MIMO-aided near-capacity turbo transceivers: taxonomy and performance versus complexity

In this treatise, we firstly review the associated Multiple-Input Multiple-Output (MIMO) system theory and review the family of hard-decision and soft-decision based detection algorithms in the context of Spatial Division Multiplexing (SDM) systems. Our discussions culminate in the introduction of a range of powerful novel MIMO detectors, such as for example Markov Chain assisted Minimum Bit-Error Rate (MC-MBER) detectors, which are capable of reliably operating in the challenging high-importance rank-deficient scenarios, where there are more transmitters than receivers and hence the resultant channel-matrix becomes non-invertible. As a result, conventional detectors would exhibit a high residual error floor. We then invoke the Soft-Input Soft-Output (SISO) MIMO detectors for creating turbo-detected two- or three-stage concatenated SDM schemes and investigate their attainable performance in the light of their computational complexity. Finally, we introduce the powerful design tools of EXtrinsic Information Transfer (EXIT)-charts and characterize the achievable performance of the diverse near- capacity SISO detectors with the aid of EXIT charts

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

Reconnaissance de codes correcteurs

In this PhD, we focus on the code reconstruction problem. This problem mainly arises in a non-cooperative context when a communication consisting of noisy codewords stemming from an unknown code is observed and its content has to be retrieved by recovering the code that is used for communicating and decoding with it the noisy codewords. We consider here three possible scenarios and suggest an original method for each case. In the first one, we assume that the code that is used is a turbo-code and we propose a method for reconstructing the associated interleaver (the other components of the turbo-code can be easily recovered by the existing methods). The interleaver is reconstructed step by step by searching for the most probable index at each time and by computing the relevant probabilities with the help of the BCJR decoding algorithm. In the second one, we tackle the problem of reconstructing LDPC codes by suggesting a new method for finding a list of parity-check equations of small weight that generalizes and improves upon all existing methods. Finally, in the last scenario we reconstruct an unknown interleaved convolutional code. In this method we used the previous one to find a list of parity-check equations for this code. Then, by introducing a graph representing how these parity-check equations intersect we recover at the same time the interleaver and the convolutional code.Dans cette thèse, nous nous intéressons au problème de la reconnaissance de code. Ce problème se produit principalement lorsqu'une communication est observée dans un milieu non-coopératif. Une liste de mots bruités issus d'un code inconnu est obtenue, l'objectif est alors de retrouver l'information contenue dans ces mots bruités. Pour cela, le code utilisé est reconstruit afin de décoder les mots observés. Nous considérons ici trois instances de ce problème et proposons pour chacune d'elle une nouvelle méthode. Dans la première, nous supposons que le code utilisé est un turbo-code et nous proposons une méthode pour reconstruire la permutation interne (les autres éléments du turbo-codeur pouvant être facilement reconstruits grâce aux méthodes existantes). Cette permutation est reconstruite pas à pas en recherchant l'indice le plus probable à chaque instant. Plus précisément, la probabilité de chaque indice est déterminée avec l'aide de l'algorithme de décodage BCJR. Dans la seconde, nous traitons le problème de la reconnaissance des codes LDPC en suggérant une nouvelle méthode pour retrouver une liste d'équations de parité de petits poids. Celle-ci généralise et améliore les méthodes existantes. Finalement, avec la dernière méthode, nous reconstruisons un code convolutif entrelacé. Cette méthode fait appel à la précédente pour retrouver une liste d'équations de parité satisfaites par le code entrelacé. Puis, en introduisant une représentation sous forme de graphe de l'intersection de ces équations de parité, nous retrouvons simultanément l'entrelaceur et le code convolutif

Development of a novel platform for high-throughput gene design and artificial gene synthesis to produce large libraries of recombinant venom peptides for drug discovery

Tese de Doutoramento em Ciências Veterinárias na Especialidade de Ciências Biológicas e BiomédicasAnimal venoms are complex mixtures of biologically active molecules that, while presenting low immunogenicity, target with high selectivity and efficacy a variety of membrane receptors. It is believed that animal venoms comprise a natural library of more than 40 million different natural compounds that have been continuously fine-tuned during the evolutionary process to disturb cellular function. Within animal venoms, reticulated peptides are the most attractive class of molecules for drug discovery. However, the use of animal venoms to develop novel pharmacological compounds is still hampered by difficulties in obtaining these low molecular mass cysteine-rich polypeptides in sufficient amounts. Here, a high-throughput gene synthesis platform was developed to produce synthetic genes encoding venom peptides. The final goal of this project is the production of large libraries of recombinant venom peptides that can be screened for drug discovery. A robust and efficient Polymerase Chain Reaction (PCR) methodology was refined to assemble overlapping oligonucleotides into small artificial genes (< 500 bp) with high-fidelity. In addition, two bioinformatics tools were constructed to design multiple optimized genes (ATGenium) and overlapping oligonucleotides (NZYOligo designer), in order to allow automation of the high-throughput gene synthesis platform. The platform can assemble 96 synthetic genes encoding venom peptides simultaneously, with an error rate of 1.1 mutations per kb. To decrease the error rate associated with artificial gene synthesis, an error removal step using phage T7 endonuclease I was designed and integrated into the gene synthesis methodology. T7 endonuclease I was shown to be highly effective to specifically recognize and cleave DNA mismatches allowing a dramatically reduction of error frequency in large synthetic genes, from 3.45 to 0.43 errors per kb. Combining the knowledge acquired in the initial stages of the work, a comprehensive study was performed to investigate the influence of gene design, presence of fusion tags, cellular localization of expression, and usage of Tobacco Etch Virus (TEV) protease for tag removal, on the recombinant expression of disulfide-rich venom peptides in Escherichia coli. Codon usage dramatically affected the levels of recombinant expression in E. coli. In addition, a significant pressure in the usage of the two cysteine codons suggests that both need to be present at equivalent levels in genes designed de novo to ensure high levels of expression. This study also revealed that DsbC was the best fusion tag for recombinant expression of disulfide-rich peptides, in particular when expression of the fusion peptide was directed to the bacterial periplasm. TEV protease was highly effective for efficient tag removal and its recognition sites can tolerate all residues at its C-terminal, with exception of proline, confirming that no extra residues need to be incorporated at the N-terminus of recombinant venom peptides. This study revealed that E. coli is a convenient heterologous host for the expression of soluble and potentially functional venom peptides. Thus, this novel high-throughput gene synthesis platform was used to produce ~5,000 synthetic genes with a low error rate. This genetic library supported the production of the largest library of recombinant venom peptides constructed until now. The library contains 2736 animal venom peptides and it is presently being screened for the discovery of novel drug leads related to different diseases.RESUMO - Desenvolvimento de uma nova plataforma de alta capacidade para desenhar e sintetizar genes artificiais, para a produção de péptidos venómicos recombinantes - Os venenos animais são misturas complexas de moléculas biologicamente activas que se ligam com elevada selectividade e eficácia a uma grande variedade de receptores de membrana. Embora apresentem baixa imunogenicidade, os venenos podem afectar a função celular actuando ao nível dos seus receptores. Actualmente, pensa-se que os venenos de animais constituam uma biblioteca natural de mais de 40 milhões de moléculas diferentes que têm sido continuamente aperfeiçoadas ao longo do processo evolutivo. Tendo em conta a composição dos venenos, os péptidos reticulados são a classe mais atractiva de moléculas com interesse farmacológico. No entanto, a utilização de venenos para o desenvolvimento de novos fármacos está limitada por dificuldades em obter estas moléculas em quantidades adequadas ao seu estudo. Neste trabalho desenvolveu-se uma plataforma de alta capacidade para a síntese de genes sintéticos codificadores de péptidos venómicos, com o objectivo de produzir bibliotecas de péptidos venómicos recombinantes que possam ser rastreadas para a descoberta de novos medicamentos. Com o objectivo de sintetizar genes pequenos (< 500 pares de bases) com elevada fidelidade e em simultâneo, desenvolveu-se uma metodologia de PCR (polymerase chain reaction) robusta e eficiente, que se baseia na extensão de oligonucleótidos sobrepostos. Para possibilitar a automatização da plataforma de síntese de genes, foram construídas duas ferramentas bioinformáticas para desenhar simultaneamente dezenas a milhares de genes optimizados para a expressão em Escherichia coli (ATGenium) e os respectivos oligonucleótios sobrepostos (NZYOligo designer). Esta plataforma foi optimizada para sintetizar em simultâneo 96 genes sintéticos, tendo-se obtido uma taxa de erro de 1.1 mutações por kb de DNA sintetizado. A fim de diminuir a taxa de erro associada à produção de genes sintéticos, desenvolveu-se um método para remoção de erros utilizando a enzima T7 endonuclease I. A enzima T7 endonuclease I mostrou-se muito eficaz no reconhecimento e clivagem de moléculas DNA que apresentam emparelhamentos incorrectos, reduzindo drasticamente a frequência de erros identificados em genes grandes, de 3.45 para 0.43 erros por kb de DNA sintetizado. Investigou-se também a influência do desenho dos genes, da presença de tags de fusão, da localização celular da expressão e da actividade da protease Tobacco Etch Virus (TEV) para a remoção eficiente de tags, na expressão de péptidos venómicos ricos em cisteínas em E. coli. A utilização de codões meticulosamente escolhidos afectou drasticamente os níveis de expressão em E. coli. Para além disso, os resultados mostram que existe uma pressão significativa no uso dos dois codões que codificam para o resíduo cisteína, o que sugere que ambos os codões têm de estar presentes, em níveis equivalentes, nos genes que foram desenhados e optimizados para garantir elevados níveis de expressão. Este trabalho indicou também que o tag de fusão DsbC foi o mais apropriado para a expressão eficiente de péptidos venómicos ricos em cisteínas, particularmente quando os péptidos recombinantes foram expressos no periplasma bacteriano. Confirmou-se que a protease TEV é eficaz na remoção de tags de fusão, podendo o seu local de reconhecimento conter quaisquer aminoácidos na extremidade C-terminal, com excepção da prolina. Desta forma, verificou-se não ser necessário incorporar qualquer aminoácido extra na extremidade N-terminal dos péptidos venómicos recombinantes. Reunindo todos os resultados, verificou-se que a E. coli é um hospedeiro adequado para a expressão, na forma solúvel, de péptidos venómicos potencialmente funcionais. Por último, foram produzidos, com uma taxa de erro reduzida, ~5000 genes sintéticos codificadores de péptidos venómicos utilizando a nova plataforma de elevada capacidade para a síntese de genes aqui desenvolvida. A nova biblioteca de genes sintéticos foi usada para produzir a maior biblioteca de péptidos venómicos recombinantes construída até agora, que inclui 2736 péptidos venómicos. Esta biblioteca recombinante está presentemente a ser rastreada com o objectivo de descobrir novas drogas com interesse para a saúde humana

Proceedings of the 2018 Canadian Society for Mechanical Engineering (CSME) International Congress

Published proceedings of the 2018 Canadian Society for Mechanical Engineering (CSME) International Congress, hosted by York University, 27-30 May 2018