb/s is investigated. These systems are attractive to reduce the cost per bit as more capacity can be integrated in a single transponder. Thanks to the development of advanced signal processing algorithms combined with state-of-the-art opto-electronic components, record high-capacity transmission experiments are demonstrated: the first single carrier 400 Gb/s transmission over transatlantic distance (at 6 b/s/Hz) and the first 1 Tb/s net data rate transmission based on the parallel synthesis of multiple spectral slices (at 8 b/s/Hz)

[pt] Este trabalho apresenta um estudo sobre compressão de imagens de sensoriamento remoto para serem transmitidas através de um canal com ruído. As imagens são capturadas por um satélite de sensoriamento remoto e transmitidas a uma estação terrestre. A compreensão das imagens é necessária para se economizar banda e potência de transmissão. Algumas técnicas muito boas de compressão de imagens apresentam sérios problemas quando na presença de ruído. Assim, a técnica de quantização vetorial foi escolhida para ser utilizada neste trabalho. Utilizando-se a idéia de quantização vetorial multi-estágios, propões-se um esquema de compressão com remoção de médias, onde separa-se a informação contida na imagem para tratá-la de forma diferenciada, de acordo com a sua importância. É feita então uma análise sobre o projeto do enlace do satélite do sensoriamento remoto comparando-se o esquema utilizado atualmente com o esquema proposto. / [en] This thesis presents a study of remote sensing image compression to be transmitted over a noisy channel. The images are obtained by a remote sensing satellite and transmitting to an earth station. The compression is due to savings in bandwidth and transmitting power. Some of the most efficient image codecs presents serious problems in the presence of noise. So, the vector quantization technique was chosen to be used. Using the multi-stage vector quantization idea, a compression scheme with mean remove is proposed as a manner to separate and treat unequally the image information as its importance. An analysis on the design of the remote sensing satellite link is done with a comparison between the current scheme used the proposed one.