Review of Parallel Decoding of Space-time Block Codes toward 4G Wireless and Mobile Communications

AbstractThis paper presents a review of recent developments in the area of STBC decoding particularly parallel decoding of full-rate full-diversity STBCs toward real-time 4G wireless communications. After reviewing some parallel STBC decoding techniques and presenting one of the most promising types of parallel processors suitable for the 4G SDR the SIMD processor, the paper shows that parallel decoding of the Golden Code on the ClearSpeed CSX700 SIMD processor achieves a speedup of up to 30 times. The paper highlights the potential to achieve real-time decoding of high-rate STBCs with the use of robust parallel processors

GPS Multipath Detection in the Frequency Domain

Multipath is among the major sources of errors in precise positioning using GPS and continues to be extensively studied. Two Fast Fourier Transform (FFT)-based detectors are presented in this paper as GPS multipath detection techniques. The detectors are formulated as binary hypothesis tests under the assumption that the multipath exists for a sufficient time frame that allows its detection based on the quadrature arm of the coherent Early-minus-Late discriminator (Q EmL) for a scalar tracking loop (STL) or on the quadrature (Q EmL) and/or in-phase arm (I EmL) for a vector tracking loop (VTL), using an observation window of N samples. Performance analysis of the suggested detectors is done on multipath signal data acquired from the multipath environment simulator developed by the German Aerospace Centre (DLR) as well as on multipath data from real GPS signals. Application of the detection tests to correlator outputs of scalar and vector tracking loops shows that they may be used to exclude multipath contaminated satellites from the navigation solution. These detection techniques can be extended to other Global Navigation Satellite Systems (GNSS) such as GLONASS, Galileo and Beidou.Comment: 2016 European Navigation Conference (ENC 2016), May 2016, Helsinki, Finland. Proceedings of the 2016 European Navigation Conference (ENC 2016

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Algorithmes de poursuite scalaire et vectorielle avec détection et exclusion de fautes pour récepteurs GNSS : conception et évaluation des performances

Navigation with Global Navigation Satellite Systems (GNSS) is a real challenge in harsh environments (suburban, urban, heavy foliage) due to multipath and signal blockage. This thesis proposes a number of GNSS receiver architectural and algorithmic solutions to deal with this challenge. These solutions aim at exploiting the strengths of scalar and vector tracking while minimizing their weaknesses and at utilizing the efficiency of some nonlinear Bayesian filtering techniques in addressing the nonlinearities and non-Gaussianities associated with the navigation and vector tracking problem. Attention is given to some Bayesian estimators that approximate the posterior distribution without linearizing the filtering model, namely the unscented Kalman and particle filtering methods, as well as to the extended Kalman filter, whose posterior estimation is grounded on linearization of the filtering model.First, a brief literature review that presents the fundamentals of GNSS and GNSS receivers together with the applied navigation and tracking algorithms is provided. Then an investigation of the GNSS receiver operation in multipath environments is performed. The thesis proposes models for characterizing multipath induced tracking errors in a vector tracking loop. These models make it possible to express the tracking errors with respect to multipath delay, multipath phase and multipath fading frequency. By exploiting the fact that multipath presence is mirrored on the Early-minus-Late correlator output, novel multipath detectors are devised. A correlator-based non-line-of-sight detector is designed as well. Attention is then directed towards the design of robust tracking and positioning GNSS receiver architectures that incorporate the proposed detectors among other signal quality indicators. A vector tracking scheme capable of detecting and excluding unhealthy measurements from position-velocity-time calculation in the navigator using correlator-based signal quality indicators is suggested. Two other novel tracking schemes, the adaptive scalar-vector tracking loop and the conjoint scalar-vector tracking loop, with the same fault detection and exclusion capability, are formulated. They benefit from vector tracking robustness in harsh environments and scalar tracking positioning accuracy in open sky environments. Experimental results show that the proposed solutions have better tracking and positioning performance than the usual scalar and vector tracking loops. Finally, the thesis presents a number of nonlinear Bayesian filtering approaches to solve the navigation and vector tracking problem. Iterative and adaptive strategies as applied to the unscented Kalman filter are studied. A novel unscented particle filter approach, the iterated adaptive unscented particle filter (IAUPF), is proposed. This approach exploits the convergence properties of iterative methods, the divergence suppression benefits of adaptive filters and the synergy of unscented Kalman and particle filtering approaches. Monte-Carlo simulations conducted with a posterior Cramér-Rao lower bound used as benchmarking reference as well as experimental results demonstrate that the IAUPF outperforms the other Bayesian estimators that are presentedLa navigation avec les systèmes de navigation par satellites (GNSS) est un réel défi dans des environnements contraints (semi-urbain, urbain, feuillage dense) à cause des multitrajets et du masquage du signal. Cette thèse propose un nombre de solutions architecturales et algorithmiques pour le récepteur GNSS afin de pallier ces problèmes. Ces solutions se veulent capables d’exploiter les atouts des poursuites scalaire et vectorielle tout en minimisant leurs défauts et de profiter de l’efficacité de certaines techniques de filtrage Bayésien non linéaire quant à aborder la non-Gaussianité et les non-linéarités associées au problème de navigation et de poursuite vectorielle. Une attention particulière est accordée à certains estimateurs Bayésiens qui essaient d’approximer la loi a posteriori sans linéariser le modèle de filtrage, notamment le filtre de Kalman et les méthodes de filtrage particulaire, mais aussi au filtre de Kalman étendu, dont l’estimation de la loi a posteriori est basée sur la linéarisation du modèle de filtrage. En premier lieu, une brève étude bibliographique présentant les fondamentaux des systèmes et des récepteurs GNSS ainsi que les algorithmes de navigation et de poursuite y associés est faite. Ensuite le fonctionnement d’un récepteur GNSS en milieux contraints est investigué. La thèse propose des modèles pour caractériser les erreurs de poursuite induites par les multitrajets dans une boucle de poursuite vectorielle. Ces modèles permettent d’exprimer les erreurs de poursuite en fonction du délai, de la phase et de la fréquence d’évanouissement des multitrajets. En exploitant le fait que la présence des multitrajets se reflète sur la sortie moins des corrélateurs, de nouveaux détecteurs de multitrajets sont formulés. Un détecteur de masquage du signal direct est aussi proposé. L’attention se tourne ensuite vers la conception d’architectures robustes de poursuite et positionnement pour un récepteur GNSS, incorporant les détecteurs proposés et d’autres indicateurs de qualité. Une boucle de poursuite vectorielle capable de détecter et d’exclure des mesures qui ne sont pas saines du calcul de la solution de navigation en utilisant les indicateurs de qualité est proposée. Deux autres boucles de poursuite, la boucle de poursuite adaptative scalaire-vectorielle et la boucle de poursuite conjointe scalaire-vectorielle, avec la même capacité de détection et exclusion de fautes, sont formulées. Elles bénéficient de la robustesse de la poursuite vectorielle en milieux contraints et de la précision de la poursuite scalaire en milieux dégagés. Des résultats expérimentaux montrent que les solutions conçues offrent une meilleure alternative de poursuite et positionnement par rapport aux boucles usuelles de poursuite scalaire et de poursuite vectorielle. Enfin, la thèse présente des approches de filtrage Bayésien non linéaire pour résoudre le problème de navigation et de poursuite vectorielle. Des stratégies de filtrage itératives et adaptatives appliquées au filtre de Kalman sont étudiées. Une nouvelle approche de filtrage particulaire dénommée filtre particulaire itératif et adaptatif (IAUPF) est formulée. Cette approche exploite les propriétés de convergence des méthodes itératives, l’immunité à la divergence dont jouissent les filtres adaptatifs, et la synergie entre les approches de filtrage particulaire et de Kalman. Des simulations de Monte Carlo avec une borne inférieure de Cramér-Rao a posteriori comme référence ainsi que des résultats expérimentaux montrent que l’approche IAUPF a une meilleure performance comparativement aux autres estimateurs Bayésiens présenté

GPS Multipath Induced Errors for the Vector Tracking Loop: Insight into Multipath Detection

International audienceMultipath is one of the most serious sources of error in the Global Positioning System (GPS). Multipath distorts the correlation function used for carrier phase and code delay measurements, and therefore induces errors in these measurements and consequently in the calculated positioning solution. This paper aims at characterizing multipath induced tracking errors for a vector tracking loop (VTL). The paper contributes to the characterization of tracking and positioning errors for VTLs by deriving models that allow the analysis of both code and carrier tracking errors with respect to multipath delay, multipath phase and multipath fading frequency. The paper further provides a simple multipath detection technique based on correlator outputs, showing another advantage of the VTL over the scalar tracking loop (STL)

Quantitative trait loci and candidate genes for physico‐chemical traits related to tuber quality in greater yam ( Dioscorea alata L.)

International audienceBACKGROUND Starch, dry matter content (DMC), proteins, and sugars are among the major influences on yam tuber quality. Genetic improvement programs need simple, rapid, and low‐cost tools to screen large populations. The objectives of this work were, using a quantitative trait loci mapping approach (QTL) on two diploid full‐sib segregating populations, (i) to acquire knowledge about the genetic control of these traits; (ii) to identify markers linked to the genomic regions controlling each trait, which are useful for marker‐assisted selection (MAS); (iii) to validate the QTLs on a diversity panel; and (iv) to identify candidate genes from the validated QTLs. RESULTS Heritability for all traits was moderately high to high. Significant correlations were observed between traits. A total of 25 QTLs were identified, including six for DMC, six for sugars, six for proteins, and seven for starch. The phenotypic variance explained by individual QTLs ranged from 14.3% to 28.6%. The majority of QTLs were validated on a diversity panel, showing that they are not specific to the genetic background of the progenitors. The approximate physical location of validated QTLs allowed the identification of candidate genes for all studied traits. Those detected for starch content were mainly enzymes involved in starch and sucrose metabolism, whereas those detected for sugars were mainly involved in respiration and glycolysis. CONCLUSION The validated QTLs will be useful for breeding programs using MAS to improve the quality of yam tubers. The putative genes should be useful in providing a better understanding of the physiological and molecular basis of these important tuber quality traits. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry

Predicting quality, texture and chemical content of yam ( Dioscorea alata L.) tubers using near infrared spectroscopy

International audienceDespite the importance of yam ( Dioscorea spp.) tuber quality traits, and more precisely texture attributes, high-throughput screening methods for varietal selection are still lacking. This study sets out to define the profile of good quality pounded yam and provide screening tools based on predictive models using near infrared reflectance spectroscopy. Seventy-four out of 216 studied samples proved to be moldable, i.e. suitable for pounded yam. While samples with low dry matter (4%) and high protein (>6%) contents, low hardness (0.5) and high cohesiveness (>0.5) grouped mostly non-moldable genotypes, the opposite was not true. This outline definition of a desirable chemotype may allow breeders to choose screening thresholds to support their choice. Moreover, traditional near infrared reflectance spectroscopy quantitative prediction models provided good prediction for chemical aspects (R 2 > 0.85 for dry matter, starch, protein and sugar content), but not for texture attributes (R 2 < 0.58). Conversely, convolutional neural network classification models enabled good qualitative prediction for all texture parameters but hardness (i.e. an accuracy of 80, 95, 100 and 55%, respectively, for moldability, cohesiveness, springiness and hardness). This study demonstrated the usefulness of near infrared reflectance spectroscopy as a high-throughput way of phenotyping pounded yam quality. Altogether, these results allow for an efficient screening toolbox for quality traits in yams

Identification and validation of QTLs for tuber quality related traits in greater yam (Dioscorea alata L.)

International audienceTwo Dioscorea alata populations were generated by hand pollination between contrasted diploid genitors. Population A (74F × Kabusa) was composed of 121 progenies while population B (74F × 14M) involved 193 progenies. These two populations were assessed over two consecutive years regarding important tuber quality traits. Analysis of variance showed that the genotype had the greatest influence on the phenotypic scores. Also for some traits, effect of the year_replicate was strong. The heritabilities of most traits were high. Based on these data and a reference high-density genetic map of greater yam, a total of 34 quantitative trait loci (QTLs) were detected on 8 of the 20 yam chromosomes. They corresponded to five of each of the following traits: tuber size, shape regularity, tubercular roots, skin texture, tuber flesh oxidation, six for oxidation ratio and three for flesh colour. The fraction of total phenotypic variance attributable to a single QTL ranged from 11.1 to 43.5%. We detected significant correlations between traits and QTL colocalizations that were consistent with these correlations. A majority of QTLs (62%) were found on linkage group LG16, indicating that this chromosome could play a major role in genetic control of the investigated traits. In addition, an inversion involving this chromosome was detected in the Kabusa male. Nine QTLs were validated on a diversity panel, including three for tuber size, three for shape regularity, two for skin texture and one for tubercular roots. The approximate physical localization of validated QTLs allowed the identification of various candidates genes. The validated QTLs should be useful for breeding programs using marker-assisted selection to improve yam tuber quality