Compensation numérique pour convertisseur large bande hautement parallélisé.

Time-interleaved analog-to-digital converters (TIADC) seem to be the holy grail of analog-to-digital conversion. Theoretically, their sampling speed can be increased, very simply, by duplicating the sub-converters. The real world is different because mismatches between the converters strongly reduce the TIADC performance, especially when trying to push forward the sampling speed, or the resolution of the converter. Using background digital mismatch calibration can alleviate this limitation. The first part of the thesis is dedicated to studying the sources and effects of mismatches in a TIADC. Performance metrics such as the SNDR and the SFDR are derived as a function of the mismatch levels. In the second part, new background digital mismatch calibration techniques are presented. They are able to reduce the offset, gain, skew and bandwidth mismatch errors. The mismatches are estimated by using the statistical properties of the input signal and digital filters are used to reconstruct the correct output samples. In the third part, a 1.6 GS/s TIADC circuit, implementing offset, gain and skew mismatch calibration, demonstrates a reduction of the mismatch spurs down to a level of -70 dBFS, up to an input frequency of 750 MHz. The circuit achieves the lowest level of mismatches among TIADCs in the same frequency range, with a reasonable power and area, in spite of the overhead caused by the calibration.Les convertisseurs analogique-numérique à entrelacement temporel (TIADC) semblent être une solution prometteuse dans le monde de la conversion analogique-numérique. Leur fréquence d’échantillonnage peut théoriquement être augmentée en augmentant le nombre de convertisseurs en parallèle. En réalité, des désappariements entre les convertisseurs peuvent fortement dégrader les performances, particulièrement à haute fréquence d’échantillonnage ou à haute résolution. Ces défauts d’appariement peuvent être réduits en utilisant des techniques de calibration en arrière-plan. La première partie de cette thèse est consacrée à l’étude des sources et effets des différents types de désappariements dans un TIADC. Des indicateurs de performance tels que le SNDR ou la SFDR sont exprimés en fonction du niveau des désappariements. Dans la deuxième partie, des nouvelles techniques de calibration sont proposées. Ces techniques permettent de réduire les effets des désappariements d’offset, de gain, d’instant d’échantillonnage et de bande passante. Les désappariements sont estimés en se basant sur des propriétés statistiques du signal et la reconstruction des échantillons de sortie se fait en utilisant des filtres numériques. La troisième partie démontre les performance d’un TIADC fonctionnant a une fréquence d’échantillonnage de 1.6 GE/s et comprenant les calibration d’offset, de gain et d’instant d’échantillonnage proposées. Les raies fréquentielles dues aux désappariements sont réduites à un niveau de -70dBc jusqu’à une fréquence d’entrée de 750 MHz. Ce circuit démontre une meilleure correction de désappariements que des circuits similaires récemment publiés, et ce avec une augmentation de puissance consommée et de surface relativement faible

FPGA Implementation of Channel Mismatch Calibration in TIADCs for Signals in Any Nyquist Bands

This paper presents a fully digital background calibration technique of the gain and timing mismatches in undersampling Time-Interleaved Analog-to-Digital Converters for the wideband bandlimited input signal at any Nyquist bands. The proposed technique does not require an additional reference channel nor a pilot input. The channel mismatch parameters are estimated based on the mismatch frequency band. The experimental results shows the efficiency of the proposed mitigation technique with the SNDR improvement of 16dB for 4-channel 60dB SNR TIADC clocked at 2.7GHz given a multi-tone input occupied at the third Nyquist band. The hardware architecture of the proposed technique is designed and validated on Altera FPGA DE4 board. The synthesized design utilizes a very little amount of the hardware resource in the FPGA chip and works correctly on a Hardware-In-the-Loop emulation framework

Wideband CMOS Data Converters for Linear and Efficient mmWave Transmitters

With continuously increasing demands for wireless connectivity, higher\ua0carrier frequencies and wider bandwidths are explored. To overcome a limited transmit power at these higher carrier frequencies, multiple\ua0input multiple output (MIMO) systems, with a large number of transmitters\ua0and antennas, are used to direct the transmitted power towards\ua0the user. With a large transmitter count, each individual transmitter\ua0needs to be small and allow for tight integration with digital circuits. In\ua0addition, modern communication standards require linear transmitters,\ua0making linearity an important factor in the transmitter design.In this thesis, radio frequency digital-to-analog converter (RF-DAC)-based transmitters are explored. They shift the transition from digital\ua0to analog closer to the antennas, performing both digital-to-analog\ua0conversion and up-conversion in a single block. To reduce the need for\ua0computationally costly digital predistortion (DPD), a linear and wellbehaved\ua0RF-DAC transfer characteristic is desirable. The combination\ua0of non-overlapping local oscillator (LO) signals and an expanding segmented\ua0non-linear RF-DAC scaling is evaluated as a way to linearize\ua0the transmitter. This linearization concept has been studied both for\ua0the linearization of the RF-DAC itself and for the joint linearization of\ua0the cascaded RF-DAC-based modulator and power amplifier (PA) combination.\ua0To adapt the linearization, observation receivers are needed.\ua0In these, high-speed analog-to-digital converters (ADCs) have a central\ua0role. A high-speed ADC has been designed and evaluated to understand\ua0how concepts used to increase the sample rate affect the dynamic performance

Post Conversion Correction of Non-Linear Mismatches for Time Interleaved Analog-to-Digital Converters

Time Interleaved Analog-to-Digital Converters (TI-ADCs) utilize an architecture which enables conversion rates well beyond the capabilities of a single converter while preserving most or all of the other performance characteristics of the converters on which said architecture is based. Most of the approaches discussed here are independent of architecture; some solutions take advantage of specific architectures. Chapter 1 provides the problem formulation and reviews the errors found in ADCs as well as a brief literature review of available TI-ADC error correction solutions. Chapter 2 presents the methods and materials used in implementation as well as extend the state of the art for post conversion correction. Chapter 3 presents the simulation results of this work and Chapter 4 concludes the work. The contribution of this research is three fold: A new behavioral model was developed in SimulinkTM and MATLABTM to model and test linear and nonlinear mismatch errors emulating the performance data of actual converters. The details of this model are presented as well as the results of cumulant statistical calculations of the mismatch errors which is followed by the detailed explanation and performance evaluation of the extension developed in this research effort. Leading post conversion correction methods are presented and an extension with derivations is presented. It is shown that the data converter subsystem architecture developed is capable of realizing better performance of those currently reported in the literature while having a more efficient implementation

A 0.9-Nyquist-Band Digital Timing Mismatch Correction for Time-Interleaved ADCs Achieving Delay Tuning Range of 0.12-Sample-Period

Time-interleaved analog-to-digital converters (TIADC) require channel matching in terms of offset, gain, and sampling clock skew to achieve best data conversion performance. Conventionally, correction of skew mismatch is realized with analog delay lines, making it challenging for high-speed ADC designs to achieve fine delay resolution over wide tuning range while maintaining low clock jitter. Digital skew correction allows greater flexibility than analog solutions, but is hindered by a significant hardware footprint. This paper demonstrates digital filter-based timing skew correction approach suitable for on-chip implementation. In a 10-bit 8-channel TI-ADC the proposed structure corrects mismatch magnitudes up to 0.12 sample period across 0.9 Nyquist band while requiring only 65% hardware of similar architectures of equivalent performance. The presented digital circuit uses reduced combinational paths and operates at a clock rate of single ADC channel, making it applicable for digitally-assisted high-speed TI-ADCs.acceptedVersionPeer reviewe

Nonlinear models and algorithms for RF systems digital calibration

Focusing on the receiving side of a communication system, the current trend in pushing the digital domain ever more closer to the antenna sets heavy constraints on the accuracy and linearity of the analog front-end and the conversion devices. Moreover, mixed-signal implementations of Systems-on-Chip using nanoscale CMOS processes result in an overall poorer analog performance and a reduced yield. To cope with the impairments of the low performance analog section in this "dirty RF" scenario, two solutions exist: designing more complex analog processing architectures or to identify the errors and correct them in the digital domain using DSP algorithms. In the latter, constraints in the analog circuits' precision can be offloaded to a digital signal processor. This thesis aims at the development of a methodology for the analysis, the modeling and the compensation of the analog impairments arising in different stages of a receiving chain using digital calibration techniques. Both single and multiple channel architectures are addressed exploiting the capability of the calibration algorithm to homogenize all the channels' responses of a multi-channel system in addition to the compensation of nonlinearities in each response. The systems targeted for the application of digital post compensation are a pipeline ADC, a digital-IF sub-sampling receiver and a 4-channel TI-ADC. The research focuses on post distortion methods using nonlinear dynamic models to approximate the post-inverse of the nonlinear system and to correct the distortions arising from static and dynamic errors. Volterra model is used due to its general approximation capabilities for the compensation of nonlinear systems with memory. Digital calibration is applied to a Sample and Hold and to a pipeline ADC simulated in the 45nm process, demonstrating high linearity improvement even with incomplete settling errors enabling the use of faster clock speeds. An extended model based on the baseband Volterra series is proposed and applied to the compensation of a digital-IF sub-sampling receiver. This architecture envisages frequency selectivity carried out at IF by an active band-pass CMOS filter causing in-band and out-of-band nonlinear distortions. The improved performance of the proposed model is demonstrated with circuital simulations of a 10th-order band pass filter, realized using a five-stage Gm-C Biquad cascade, and validated using out-of-sample sinusoidal and QAM signals. The same technique is extended to an array receiver with mismatched channels' responses showing that digital calibration can compensate the loss of directivity and enhance the overall system SFDR. An iterative backward pruning is applied to the Volterra models showing that complexity can be reduced without impacting linearity, obtaining state-of-the-art accuracy/complexity performance. Calibration of Time-Interleaved ADCs, widely used in RF-to-digital wideband receivers, is carried out developing ad hoc models because the steep discontinuities generated by the imperfect canceling of aliasing would require a huge number of terms in a polynomial approximation. A closed-form solution is derived for a 4-channel TI-ADC affected by gain errors and timing skews solving the perfect reconstruction equations. A background calibration technique is presented based on cyclo-stationary filter banks architecture. Convergence speed and accuracy of the recursive algorithm are discussed and complexity reduction techniques are applied

Data Conversion Within Energy Constrained Environments

Within scientific research, engineering, and consumer electronics, there is a multitude of new discrete sensor-interfaced devices. Maintaining high accuracy in signal quantization while staying within the strict power-budget of these devices is a very challenging problem. Traditional paths to solving this problem include researching more energy-efficient digital topologies as well as digital scaling.;This work offers an alternative path to lower-energy expenditure in the quantization stage --- content-dependent sampling of a signal. Instead of sampling at a constant rate, this work explores techniques which allow sampling based upon features of the signal itself through the use of application-dependent analog processing. This work presents an asynchronous sampling paradigm, based off the use of floating-gate-enabled analog circuitry. The basis of this work is developed through the mathematical models necessary for asynchronous sampling, as well the SPICE-compatible models necessary for simulating floating-gate enabled analog circuitry. These base techniques and circuitry are then extended to systems and applications utilizing novel analog-to-digital converter topologies capable of leveraging the non-constant sampling rates for significant sample and power savings

Estimation and Calibration Algorithms for Distributed Sampling Systems

Thesis Supervisor: Gregory W. Wornell Title: Professor of Electrical Engineering and Computer ScienceTraditionally, the sampling of a signal is performed using a single component such as an analog-to-digital converter. However, many new technologies are motivating the use of multiple sampling components to capture a signal. In some cases such as sensor networks, multiple components are naturally found in the physical layout; while in other cases like time-interleaved analog-to-digital converters, additional components are added to increase the sampling rate. Although distributing the sampling load across multiple channels can provide large benefits in terms of speed, power, and resolution, a variety mismatch errors arise that require calibration in order to prevent a degradation in system performance. In this thesis, we develop low-complexity, blind algorithms for the calibration of distributed sampling systems. In particular, we focus on recovery from timing skews that cause deviations from uniform timing. Methods for bandlimited input reconstruction from nonuniform recurrent samples are presented for both the small-mismatch and the low-SNR domains. Alternate iterative reconstruction methods are developed to give insight into the geometry of the problem. From these reconstruction methods, we develop time-skew estimation algorithms that have high performance and low complexity even for large numbers of components. We also extend these algorithms to compensate for gain mismatch between sampling components. To understand the feasibility of implementation, analysis is also presented for a sequential implementation of the estimation algorithm. In distributed sampling systems, the minimum input reconstruction error is dependent upon the number of sampling components as well as the sample times of the components. We develop bounds on the expected reconstruction error when the time-skews are distributed uniformly. Performance is compared to systems where input measurements are made via projections onto random bases, an alternative to the sinc basis of time-domain sampling. From these results, we provide a framework on which to compare the effectiveness of any calibration algorithm. Finally, we address the topic of extreme oversampling, which pertains to systems with large amounts of oversampling due to redundant sampling components. Calibration algorithms are developed for ordering the components and for estimating the input from ordered components. The algorithms exploit the extra samples in the system to increase estimation performance and decrease computational complexity