Motivated by potential applications in wireless sensor networks, this thesis considers the problem of communicating a large number of correlated analog sources over a Gaussian multiple-access channel using non-orthogonal code-division multiple-access (CDMA). A joint source-channel decoder is presented which can exploit the inter-source correlation for interference reduction in the CDMA channel. This decoder uses a linear minimum mean square error (MMSE) multi-user detector (MUD) in tandem with a MMSE joint source decoder (JSD) for multiple sources to achieve a computational complexity that scales with the number of sources. The MUD and the JSD, then iteratively exchange extrinsic information to improve the interference cancellation. Experimental results show that, compared to a non-iterative decoder, the proposed iterative decoder is more robust against potential performance degradation due to correlated channel interference and offers better near far resistance.

abstract: There has been a lot of work on the characterization of capacity and achievable rate regions, and rate region outer-bounds for various multi-user channels of interest. Parallel to the developed information theoretic results, practical codes have also been designed for some multi-user channels such as multiple access channels, broadcast channels and relay channels; however, interference channels have not received much attention and only a limited amount of work has been conducted on them. With this motivation, in this dissertation, design of practical and implementable channel codes is studied focusing on multi-user channels with special emphasis on interference channels; in particular, irregular low-density-parity-check codes are exploited for a variety of cases and trellis based codes for short block length designs are performed. Novel code design approaches are first studied for the two-user Gaussian multiple access channel. Exploiting Gaussian mixture approximation, new methods are proposed wherein the optimized codes are shown to improve upon the available designs and off-the-shelf point-to-point codes applied to the multiple access channel scenario. The code design is then examined for the two-user Gaussian interference channel implementing the Han-Kobayashi encoding and decoding strategy. Compared with the point-to-point codes, the newly designed codes consistently offer better performance. Parallel to this work, code design is explored for the discrete memoryless interference channels wherein the channel inputs and outputs are taken from a finite alphabet and it is demonstrated that the designed codes are superior to the single user codes used with time sharing. Finally, the code design principles are also investigated for the two-user Gaussian interference channel employing trellis-based codes with short block lengths for the case of strong and mixed interference levels. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2015

Orientador: Jaime Portugheis / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-03T15:25:23Z (GMT). No. of bitstreams: 1 Cunha_DanielCarvalhoda_M.pdf: 3453050 bytes, checksum: 13fe48dc7912e447d190ba1ba03e67dd (MD5) Previous issue date: 2003 / Resumo: Neste trabalho desenvolvemos um estudo sobre a aplicação de um algoritmo de de-codificação iterativa (turbo) de códigos produto em sistemas de transmissão que utilizam dois tipos de canais não-gaussianos: o canal CDMA de salto rápido em freqüência e o canal com ruído impulsivo juntamente com modulação BPSK. Para ambos os casos, propusemos uma maneira de calcular a confiabilidade das decisões tomadas após cada iteração, que leva em conta as densidades de probabilidade dos canais considerados. No caso do canal CDMA, os resultados mostraram que, para códigos de taxas baixa, média e alta, o desempenho do sistema melhora com o aumento do número de iterações de decodificação, o que comprova a validade da proposta. No caso de canais com ruído impulsivo, além da validade da proposta, ve-rificamos que o conhecimento da relação sinal-ruído do canal pelo decodificador pode melhorar o desempenho do sistema. Entretanto, para alguns valores dos parâmetros do ruído impulsivo, verificamos que uma escolha antecipada dos fatores a e ? do algoritmo iterativo que garanta a convergência do mesmo, pode se tornar uma tarefa bastante árdua / Abstract: In this work we develop a study of iterative (turbo) algorithms for product codes applied to transmission systems which utilize two types of non-Gaussian channels: a fast frequency hopping CDMA channel and impulsive noise channels with BPSK modulation. In both cases, we propose a way to calculate the reliability of decisions made after each iteration taking into account the probability density functions of the considered channels. In the case of a CDMA channel, for low, medium and high rate codes, the results showed that the performance of the systems becomes better as the number of decoding iterations increases, a result that validates the proposal. In the case of impulsive noise channels, we verified not only the validity of the proposal but also that the decoder knowledge of channel signal-to-noise ratios can improve the performance of the system. However, for some specific values of impulsive noise parameters, we verified that to give a predefined value to a and ? factors for the iterative algorithm which guarantees its convergence, can become a considerable difficult task / Mestrado / Mestre em Engenharia Elétrica

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Since the 1950s, hidden Markov models (HMMS) have seen widespread use in electrical engineering. Foremost has been their use in speech processing, pattern recognition, artificial intelligence, queuing theory, and communications theory. However, recent years have witnessed a renaissance in the application of HMMs to the analysis and simulation of digital communication systems. Typical applications have included signal estimation, frequency tracking, equalization, burst error characterization, and transmit power control. Of special significance to this thesis, however, has been the use of HMMs to model fading channels typical of wireless communications. This variegated use of HMMs is fueled by their ability to model time-varying systems with memory, their ability to yield closed form solutions to otherwise intractable analytic problems, and their ability to help facilitate simple hardware and/or software based implementations of simulation test-beds. The aim of this thesis is to employ and exploit hidden Markov fading models within an iterative (turbo) decoding framework. Of particular importance is the problem of channel estimation, which is vital for realizing the large coding gains inherent in turbo coded schemes. This thesis shows that a Markov fading channel (MFC) can be conceptualized as a trellis, and that the transmission of a sequence over a MFC can be viewed as a trellis encoding process much like convolutional encoding. The thesis demonstrates that either maximum likelihood sequence estimation (MLSE) algorithms or maximum <I> a posteriori</I> (MAP) algorithms operating over the trellis defined by the MFC can be used for channel estimation. Furthermore, the thesis illustrates sequential and decision-directed techniques for using the aforementioned trellis based channel estimators <I>en masse</I> with an iterative decoder. / Master of Science

Ces dernières années ont vu naitre un intérêt grandissant pour les décodeurs correcteurs d'erreurs opérant sur des circuits non fiables. En effet, la miniaturisation croissante des composants électroniques ainsi l'échelonnage agressif de la tension d'alimentation ont pour conséquence la diminution de la fiabilité des systèmes. Par conséquent, les futures générations de circuits électroniques seront intrinsèquement non fiables. En outre, les décodeurs correcteurs d'erreurs sont indispensables non seulement pour assurer une transmission fiable de l'information mais aussi pour concevoir des systèmes de stockage performants.Nous nous intéressons, dans cette thèse, plus particulièrement aux décodeurs à précision finie Min-Sum (MS), Self-Corrected Min-Sum (SCMS) et Stochastiques.Nous commençons par effectuer une analyse statistique du décodeur Min-Sum opérant sur des circuits à comportement probabiliste. Pour ce faire nous introduisons des modèles d'erreurs probabilistes pour les composants logiques et les opérateurs arithmétiques du décodeur et étudions leurs propriétés de symétrie. Puis nous effectuions une analyse asymptotique rigoureuse et en déduisons les équations d'évolution de densité du décodeur Min-Sum bruité. Nous mettons ainsi en évidence l'effet positif, dans certains cas, du bruit issu du circuit sur la capacité de correction du décodeur. Nous révélons ensuite l'existence d'un phénomène de seuil particulier que nous nommons seuil fonctionnel. Ce dernier peut être considéré comme la généralisation du seuil classique pour les décodeurs non fiables. Nous corroborons ensuite les résultats asymptotiques par des simulations Monte-Carlo.Nous implémentons des décodeurs LDPC bruités pour plusieurs paramètres de bruit et montrons que les décodeurs LDPC bruité ont des résultats très proches de ceux des décodeurs non bruités. Nous pouvons par conséquent considérer le circuit d'autocorrection comme un patch bruité appliqué au décodeur MS bruité afin d'améliorer la robustesse du décodeur face au bruit issu des composants non fiables. Nous évaluons par railleurs l'impact de l'ordonnancement et montrons qu'un ordonnancement série dégrade fortement la robustesse des décodeurs bruités MS et SCMS qui ne parviennent plus à atteindre une capacité de correction acceptable.Pour finir nous étudions les performances des décodeurs stochastiques pourvus de mémoires d'arêtes et opérant sur des circuits non fiables. Nous proposons deux modèles d'erreurs décrivant le comportement probabiliste des composants du décodeur. Nous montrons que, dans certains cas, le bruit issu du circuit non fiable permet de réduire le plancher d'erreur. Nous en déduisons alors que le décodeur stochastique est intrinsèquement tolérant aux fautes. / Over the past few years, there has been an increasing interest in error correction decoders built out of unreliable components. Indeed, it is widely accepted that future generation of electronic circuit will be inherently unreliable, due to the increase in density integration and aggressive voltage scaling. Furthermore, error correction decoders play a crucial role both in reliable transmission of information and in the design of reliable storage systems. It is then important to investigate the robustness of error correction decoders in presence of hardware noise.In this thesis we focus on LDPC decoders built out of unreliable computing units. We consider three types of LDPC decoders: the finite-precision Min-Sum (MS) decoder, the Self-Corrected Min-Sum (SCMS) decoder and the Stochastic decoder.We begin our study by the statistical analysis of the finite-precision Min-Sum decoder with probabilistic components. To this end, we first introduce probabilistic models for the arithmetic and logic units of the decoder and discuss their symmetry properties. We conduct a thorough asymptotic analysis and derive density evolution equations for the noisy Min-Sum decoder. We highlight that in some particular cases, the noise introduced by the device can increase the correction capacity of the noisy Min-Sum with respect to the noiseless decoder. We also reveal the existence of a specific threshold phenomenon, referred to as functional threshold, which can be viewed as the generalization of the threshold definition for noisy decoders. We then corroborate the asymptotic results through Monte-Carlo simulations.Since density evolution cannot be defined for decoders with memory, the analysis of noisy Self-corrected Min-Sum decoders and noisy Stochastic decoders was restricted to Monte-Carlo simulations.We emulate the noisy SCMS decoders with various noise parameters and show that noisy SCMS decoders perform close to the noiseless SCMS decoder for a wide range of noise parameters. Therefore, one can think of the self-correction circuit as a noisy patch applied to the noisy MS decoder, in order to improve its robustness to hardware defect. We also evaluate the impact of the decoder scheduling on the robustness of the noisy MS and SCMS decoders and show that when the serial scheduling is used neither the noisy MS decoder nor the noisy SCMS decoder can provide acceptable error correction.Finally, we investigate the performance of stochastic decoders with edge-memories in presence of hardware noise. We propose two error models for the noisy components. We show that in some cases, the hardware noise can be used to lower the error floor of the decoder meaning that stochastic decoders have an inherent fault tolerant capability.

Efficient multimedia communication over mobile or wireless channels remains a challenging problem. To deal with that problem so far, the industry has followed mostly a divide and conquer approach, by considering separately the source of data (text, image, video, etc.) and the communication channel (electromagnetic waves across the air, a telephone line, a coaxial cable, etc.). The goal is always the same: to transmit (or store) more data reliably per unit of time, of energy, of physical medium, etc. With today's applications, the divide and conquer approach has, in a sense, started to show its limits. Let us consider, for example, the digital transmission of an image. At the transmitter, the first main step is data compression, at the source level. The number of bits that are necessary to represent the image with a given level of quality is reduced, usually by removing details in the image that are invisible (or less visible) to the human eye. The second main step is data protection, at the channel level. The transmission is made ideally resistant to deteriorations caused by the channel, by implementing techniques such as time/frequency/space expansions. In a sense, the two steps are quite antagonistic --- we first compress then expand the original signal --- and have different goals --- compression enables to transfer more data per unit of time/energy/medium while protection enables to transfer data reliably. At the receiver, the "reversed" operations are implemented. This separation in two steps dates back to Shannon's source and channel coding separation theorem in 1948 and has encouraged the division of the research community in two groups, one focusing on data compression, the other on data protection. This separation has also seduced the industry for the design, thereby supported by theory, of layered communication protocols. But this theorem holds only under asymptotic conditions that are rarely satisfied with today's multimedia content and mobile channels. Therefore, it is usually wise in practice to drop this strict separation and to allow at least some cross-layer cooperation between the source and channel layers. This is what lies behind the words joint source-channel techniques. As the name suggests, these techniques are optimized jointly, without a strict separation. Intuitively, since the optimization is less constrained from a mathematical standpoint, the solution can only be better or equivalent. In this thesis, we investigate a promising subset of these techniques, based on the turbo principle and on variable length codes. The potential of this subset has been illustrated for the first time in 2000, with an example that, since then, has been successfully improved in several directions. Unfortunately, most decoding algorithms have been so far developed on an ad hoc basis, without a unified view and often without specifying the approximations made. Besides, most code-related conclusions are based on simulations or on extrinsic information analysis. A theoretical framework on the error correcting properties of variable length codes in turbo systems is lacking. The purpose of this work, in three parts, is to fill in these gaps up to a certain extent. The first part presents the literature in this field and attempts to give a unified overview. The second part proposes a transmission system that generalizes previous systems from the literature, with the simple addition of a repetition code. While most previous systems are designed for bit streams with a high level of residual redundancy, the proposed system has the interesting flexibility to handle easily different levels of redundancy. Its performance is then analyzed for small levels of redundancy, which is a case not tackled extensively in the literature. This analysis leads notably to the discovery of surprising interleaving gains with reversible variable length codes. The third part develops the mathematical framework that was motivated during the second part but skipped on purpose for the sake of clarity. We first clarify several issues that arise with non-uniform bits and the extrinsic information charts, and propose and discuss two methods to compute these charts. Next, several theoretical results are stated on the robustness of variable length codes concatenated with linear error correcting codes. Notably, an approximate average distance spectrum of the concatenated code is rigorously developed. Together with the union bound, this spectrum provides upper bounds on the symbol and frame/packet error rates. These bounds are then analyzed from an interleaving gain standpoint and it is proved that the variable length code improves the interleaving gain if its spectrum is bounded.

This thesis considers the real-time implementation phases of a multiple-input multiple-output (MIMO) wireless communication system. The parts which are related to the implementation detail the blocks realized on a field programmable gate array (FPGA) board and define the connections between these blocks and typical radio frequency front-end modules assisting the wireless communication. Two sides of the implemented communication testbed are discussed separately as the transmitter and the receiver parts. In addition to usual building blocks of the transmitter and the receiver blocks, a special type of iterative parallelized decoding architecture has also been implemented on the testbed to demonstrate its potential in low-latency communication systems. In addition to practical aspects, this thesis also presents theoretical findings for an improved version of the built system using analytical tools and simulation results for possible extensions to orthogonal frequency division multiplexing (OFDM).

In this thesis, implementation details of a joint channel estimator and parallelized decoder structure on an FPGA-based platform is considered. Turbo decoders are used for the decoding process in this structure. However, turbo decoders introduce large decoding latencies since they operate in an iterative manner. To overcome that problem, parallelization is applied to the turbo codes and the resulting parallel decodable turbo code (PDTC) structure is employed for coding. The performance of a PDTC decoder and parameters affecting its performance is given on an additive white Gaussian noise (AWGN) channel. These results are compared with the results of a parallel study which employs a different architecture in implementing the PDTC decoder. In the fading channel case, a pilot symbol assisted estimation method is employed for the channel estimation process. In this method, the channel coefficients are estimated by a 2-way LMS (least mean-squares) algorithm. The difficulties in the implementation of this joint structure in a fixed-point arithmetic and the solutions to overcome these difficulties are described in details. The proposed joint structure is tested with varying design parameters over a Rayleigh fading channel. The overall decoding latencies and allowed data rates are calculated after obtaining a reasonable performance from the design.