Multi-Dimensional Codebooks for Multiple Access Schemes

The sparse code multiple access (SCMA) scheme directly maps the incoming bits of several sources (users/streams) to complex multi-dimensional codewords selected from a specific predefined sparse codebook set. The codewords of all sources are then superimposed and exchanged. The shaping gain of the multi-dimensional constellation of SCMA leads to a better system performance. The decoder’s objective will be to separate the superimposed sparse codewords. Most existing works on SCMA decoders employ message passing algorithm (MPA) or one of its variations, or a combination of MPA and other methods. The system architecture is highlighted and its basic principles are presented. Then, an overview of main multi-dimensional constellations for SCMA systems will be provided. Afterwards, we will focus on how the SCMA codebooks are decoded and how their performance is evaluated and compared

Genomic Research Data Generation, Analysis and Sharing – Challenges in the African Setting

International audienceGenomics is the study of the genetic material that constitutes the genomes of organisms. This genetic material can be sequenced and it provides a powerful tool for the study of human, plant and animal evolutionary history and diseases. Genomics research is becoming increasingly commonplace due to significant advances in and reducing costs of technologies such as sequencing. This has led to new challenges including increasing cost and complexity of data. There is, therefore, an increasing need for computing infrastructure and skills to manage, store, analyze and interpret the data. In addition, there is a significant cost associated with recruitment of participants and collection and processing of biological samples, particularly for large human genetics studies on specific diseases. As a result, researchers are often reluctant to share the data due to the effort and associated cost. In Africa, where researchers are most commonly at the study recruitment, determination of phenotypes and collection of biological samples end of the genomic research spectrum, rather than the generation of genomic data, data sharing without adequate safeguards for the interests of the primary data generators is a concern. There are substantial ethical considerations in the sharing of human genomics data. The broad consent for data sharing preferred by genomics researchers and funders does not necessarily align with the expectations of researchers, research participants, legal authorities and bioethicists. In Africa, this is complicated by concerns about comprehension of genomics research studies, quality of research ethics reviews and understanding of the implications of broad consent, secondary analyses of shared data, return of results and incidental findings. Additional challenges with genomics research in Africa include the inability to transfer, store, process and analyze large-scale genomics data on the continent, because this requires highly specialized skills and expensive computing infrastructure which are often unavailable. Recently initiatives such as H3Africa and H3ABioNet which aim to build capacity for large-scale genomics projects in Africa have emerged. Here we describe such initiatives, including the challenges faced in the generation, analysis and sharing of genomic data and how these challenges are being overcome

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Contributions aux capacités de reconnaissance de l'environnement de la Radio Cognitive pour des applications mobiles à grande vitesse

Les principaux objectifs des opérateurs ferroviaires visent à accroître la sécurité, réduire les coûts d’exploitation et de maintenance et augmenter l’attractivité et les bénéfices du transport ferroviaire en offrant de nouveaux services aux passagers. Ceci ne pourra être atteint que grâce à la multiplication des échanges de données entre les différents acteurs du monde ferroviaire. L’interopérabilité, l’efficacité spectrale, l’optimisation de l’usage des ressources radio et l’amélioration de la fiabilité des communications sont des exigences fortes pour les applications de télécommunication ferroviaires. Les recherches dans le domaine de la radio cognitive ont vu le jour afin de répondre aux besoins de communication de l’armée ainsi qu’aux besoins dans les secteurs de la sécurité publique. Ces domaines partagent souvent les mêmes exigences que les chemins de fers. Ainsi, la radio cognitive a montré un potentiel prometteur pour répondre aux besoins listés précédemment. Une des principales fonctionnalités d’un dispositif de radio cognitive est de prendre conscience de son environnement radioélectrique et de détecter les bandes disponibles. Trois principaux éléments définissent l’environnement de la radio cognitive : l’utilisateur, les règles d’accès au spectre radio et les domaines radio. Cette thèse met en avant plusieurs contributions relatives à la reconnaissance de l’environnement radiofréquence et la détection de bandes libres. Plus spécifiquement, ces contributions portent sur la reconnaissance par la radio cognitive de l’occupation du spectre et de la modulation des signaux présents dans les bandes analysées. Ces fonctions ont été conçues pour le contexte ferroviaire, c’est-à-dire la grande vitesse et un environnement électromagnétique difficile en présence de bruit impulsif.An essential goal of railway operators is to increase safety, reduce operation and maintenance costs, and increase attraction and profit by offering new services to passengers. These objectives will be reached thanks to a huge increase of data fluxes exchanges between railways stakeholders and infrastructures.Interoperability, spectral efficiency, optimization of radio resource usages, and improvement of communications reliability are of significant interest for railway applications. The Cognitive Radio (CR) research has been successfully applied to meet the communication needs of the military as well as the public-safety sectors, which share many of the same needs as railway. CRs have shown significant promise to answer all of the previously listed requirements. One of the main capabilities of a CR device is to sense and finally become aware of its environment. Three major domains define the environment of the CR, namely, the user, policy, and radio domains. This thesis highlights several contributions to radio environment awareness of a CR device. More specifically, these contributions lie in the spectrum awareness and waveform awareness functions of the CR. We designed these functions for the railways context, that is, a high speed vehicular context, besides difficult electromagnetic environments resulting a heavy-tailed impulsive noise

Blind Spectrum Sensing Using Extreme Eigenvalues for Cognitive Radio Networks

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Sparse Code Multiple Access: Potentials and Challenges

International audienceThe massive connectivity is among other unprecedented requirements which are expected to be satisfied in order to follow the perpetual increase of connected devices in the era of Internet of Things. In contrast to the family of conventional orthogonal multiple access schemes, the key distinguishing feature of non-orthogonal multiple access (NOMA) is its capacity to support the massive connectivity. Sparse code multiple access (SCMA) is one of the powerful schemes of code-domain NOMA (CD-NOMA) and is among the promising candidates of multiple access techniques to be employed in future generations of wireless communication systems thanks to the sparsity pattern of its codebooks. This technique has been actively investigated in recent years. In this paper, we provide a comprehensive survey of the state-of-the-art of SCMA. First, we will pinpoint SCMA place in the NOMA landscape including power-domain NOMA and CD-NOMA with the aim of justifying why SCMA is prominent. Then, its system architecture is highlighted and its basic principles are presented, afterwards a review of exiting codebook designs and available SCMA detectors is provided, before showing how resources are expected to be assigned, and how SCMA can be combined with other existing and emerging technologies. Finally, we present a range of future research trends and challenging open issues that should be addressed to optimize SCMA performance

An adaptive Uplink SCMA Scheme Based on Channel State Information

International audienceThe sparse code multiple access (SCMA) is one of the promoting candidate of code-domain non-orthogonal multiple access (CD-NOMA) for the upcoming generations of wireless communications systems, and it has been actively investigated in recent years. The key distinguishing feature of SCMA comes from the gain of its multi-dimensional sparse codebooks. Nevertheless, all users have not the same business requirements, and their physical layer needs depend on many factors such as the maximum allowed delay, the required rate and the targeted quality of service. In this paper, an adaptive SCMA scheme is proposed to tackle this problem. The idea is to divide users into different groups such as an adaptive designed codebook is allocated to each group. Unlike the traditional SCMA, the sparsity degree, the constellation size, and the allocated power per user, can be adapted to each group requirements in order to increase the overall performance of an uplink SCMA system. Simulation results show that the proposed scheme outperforms the traditional regular SCMA

Automatic modulation recognition using wavelet transform and neural network

International audienceModulation type is one of the most important characteristics used in signal waveform identification. An algorithm for automatic modulation recognition has been developed and presented in this study. The suggested algorithm is verified using higher order statistical moments of wavelet transform as a features set. A multi-layer neural network with resilient backpropagation learning algorithm is proposed as a classifier. The purpose is to discriminate different M-ary shift keying modulation types and modulation order without any priori signal information. Pre-processing and features subset selection using principal component analysis will reduce the network complexity and increase the recognizer performance

Irregular SCMA System for Enhanced Quality of Service

International audienceAs a scheme of non-orthogonal multiple access in the code-domain, sparse code multiple access (SCMA) is one of the promoting candidate for the upcoming generations of wireless communication systems, and it has been actively investigated in recent years with several challenges about high accuracy codebook design algorithms. Based on the different parameters of SCMA system, for instance, the codebook sparsity degree, we can distinguish two kinds of SCMA system architectures: (i) regular SCMA and (ii) irregular SCMA. In this paper, we investigate first realistic massive communication scenario where, all users have the same channel states but different needs in terms of delay, bandwidth and packet-delivery. However, it is not ideal to equally treat the users when they have different channel states, that may lead to poor quality of service (QoS) for users with bad channel conditions. Motivated by this, we explore new approaches to improve the irregular SCMA structure based on the QoS needed by each user. We propose an optimized irregular SCMA to reply to these needs based on an algorithm of sparsity degree assignment according to the QoS parameters. Simulation results confirms that the different objectives were achieved