8 research outputs found
Ăchantillonnage Non Uniforme : Application aux filtrages et aux conversions CAN/CNA (Convertisseurs Analogique-NumĂ©rique et NumĂ©rique/Analogique) dans les tĂ©lĂ©communications par satellite
La thĂ©orie de l'Ă©chantillonnage uniforme des signaux, dĂ©veloppĂ©e en particulier par C. Shannon, est Ă l'origine du traitement numĂ©rique du signal. Depuis, de nombreux travaux ont Ă©tĂ© consacrĂ©s Ă l'Ă©chantillonnage non uniforme. Celui-ci permet, d'une part, de modĂ©liser les imperfections des dispositifs d'Ă©chantillonnage uniforme. D'autre part, l'Ă©chantillonnage peut ĂȘtre effectuĂ© de maniĂšre dĂ©libĂ©rĂ©ment non uniforme afin de bĂ©nĂ©ficier de propriĂ©tĂ©s particuliĂšres, notamment un assouplissement des conditions portant sur le choix de la frĂ©quence moyenne d'Ă©chantillonnage. La plupart de ces travaux reste dans un cadre thĂ©orique en adoptant des schĂ©mas d'Ă©chantillonnage et des modĂšles de signaux simplifiĂ©s. Or, actuellement, dans de nombreux domaines d'application, tels que les communications par satellites, la conversion analogique-numĂ©rique s'effectue sous des contraintes fortes pour les largeurs de bande mises en jeu, en raison notamment des frĂ©quences trĂšs Ă©levĂ©es utilisĂ©es. Ces conditions opĂ©rationnelles accentuent les imperfections des dispositifs Ă©lectroniques rĂ©alisant l'Ă©chantillonnage et induisent le choix de modĂšles de signaux et de schĂ©mas d'Ă©chantillonnage spĂ©cifiques. Cette thĂšse a pour objectif gĂ©nĂ©ral d'identifier des modĂšles d'Ă©chantillonnage adaptĂ©s Ă ce cadre applicatif. Ceux-ci s'appliquent Ă des signaux alĂ©atoires passe-bande, qui constituent un modĂšle classique en tĂ©lĂ©communications. Ils doivent prendre en compte des facteurs technologiques, Ă©conomiques ainsi que des contraintes bord de complexitĂ© et Ă©ventuellement intĂ©grer des fonctionnalitĂ©s propres aux tĂ©lĂ©communications. La premiĂšre contribution de cette thĂšse est de dĂ©velopper des formules d'Ă©chantillonnage non uniforme qui intĂšgrent dans le domaine numĂ©rique des fonctionnalitĂ©s dĂ©licates Ă implĂ©menter dans le domaine analogique aux frĂ©quences considĂ©rĂ©es. La deuxiĂšme contribution consiste Ă caractĂ©riser et Ă compenser les erreurs de synchronisation de dispositifs d'Ă©chantillonnage non uniforme particuliers, Ă savoir les convertisseurs analogique-numĂ©rique entrelacĂ©s temporellement, via des mĂ©thodes supervisĂ©es ou aveugles
Conversion Numérique-Analogique sélective d'un signal passe-bande soumis à des interférences
National audienceCet article propose une mĂ©thode qui permet une conversion numĂ©rique-analogique sĂ©lective dâun processus alĂ©atoire passe-bande soumis Ă des interfĂ©rences. Cette mĂ©thode permet dâeffectuer simultanĂ©ment la conversion numĂ©rique-analogique du signal et le rejet de lâinterfĂ©rence Ă partir des Ă©chantillons du processus observĂ© : aucun dĂ©modulation prĂ©alable du processus passe-bande nâest nĂ©cessaire et le filtrage est effectuĂ© dans le domaine temporel grĂące Ă lâexpression explicite des coefficients du filtre. La mĂ©thode se base sur lâutilisation dâun schĂ©ma dâĂ©chantillonnage pĂ©riodique non uniforme appelĂ© PNS2 (pour Periodic Nonuniform Sampling dâordre 2) qui utilise deux sĂ©quences dâĂ©chantillonnage pĂ©riodique entrelacĂ©es. Des formules appropriĂ©es sont Ă©tablies afin de reconstruire le signal, permettant Ă©galement de supprimer lâinterfĂ©rence grĂące Ă un filtrage sĂ©lectif. Lâobservation sur une fenĂȘtre de taille infinie (nombre infini dâĂ©chantillons) mĂšne Ă une reconstruction exacte. Cependant, dans les applications, la conversion numĂ©rique-analogique est gĂ©nĂ©ralement pratiquĂ©e en temps rĂ©el Ă lâaide dâune fenĂȘtre dâobservation glissante et de taille finie (nombre fini dâĂ©chantillons). Ainsi les formules de reconstruction doivent avoir un taux de convergence Ă©levĂ©. Cet article propose donc des formules avec diffĂ©rents taux de convergence grĂące Ă lâutilisation de filtres avec des fonctions de tranfert de rĂ©gularitĂ© croissante. Des simulations se basant sur la variation de diffĂ©rents paramĂštres expĂ©rimentaux nous ont permis de tester la mĂ©thode
Estimation du retard en échantillonnage périodique non uniforme - Application aux CAN entrelacés désynchronisés
Augmenter la frĂ©quence dâĂ©chantillonnage des Convertisseurs Analogique NumĂ©rique (CAN) constitue actuellement un dĂ©fi dans de nombreux domaines et en particulier dans les tĂ©lĂ©communications. Les CAN entrelacĂ©s constituent une solution technique pour lâĂ©chantillonnage Ă haute frĂ©quence. Ils sont obtenus par entrelacement temporel et multiplexage de plusieurs CAN fonctionnant Ă faible frĂ©quence. Toutefois,lâopĂ©ration inverse de CNA Ă©tant basĂ©e sur lâhypothĂšse dâun Ă©chantillonnage global uniforme, la synchronisation entre les CAN doit ĂȘtre parfaite. Toute dĂ©synchronisation doit ĂȘtre corrigĂ©e en amont ce qui nĂ©cessite une calibration et des reconfigurations coĂ»teuses au niveau des circuits. Dans cet article, nous considĂ©rons un modĂšle alternatif et plus flexible pour les CAN entrelacĂ©s, basĂ© sur lâutilisation dâun schĂ©ma dâĂ©chantillonnage non uniforme pĂ©riodique. LâintĂ©rĂȘt de ce schĂ©ma est de permettre une reconstruction exacte du signal en prĂ©sence de dĂ©synchronisation lorsque celle-ci est connue. Les Ă©tapes de calibration et de reconfiguration matĂ©rielles ne sont plus alors nĂ©cessaires. La principale contribution de cet article est de proposer deux mĂ©thodes pour lâestimation de la dĂ©synchronisation lâune fonctionnant par auto-calibration du systĂšme et lâautre de maniĂšre aveugle. Les performances de ces mĂ©thodes sont Ă©valuĂ©es en termes dâerreur de reconstruction du signa
Adaptive Estimation and Compensation of the Time Delay in a Periodic Non-uniform Sampling Scheme
High sampling rate Analog-to-Digital Converters (ADCs) can be obtained by time-interleaving low rate (and thus low cost) ADCs into so-called Time-Interleaved ADCs (TI-ADCs). Nevertheless increasing the sampling frequency involves an increasing sensibility of the system to desynchronization between the different ADCs that leads to time-skew errors, impacting the system with non linear distortions. The estimation and compensation of these errors are considered as one of the main challenge to deal with in TI-ADCs. Some methods have been previously proposed, mainly in the field of circuits and systems, to estimate the time-skew error but they mainly involve hardware correction and they lack of flexibility, using an inflexible uniform sampling reference. In this paper, we propose to model the output of L interleaved and desynchronized ADCs with a sampling scheme called Periodic Non-uniform Sampling of order L (PNSL). This scheme has been initially proposed as an alternative to uniform sampling for aliasing cancellation, particularly in the case of bandpass signals. We use its properties here to develop a flexible on-line digital estimation and compensation method of the time delays between the desynchronized channels. The estimated delay is exploited in the PNSL reconstruction formula leading to an accurate reconstruction without hardware correction and without any need to adapt the sampling operation. Our method can be used in a simple Built-In Self-Test (BIST) strategy with the use of learning sequences and our model appears more flexible and less electronically expensive, following the principles of âDirty Radio Frequencyâ paradigm: designing imperfect analog circuits with subsequently digital corrections of these imperfections
Adaptive Estimation and Compensation of the Time Delay in a Periodic Non-uniform Sampling Scheme
High sampling rate Analog-to-Digital Converters (ADCs) can be obtained by time-interleaving low rate (and thus low cost) ADCs into so-called Time-Interleaved ADCs (TI-ADCs). Nevertheless increasing the sampling frequency involves an increasing sensibility of the system to desynchronization between the different ADCs that leads to time-skew errors, impacting the system with non linear distortions. The estimation and compensation of these errors are considered as one of the main challenge to deal with in TI-ADCs. Some methods have been previously proposed, mainly in the field of circuits and systems, to estimate the time-skew error but they mainly involve hardware correction and they lack of flexibility, using an inflexible uniform sampling reference. In this paper, we propose to model the output of L interleaved and desynchronized ADCs with a sampling scheme called Periodic Non-uniform Sampling of order L (PNSL). This scheme has been initially proposed as an alternative to uniform sampling for aliasing cancellation, particularly in the case of bandpass signals. We use its properties here to develop a flexible on-line digital estimation and compensation method of the time delays between the desynchronized channels. The estimated delay is exploited in the PNSL reconstruction formula leading to an accurate reconstruction without hardware correction and without any need to adapt the sampling operation. Our method can be used in a simple Built-In Self-Test (BIST) strategy with the use of learning sequences and our model appears more flexible and less electronically expensive, following the principles of âDirty Radio Frequencyâ paradigm: designing imperfect analog circuits with subsequently digital corrections of these imperfections
Non Uniform Sampling : Application to filtering and ADC/DAC conversions (Analog-to-Digital and Digital-to-Analog) in the telecommunications by satellite
La thĂ©orie de l'Ă©chantillonnage uniforme des signaux, dĂ©veloppĂ©e en particulier par C. Shannon, est Ă l'origine du traitement numĂ©rique du signal. Depuis, de nombreux travaux ont Ă©tĂ© consacrĂ©s Ă l'Ă©chantillonnage non uniforme. Celui-ci permet, d'une part, de modĂ©liser les imperfections des dispositifs d'Ă©chantillonnage uniforme. D'autre part, l'Ă©chantillonnage peut ĂȘtre effectuĂ© de maniĂšre dĂ©libĂ©rĂ©ment non uniforme afin de bĂ©nĂ©ficier de propriĂ©tĂ©s particuliĂšres, notamment un assouplissement des conditions portant sur le choix de la frĂ©quence moyenne d'Ă©chantillonnage. La plupart de ces travaux reste dans un cadre thĂ©orique en adoptant des schĂ©mas d'Ă©chantillonnage et des modĂšles de signaux simplifiĂ©s. Or, actuellement, dans de nombreux domaines d'application, tels que les communications par satellites, la conversion analogique-numĂ©rique s'effectue sous des contraintes fortes pour les largeurs de bande mises en jeu, en raison notamment des frĂ©quences trĂšs Ă©levĂ©es utilisĂ©es. Ces conditions opĂ©rationnelles accentuent les imperfections des dispositifs Ă©lectroniques rĂ©alisant l'Ă©chantillonnage et induisent le choix de modĂšles de signaux et de schĂ©mas d'Ă©chantillonnage spĂ©cifiques. Cette thĂšse a pour objectif gĂ©nĂ©ral d'identifier des modĂšles d'Ă©chantillonnage adaptĂ©s Ă ce cadre applicatif. Ceux-ci s'appliquent Ă des signaux alĂ©atoires passe-bande, qui constituent un modĂšle classique en tĂ©lĂ©communications. Ils doivent prendre en compte des facteurs technologiques, Ă©conomiques ainsi que des contraintes bord de complexitĂ© et Ă©ventuellement intĂ©grer des fonctionnalitĂ©s propres aux tĂ©lĂ©communications. La premiĂšre contribution de cette thĂšse est de dĂ©velopper des formules d'Ă©chantillonnage non uniforme qui intĂšgrent dans le domaine numĂ©rique des fonctionnalitĂ©s dĂ©licates Ă implĂ©menter dans le domaine analogique aux frĂ©quences considĂ©rĂ©es. La deuxiĂšme contribution consiste Ă caractĂ©riser et Ă compenser les erreurs de synchronisation de dispositifs d'Ă©chantillonnage non uniforme particuliers, Ă savoir les convertisseurs analogique-numĂ©rique entrelacĂ©s temporellement, via des mĂ©thodes supervisĂ©es ou aveugles.The theory of uniform sampling, developed among others by C. Shannon, is the foundation of today digital signal processing. Since then, numerous works have been dedicated to non uniform sampling schemes. On the one hand, these schemes model uniform sampling device imperfections. On the other hand, sampling can be intentionally performed in a non uniform way to benefit from specific properties, in particular simplifications concerning the choice of the mean sampling frequency. Most of these works have focused on theoretical approaches, adopting simplified models for signals and sampling devices. However, in many application domains, such as satellite communications, analog-to-digital conversion is submitted to strong constraints over the involved bandwidth due to the very high frequencies used. These operational conditions enhance the imperfections of the involved electronic devices and require the choice of particular signal models and sampling schemes. This thesis aims at proposing sampling models suitable for this context. These models apply to random band-pass signals, which are the classical models for telecommunication signals. They must take into account technological, economical factors and on-board complexity constraints and allow to integrate particular functionalities useful for telecommunication applications. This thesis first contribution is to develop non uniform sampling formulas that can digitally integrate functionalities that appear to be tricky in the analog domain at the considered frequencies. The thesis second contribution consists in applying non uniform sampling theory to the estimation and compensation of synchronization errors encountered in particular sampling devices, the timeinterleaved analog-to-digital converters. This estimation will be performed through supervised or blind methods
Selective analytic signal construction from a non-uniformly sampled bandpass signal
International audienceThis paper proposes a method that simultaneously builds the analytic signal from non-uniform samples of a bandpass signal and rejects interferences. The analytic signal is required for many onboard operations in communication satellites. This method operates in the time domain and without preliminary demodulation, using Periodic Non-uniform Sampling of order 2 (PNS2). This non-uniform sampling scheme can be easily implemented with available devices. Exact formulas for the analytic signal construction are derived for an infinite observation window (an infinite number of samples). For practical applications, the formulas should also demonstrate a high convergence rate due to the finite observation window. Formulas with increasing convergence rates are thus derived. The proposed method has been tested through simulations according to the number of available samples, the interference parameters and the filter transfer function regularity
Blind estimation of unknown time delay in periodic non-uniform sampling: Application to desynchronized time interleaved-ADCs
International audienceIncreasing the sampling rate of Analog-to-Digital Converters (ADC) is a main challenge in many fields and especially in telecommunications. Time-Interleaved ADCs (TI-ADC) were introduced as a technical solution to reach high sampling rates by time interleaving and multiplexing several low-rate ADCs at the price of a perfect synchronization between them. Indeed, as the signal reconstruction formulas are derived under the assumption of uniform sampling, a desynchronization between the elementary ADCs must be compensated upstream with an online calibration and expensive hardware corrections of the sampling device. Based on the observation that desynchronized TI-ADCs can be effectively modeled using a Periodic Non-uniform Sampling (PNS) scheme, we develop a general method to blindly estimate the time delays involved in PNS. The proposed strategy exploits the signal stationarity properties and thus is simple and quite generalizable to other applications. Moreover, contrarily to state-of-the-art methods, it applies to bandpass signals which is the more judicious application framework of the PNS scheme