Woven convolutional graph codes with large free distances

Constructions of woven graph codes based on constituent convolutional codes are studied and examples of woven convolutional graph codes are presented. The existence of codes, satisfying the Costello lower bound on the free distance, within the random ensemble of woven graph codes based on s-partite, s-uniform hypergraphs, where s depends only on the code rate, is shown. Simulation results for Viterbi decoding of woven graph codes are presented and discussed

Woven Graph Codes: Asymptotic Performances and Examples

Constructions of woven graph codes based on constituent block and convolutional codes are studied. It is shown that within the random ensemble of such codes based on $s$-partite, $s$-uniform hypergraphs, where $s$ depends only on the code rate, there exist codes satisfying the Varshamov-Gilbert (VG) and the Costello lower bound on the minimum distance and the free distance, respectively. A connection between regular bipartite graphs and tailbiting codes is shown. Some examples of woven graph codes are presented. Among them an example of a rate $R_{\rm wg}=1/3$ woven graph code with $d_{\rm free}=32$ based on Heawood's bipartite graph and containing $n=7$ constituent rate $R^{c}=2/3$ convolutional codes with overall constraint lengths $\nu^{c}=5$ is given. An encoding procedure for woven graph codes with complexity proportional to the number of constituent codes and their overall constraint length $\nu^{c}$ is presented.Comment: Submitted to IEEE Trans. Inform. Theor

A rate R=5/20 hypergraph-based woven convolutional code with free distance 120

A rate R=5/20 hypergraph-based woven convolu- tional code with overall constraint length 67 and constituent con- volutional codes is presented. It is based on a 3-partite, 3-uniform, 4-regular hypergraph and contains rate R=3/4 constituent convolutional codes with overall constraint length 5. Although the code construction is based on low-complexity codes, the free distance of this construction, computed with the BEAST algorithm, is dfree=120, which is remarkably large

Codes on Graphs and More

Modern communication systems strive to achieve reliable and efficient information transmission and storage with affordable complexity. Hence, efficient low-complexity channel codes providing low probabilities for erroneous receptions are needed. Interpreting codes as graphs and graphs as codes opens new perspectives for constructing such channel codes. Low-density parity-check (LDPC) codes are one of the most recent examples of codes defined on graphs, providing a better bit error probability than other block codes, given the same decoding complexity. After an introduction to coding theory, different graphical representations for channel codes are reviewed. Based on ideas from graph theory, new algorithms are introduced to iteratively search for LDPC block codes with large girth and to determine their minimum distance. In particular, new LDPC block codes of different rates and with girth up to 24 are presented. Woven convolutional codes are introduced as a generalization of graph-based codes and an asymptotic bound on their free distance, namely, the Costello lower bound, is proven. Moreover, promising examples of woven convolutional codes are given, including a rate 5/20 code with overall constraint length 67 and free distance 120. The remaining part of this dissertation focuses on basic properties of convolutional codes. First, a recurrent equation to determine a closed form expression of the exact decoding bit error probability for convolutional codes is presented. The obtained closed form expression is evaluated for various realizations of encoders, including rate 1/2 and 2/3 encoders, of as many as 16 states. Moreover, MacWilliams-type identities are revisited and a recursion for sequences of spectra of truncated as well as tailbitten convolutional codes and their duals is derived. Finally, the dissertation is concluded with exhaustive searches for convolutional codes of various rates with either optimum free distance or optimum distance profile, extending previously published results

On the weight distribution of convolutional codes

Detailed information about the weight distribution of a convolutional code is given by the adjacency matrix of the state diagram associated with a controller canonical form of the code. We will show that this matrix is an invariant of the code. Moreover, it will be proven that codes with the same adjacency matrix have the same dimension and the same Forney indices and finally that for one-dimensional binary convolutional codes the adjacency matrix determines the code uniquely up to monomial equivalence

A Combined Equaliser and Decoder for Maximum Likelihood Decoding of Convolutional Codes in the presence of ISI. Incorporation into GSM 3GPP Standard

The dissertation describes a new approach in combining the equalising and decoding operations in wireless telecommunications, namely MS decoder. It provides performance results (SNR) and carries out simulations based on GSM 3GPP standard

Could Cultures Determine the Course of Epidemics and Explain Waves of COVID-19?

Coronavirus Disease (COVID-19), caused by the SARS-CoV-2 virus, is an infectious disease that quickly became a pandemic spreading with different patterns in each country. Travel bans, lockdowns, social distancing, and non-essential business closures caused significant economic disruptions and stalled growth worldwide in the pandemic’s first year. In almost every country, public health officials forced and/or encouraged Nonpharmaceutical Interventions (NPIs) such as contact tracing, social distancing, masks, and quarantine. Human behavioral decision-making regarding social isolation significantly impedes global success in containing the pandemic. This thesis focuses on human behaviors and cultures related to the decision-making of social isolation during the pandemic. Within a COVID-19 disease transmission model, we created a conceptual and deterministic model of human behavior and cultures. This study emphasizes the importance of human behavior in successful disease control strategies. Additionally, we introduce a back engineering approach to determine whether cultures are explained by the courses of COVID-19 epidemics. We used a deep learning technique based on a convolutional neural network (CNN) to predict cultures from COVID-19 courses. In this system, CNN is used for deep feature extraction with ordinary convolution and with residual blocks. Also, a novel concept is introduced that converts tabular data into an image using matrix transformation and image processing validated by identifying some well-known function. Despite having a small and novel data set, we have achieved an 80-95% accuracy, depending on the cultural measures

TOWARD DEEP LEARNING EMULATORS FOR MODELING THE LARGE-SCALE STRUCTURE OF THE UNIVERSE

Multi-billion dollar cosmological surveys are being conducted almost every decade in today’s era of precision cosmology. These surveys scan vast swaths of sky and generate tons of observational data. In order to extract meaningful information from this data and test these observations against theory, rigorous theoretical predictions are needed. In the absence of an analytic method, cosmological simulations become the most widely used tool to provide these predictions in order to test against the observations. They can be used to study covariance matrices, generate mock galaxy catalogs and provide ready-to-use snapshots for detailed redshift analyses. But cosmological simulations of matter formation in the universe are one of the most computationally intensive tasks. Faster but equally reliable tools that could approximate these simulations are thus desperately needed. Recently, deep learning has come up as an innovative and novel tool that can generate numerous cosmological simulations orders of magnitude faster than traditional simulations. Deep learning models of structure formation and evolution in the universe are unimaginably fast and retain most of the accuracy of conventional simulations, thus providing a fast, reliable, efficient, and accurate method to study the evolution of the universe and reducing the computational burden of current simulation methods. In this dissertation, we will focus on deep learning-based models that could mimic the process of structure formation in the universe. In particular, we focus on developing deep convolutional neural network models that could learn the present 3D distribution of the cold dark matter and generate 2D dark matter cosmic mass maps. We employ summary statistics most commonly employed in cosmology and computer vision to quantify the robustness of our models

Optimisation de la transmission de phonie et vidéophonie sur les réseaux à larges bandes PMR

Cet exposé analyse les perspectives large bande des réseaux PMR, à travers l'évaluation du candidat LTE, et la proposition d'une possible évolution du codage canal, la solution brevetée des codes turbo à protection non uniforme. Une première étude dans le chapitre 2 se concentre sur l'analyse multi-couche et l'identification des problèmes clé des communications de voix et de vidéo sur un réseau LTE professionnel. Les capacités voix et vidéo sont estimées pour les liens montant et descendant de la transmission LTE, et l'efficacité spectrale de la voix en lien descendant est comparée à celle de PMR et GSM. Ce chapitre souligne certains points clé de l'évolution de LTE. S'ils étaient pas résolus par la suite, LTE se verrait perdre de sa crédibilité en tant que candidat à l'évolution de la PMR. Une telle caractéristique clé des réseaux PMR est le codage canal à protection non uniforme, qui pourrait être adapté au système LTE pour une évolution aux contraintes de la sécurité publique. Le chapitre 3 introduit cette proposition d'évolution, qui a été brevetée: les turbo codes à protection non uniforme intégrée. Nous proposons une nouvelle approche pour le codage canal à protection non uniforme à travers les codes turbo progressives hiérarchiques. Les configurations parallèles et séries sont analysées. Les mécanismes de protection non uniformes sont intégrés dans la structure de l'encodeur même à travers l'insertion progressif et hiérarchique de nouvelles données de l'utilisateur. Le turbo décodage est modifié pour exploiter de façon optimale l'insertion progressive de données dans le processus d'encodage et estimer hiérarchiquement ces données. Les propriétés des structures parallèles et séries sont analysées à l'aide d'une analogie aux codes pilotes, ainsi qu'en regardant de plus près leurs caractéristiques de poids de codage. Le taux de transmission virtuel et les représentations des graphs factor fournissent une meilleure compréhension de ces propriétés. Les gains de codage sont évalués à l'aide de simulations numériques, en supposant des canaux de transmission radio statiques et dynamiques, et en utilisant des codes de référence. Enfin, dans le chapitre 4, l'idée breveté du code turbo parallal progressif et hiérarchique (PPHTC) est évaluée sur la plateforme LTE. Une description détaillée de l'architecture des bearers de LTE est donnée, et ses conséquences sont discutées. Le nouveau codage canal est inséré et évalué sur cette plateforme, et ses performances sont comparées avec des schémas de transmission typique à LTE. L'analyse de la qualité de la voix aide à conclure sur l'efficacité de la solution proposée dans un système de transmission réel. Pourtant, même si cette dernière donne les meilleurs résultats, d'avantage d'optimisations devraient être envisagées pour obtenir des gains améliorés et mieux exploiter le potentiel du codage proposé. L'exposé se conclut dans le chapitre 5 et une courte discussion présente les futures perspectives de rechercheThis dissertation analyzes the PMR broadband perspectives, through the evaluation of the preferred candidate, LTE, and the proposal of a possible channel coding evolution, the patented solution of unequal error protection embedded turbo codes. A first study in chapter 2 focuses on the multi-layer analysis and the identification of key issues for professional-like LTE for voice and video communications. The voice and video capacities are estimated for both downlink and uplink LTE transmissions, and the downlink LTE voice system efficiency is compared with that of the PMR and Global System for Mobile Communications (GSM). This chapter helps highlighting some of the key points. If not resolved, the latter could lead to the LTE downfall as a candidate for the PMR evolution. One such key characteristic of PMR systems is the unequal error protection channel coding technique, which might be adapted to the LTE technology for its evolution to public safety requirements. Chapter 3 further introduces the proposed evolution patented ideas: the unequal error protection embedded turbo codes. We propose a new approach for the unequal error protection channel coding through the progressive hierarchical turbo codes. Both parallel and serial turbo configurations are closely studied. The unequal error protection mechanisms are embedded in the encoder s structure itself through the progressive and hierarchical insertion of new data. The turbo decoding is modified as to optimally exploit the progressive insertion of information in the encoding process and hierarchically estimate the corresponding data. Both parallel and serial configurations properties are analyzed using an analogy with a pilot code behavior, as well as a zoom on the weight error functions coefficients. The virtual code rate and factor graph interpretations also provide a better insight on the code properties. The code possible gains are highlighted through computer simulations in both static and dynamic transmission environments, by using carefully chosen benchmarks. Finally, in chapter 4, the patented idea of parallel progressive hierarchical turbo codes (PPHTC) is evaluated over the LTE platform. A detailed description is given of the voice transmission bearer architecture over LTE, and its consequences are discussed. The new channel code is inserted and evaluated over this platform and its performances compared with the existent LTE transmission schemes. The voice quality results help concluding on the efficiency of the proposed solution in a real transmission scenario. However, even though the newly presented solution gives the best results, further system optimizations should be envisaged for obtaining better gains and exploit the parallel progressive hierarchical turbo codes potential. The dissertation concludes in chapter 5 and a short discussion is given on future research perspectivesEVRY-INT (912282302) / SudocSudocFranceF