Enabling Fine Sample Rate Settings in DSOs with Time-Interleaved ADCs

The time-base used by digital storage oscilloscopes allows limited selections of the sample rate, namely constrained to a few integer submultiples of the maximum sample rate. This limitation offers the advantage of simplifying the data transfer from the analog-to-digital converter to the acquisition memory, and of assuring stability performances, expressed in terms of absolute jitter, that are independent of the chosen sample rate. On the counterpart, it prevents an optimal usage of the memory resources of the oscilloscope and compels to post processing operations in several applications. A time-base that allows selecting the sample rate with very fine frequency resolution, in particular as a rational submultiple of the maximum rate, is proposed. The proposal addresses the oscilloscopes with time-interleaved converters, that require a dedicated and multifaceted approach with respect to architectures where a single monolithic converter is in charge of signal digitization. The proposed time-base allows selecting with fine frequency resolution sample rate values up to 200 GHz and beyond, still assuring jitter performances independent of the sample rate selection

Calibration and Uncertainty Analysis of Sample-Time Error on High Jitter of Samplers

In this paper, we propose an estimation method using multiple in-phase and quadrature (IQ) signals of different frequencies to evaluate the sample-time errors in the sampling oscilloscope. The estimator is implemented by ODRPACK, and a novel iteration scheme is applied to achieve fast convergence without any prior information. Monte-Carlo simulation is conducted to confirm the proposed method. It clearly shows that the multiple IQ approach achieves more accurate results compared to the conventional method. Finally, the criteria for the frequency selection and the signal capture time are investigated

Slice-Less Optical Arbitrary Waveform Measurement (OAWM) in a Bandwidth of More than 600 GHz Using Soliton Microcombs

We propose and demonstrate a novel scheme for optical arbitrary waveform measurement (OAWM) that exploits chip-scale Kerr soliton combs as highly scalable multiwavelength local oscillators (LO) for ultra-broadband full-field waveform acquisition. In contrast to earlier concepts, our approach does not require any optical slicing filters and thus lends itself to efficient implementation on state-of-the-art high-index-contrast integration platforms such as silicon photonics. The scheme allows to measure truly arbitrary waveforms with high accuracy, based on a dedicated system model which is calibrated by means of a femtosecond laser with known pulse shape. We demonstrated the viability of the approach in a proof-of-concept experiment by capturing an optical waveform that contains multiple 16 QAM and 64 QAM wavelength-division multiplexed (WDM) data signals with symbol rates of up to 80 GBd, reaching overall line rates of up to 1.92 Tbit/s within an optical acquisition bandwidth of 610 GHz. To the best of our knowledge, this is the highest bandwidth that has so far been demonstrated in an OAWM experiment

All Digital, Background Calibration for Time-Interleaved and Successive Approximation Register Analog-to-Digital Converters

The growth of digital systems underscores the need to convert analog information to the digital domain at high speeds and with great accuracy. Analog-to-Digital Converter (ADC) calibration is often a limiting factor, requiring longer calibration times to achieve higher accuracy. The goal of this dissertation is to perform a fully digital background calibration using an arbitrary input signal for A/D converters. The work presented here adapts the cyclic Split-ADC calibration method to the time interleaved (TI) and successive approximation register (SAR) architectures. The TI architecture has three types of linear mismatch errors: offset, gain and aperture time delay. By correcting all three mismatch errors in the digital domain, each converter is capable of operating at the fastest speed allowed by the process technology. The total number of correction parameters required for calibration is dependent on the interleaving ratio, M. To adapt the Split-ADC method to a TI system, 2M+1 half-sized converters are required to estimate 3(2M+1) correction parameters. This thesis presents a 4:1 Split-TI converter that achieves full convergence in less than 400,000 samples. The SAR architecture employs a binary weight capacitor array to convert analog inputs into digital output codes. Mismatch in the capacitor weights results in non-linear distortion error. By adding redundant bits and dividing the array into individual unit capacitors, the Split-SAR method can estimate the mismatch and correct the digital output code. The results from this work show a reduction in the non-linear distortion with the ability to converge in less than 750,000 samples

HIGH FIDELITY MEASUREMENT OF BIOELECTRICAL SIGNALS

Previous research regarding the acquisition and electrical characterization of bio- electrical signals of both noninvasive “oriundis in vivo”, generally associated with elec- tromyography (EMG), electrocardiography (EKG), or electroencephalography (EEG), and active “oriundis ex vivo et vitro” material characterization, generally associated with bioimpedance spectroscopy (BIS); while successfully providing beneficial results, was ul- timately plagued with a variety of intrinsic electrical distortions [1] [2]. Conversely, the frequent manifestation of such distortions resulted in an investigation into the nature of their occurrence, which subsequently resulted in my research into the nature of such dis- tortions, the conditions in which they occur, useful techniques to model and minimize their impact, and the underlying methodology needed to obtain the highest fidelity possi- ble when acquiring such measurements. Furthermore, the techniques developed are then applied to both noninvasively obtained “oriundis in vivo” and active “oriundis ex vivo et vitro” applied bioelectrical signals, and the compensated measurements are compared with the uncompensated measurements obtained within the previously mentioned research

A fast engineering approach to high efficiency power amplifier linearization for avionics applications

This PhD thesis provides a fast engineering approach to the design of digital predistortion (DPD) linearizers from several perspectives: i) enhancing the off-line training performance of open-loop DPD, ii) providing robustness and reducing the computational complexity of the parameters identification subsystem and, iii) importing machine learning techniques to favor the automatic tuning of power amplifiers (PAs) and DPD linearizers with several free-parameters to maximize power efficiency while meeting the linearity specifications. One of the essential parts of unmanned aerial vehicles (UAV) is the avionics, being the radio control one of the earliest avionics present in the UAV. Unlike the control signal, for transferring user data (such as images, video, etc.) real-time from the drone to the ground station, large transmission rates are required. The PA is a key element in the transmitter chain to guarantee the data transmission (video, photo, etc.) over a long range from the ground station. The more linear output power, the better the coverage or alternatively, with the same coverage, better SNR allows the use of high-order modulation schemes and thus higher transmission rates are achieved. In the context of UAV wireless communications, the power consumption, size and weight of the payload is of significant importance. Therefore, the PA design has to take into account the compromise among bandwidth, output power, linearity and power efficiency (very critical in battery-supplied devices). The PA can be designed to maximize its power efficiency or its linearity, but not both. Therefore, a way to deal with this inherent trade-off is to design high efficient amplification topologies and let the PA linearizers take care of the linearity requirements. Among the linearizers, DPD linearization is the preferred solution to both academia and industry, for its high flexibility and linearization performance. In order to save as many computational and power resources as possible, the implementation of an open-loop DPD results a very attractive solution for UAV applications. This thesis contributes to the PA linearization, especially on off-line training for open-loop DPD, by presenting two different methods for reducing the design and operating costs of an open-loop DPD, based on the analysis of the DPD function. The first method focuses on the input domain analysis, proposing mesh-selecting (MeS) methods to accurately select the proper samples for a computationally efficient DPD parameter estimation. Focusing in the MeS method with better performance, the memory I-Q MeS method is combined with feature extraction dimensionality reduction technique to allow a computational complexity reduction in the identification subsystem by a factor of 65, in comparison to using the classical QR-LS solver and consecutive samples selection. In addition, the memory I-Q MeS method has been proved to be of crucial interest when training artificial neural networks (ANN) for DPD purposes, by significantly reducing the ANN training time. The second method involves the use of machine learning techniques in the DPD design procedure to enlarge the capacity of the DPD algorithm when considering a high number of free parameters to tune. On the one hand, the adaLIPO global optimization algorithm is used to find the best parameter configuration of a generalized memory polynomial behavioral model for DPD. On the other hand, a methodology to conduct a global optimization search is proposed to find the optimum values of a set of key circuit and system level parameters, that properly combined with DPD linearization and crest factor reduction techniques, can exploit at best dual-input PAs in terms of maximizing power efficiency along wide bandwidths while being compliant with the linearity specifications. The advantages of these proposed techniques have been validated through experimental tests and the obtained results are analyzed and discussed along this thesis.Aquesta tesi doctoral proporciona unes pautes per al disseny de linealitzadors basats en predistorsió digital (DPD) des de diverses perspectives: i) millorar el rendiment del DPD en llaç obert, ii) proporcionar robustesa i reduir la complexitat computacional del subsistema d'identificació de paràmetres i, iii) incorporació de tècniques d'aprenentatge automàtic per afavorir l'auto-ajustament d'amplificadors de potència (PAs) i linealitzadors DPD amb diversos graus de llibertat per poder maximitzar l’eficiència energètica i al mateix temps acomplir amb les especificacions de linealitat. Una de les parts essencials dels vehicles aeris no tripulats (UAV) _es l’aviònica, sent el radiocontrol un dels primers sistemes presents als UAV. Per transferir dades d'usuari (com ara imatges, vídeo, etc.) en temps real des del dron a l’estació terrestre, es requereixen taxes de transmissió grans. El PA _es un element clau de la cadena del transmissor per poder garantir la transmissió de dades a grans distàncies de l’estació terrestre. A major potència de sortida, més cobertura o, alternativament, amb la mateixa cobertura, millor relació senyal-soroll (SNR) la qual cosa permet l’ús d'esquemes de modulació d'ordres superiors i, per tant, aconseguir velocitats de transmissió més altes. En el context de les comunicacions sense fils en UAVs, el consum de potència, la mida i el pes de la càrrega útil són de vital importància. Per tant, el disseny del PA ha de tenir en compte el compromís entre ample de banda, potència de sortida, linealitat i eficiència energètica (molt crític en dispositius alimentats amb bateries). El PA es pot dissenyar per maximitzar la seva eficiència energètica o la seva linealitat, però no totes dues. Per tant, per afrontar aquest compromís s'utilitzen topologies amplificadores d'alta eficiència i es deixa que el linealitzador s'encarregui de garantir els nivells necessaris de linealitat. Entre els linealitzadors, la linealització DPD és la solució preferida tant per al món acadèmic com per a la indústria, per la seva alta flexibilitat i rendiment. Per tal d'estalviar tant recursos computacionals com consum de potència, la implementació d'un DPD en lla_c obert resulta una solució molt atractiva per a les aplicacions UAV. Aquesta tesi contribueix a la linealització del PA, especialment a l'entrenament fora de línia de linealitzadors DPD en llaç obert, presentant dos mètodes diferents per reduir el cost computacional i augmentar la fiabilitat dels DPDs en llaç obert. El primer mètode se centra en l’anàlisi de l’estadística del senyal d'entrada, proposant mètodes de selecció de malla (MeS) per seleccionar les mostres més significatives per a una estimació computacionalment eficient dels paràmetres del DPD. El mètode proposat IQ MeS amb memòria es pot combinar amb tècniques de reducció del model del DPD i d'aquesta manera poder aconseguir una reducció de la complexitat computacional en el subsistema d’identificació per un factor de 65, en comparació amb l’ús de l'algoritme clàssic QR-LS i selecció de mostres d'entrenament consecutives. El segon mètode consisteix en l’ús de tècniques d'aprenentatge automàtic pel disseny del DPD quan es considera un gran nombre de graus de llibertat (paràmetres) per sintonitzar. D'una banda, l'algorisme d’optimització global adaLIPO s'utilitza per trobar la millor configuració de paràmetres d'un model polinomial amb memòria generalitzat per a DPD. D'altra banda, es proposa una estratègia per l’optimització global d'un conjunt de paràmetres clau per al disseny a nivell de circuit i sistema, que combinats amb linealització DPD i les tècniques de reducció del factor de cresta, poden maximitzar l’eficiència de PAs d'entrada dual de gran ample de banda, alhora que compleixen les especificacions de linealitat. Els avantatges d'aquestes tècniques proposades s'han validat mitjançant proves experimentals i els resultats obtinguts s'analitzen i es discuteixen al llarg d'aquesta tesi

Master of Science

thesisAn ever-present challenge at most active mining operations is controlling blastinduced damage beyond design limits. Implementing more effective wall control during blasting activities requires (1) understanding the damage mechanisms involved and (2) reasonably predicting the extent of blast-induced damage. While a common consensus on blast damage mechanisms in rock exists within the scientific community, there is much work to be done in the area of predicting overbreak. A new method was developed for observing near-field fracturing with a borescope. A field test was conducted in which a confined explosive charge was detonated in a body of competent rhyolite rock. Three instrumented monitoring holes filled with quick-setting cement were positioned in close proximity to the blasthole. Vibration transducers were secured downhole and on the surface to measure near-field vibrations. Clear acrylic tubing was positioned downhole and a borescope was lowered through it to view fractures in the grout. Thin, two-conductor, twisted wires were placed downhole and analyzed using a time-domain reflectometer (TDR) to assess rock displacement. Fracturing in the grout was easily observed with the borescope up to 3.78 m (12.4 ft) from the blasthole, with moderate fracturing visible up to 2.10 m (6.9 ft). Measured peak particle velocities (PPV) at these distances were 310 mm/s (12.2 in./s) and 1,490 mm/s (58.5 in./s), respectively, although no fracturing was observed near the depth of the vibration transducers located 3.78 m (12.4 ft) from the blasthole. TDR readings were difficult to interpret but indicated rock displacement in two of the monitoring holes. Three methods were used to predict the radial extent of tensile damage around the blasthole: a modified Holmberg-Persson (HP) model, a shockwave transfer (SWT) model, and a dynamic finite element simulation using ANSYS AutodynTM. The extent of damage predicted by the HP and SWT models is similar to field measurements when using static material properties of the rock, but is underestimated using dynamic material properties. The Autodyn™ model significantly overpredicted the region of damage but realistically simulated the zones of crushing and radial cracking. Calibration of material parameters for the AutodynTM model would be needed to yield more accurate results

A self-adaptive frequency response compensation method for a TIADC system

Time interleaving is one of the most efficient techniques employed in high-speed sampling systems. However, the frequency response mismatch among different channels will create distortion tones that degrade the system performance. In this paper, a selfadaptive frequency response mismatch compensation method is presented, where the design of compensation filter is optimized with a self-adapting strategy. This digital postprocessing technique realizes the compensation of frequency response effectively and also the increase of the digital bandwidth of the acquisition system. MATLAB-based simulation and an actual two-channel acquisition system test verify the effectiveness of the algorithm