Developing Model-Based Design Evaluation for Pipelined A/D Converters

This paper deals with a prospective approach of modeling, design evaluation and error determination applied to pipelined A/D converter architecture. In contrast with conventional ADC modeling algorithms targeted to extract the maximum ADC non-linearity error, the innovative approach presented allows to decompose magnitudes of individual error sources from a measured or simulated response of an ADC device. Design Evaluation methodology was successfully applied to Nyquist rate cyclic converters in our works [13]. Now, we extend its principles to pipelined architecture. This qualitative decomposition can significantly contribute to the ADC calibration procedure performed on the production line in term of integral and differential nonlinearity. This is backgrounded by the fact that the knowledge of ADC performance contributors provided by the proposed method helps to adjust the values of on-chip converter components so as to equalize (and possibly minimize) the total non-linearity error. In this paper, the design evaluation procedure is demonstrated on a system design example of pipelined A/D converter. Significant simulation results of each stage of the design evaluation process are given, starting from the INL performance extraction proceeded in a powerful Virtual Testing Environment implemented in Maple™ software and finishing by an error source simulation, modeling of pipelined ADC structure and determination of error source contribution, suitable for a generic process flow

Energy Efficient Pipeline ADCs Using Ring Amplifiers

Pipeline ADCs require accurate amplification. Traditionally, an operational transconductance amplifier (OTA) configured as a switched-capacitor (SC) amplifier performs such amplification. However, traditional OTAs limit the power efficiency of ADCs since they require high quiescent current for slewing and bandwidth. In addition, it is difficult to design low-voltage OTAs in modern, scaled CMOS. The ring amplifier is an energy efficient and high output swing alternative to an OTA for SC circuits which is basically a three-stage inverter amplifier stabilized in a feedback configuration. However, the conventional ring amplifier requires external biases, which makes the ring amplifier less practical when we consider process, supply voltage, and temperature (PVT) variation. In this dissertation, three types of innovative ring amplifiers are presented and verified with state-of-the-art energy efficient pipeline ADCs. These new ring amplifiers overcome the limitations of the conventional ring amplifier and further improve energy efficiency. The first topic of this dissertation is a self-biased ring amplifier that makes the ring amplifier more practical and power efficient, while maintaining the benefits of efficient slew-based charging and an almost rail-to-rail output swing. In addition, the ring amplifiers are also used as comparators in the 1.5b sub-ADCs by utilizing the unique characteristics of the ring amplifier. This removes the need for dedicated comparators in sub-ADCs, thus further reducing the power consumption of the ADC. The prototype 10.5b 100 MS/s comparator-less pipeline ADC with the self-biased ring amplifiers has measured SNDR, SNR and SFDR of 56.6 dB (9.11b), 57.5 dB and 64.7 dB, respectively, and consumes 2.46 mW, which results in Walden Figure-of-Merit (FoM) of 46.1 fJ/ conversion∙step. The second topic is a fully-differential ring amplifier, which solves the problems of single-ended ring amplifiers while maintaining the benefits of the single-ended ring amplifiers. This differential ring-amplifier is applied in a 13b 50 MS/s SAR-assisted pipeline ADC. Furthermore, an improved capacitive DAC switching method for the first stage SAR reduces the DAC linearity errors and switching energy. The prototype ADC achieves measured SNDR, SNR and SFDR of 70.9 dB (11.5b), 71.3 dB and 84.6 dB, respectively, and consumes 1 mW. This measured performance is equivalent to Walden and Schreier FoMs of 6.9 fJ/conversion∙step and 174.9 dB, respectively. Finally, a four-stage fully-differential ring amplifier improves the small-signal gain to over 90 dB without compromising speed. In addition, a new auto-zero noise filtering method reduces noise without consuming additional power. This is more area efficient than the conventional auto-zero noise folding reduction technique. A systematic mismatch free SAR CDAC layout method is also presented. The prototype 15b 100 MS/s calibration-free SAR-assisted pipeline ADC using the four-stage ring amplifier achieves 73.2 dB SNDR (11.9b) and 90.4 dB SFDR with a 1.1 V supply. It consumes 2.3 mW resulting in Schreier FoM of 176.6 dB.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/138759/1/yonglim_1.pd

Carbon footprint of 3D-printed bone tissue engineering scaffolds: an life cycle assessment study

The bone tissue engineering scaffolds is one of the methods for repairing bone defects caused by various factors. According to modern tissue engineering technology, three-dimensional (3D) printing technology for bone tissue engineering provides a temporary basis for the creation of biological replacements. Through the generated 3D bone tissue engineering scaffolds from previous studies, the assessment to evaluate the environmental impact has shown less attention in research. Therefore, this paper is aimed to propose the Model of life cycle assessment (LCA) for 3D bone tissue engineering scaffolds of 3D gel-printing technology and presented the analysis technique of LCA from cradle-to-gate for assessing the environmental impacts of carbon footprint. Acrylamide (C3H5NO), citric acid (C6H8O7), N,N-Dimethylaminopropyl acrylamide (C8H16N2O), deionized water (H2O), and 2-Hydroxyethyl acrylate (C5H8O3) was selected as the material resources. Meanwhile, the 3D gel-printing technology was used as the manufacturing processes in the system boundary. The analysis is based on the LCA Model through the application of GaBi software. The environmental impact was assessed in the 3D gel-printing technology and it was obtained that the system shows the environmental impact of global warming potential (GWP). All of the emissions contributed to GWP have been identified such as emissions to air, freshwater, seawater, and industrial soil. The aggregation of GWP result in the stage of manufacturing process for input and output data contributed 47.6% and 32.5% respectively. Hence, the data analysis of the results is expected to use for improving the performance at the material and manufacturing process of the product life cycle

A 12b 100MSps Split Pipeline ADC with Open-Loop Residue Amplification

The design of a low-power 12-bit 100MSps pipeline analog-to-digital converter (ADC) with open-loop residue amplification using the novel Split-ADC architecture is described. The choice of a 12b 100MSps specification targets medical applications such as portable ultrasound. For a representative ADC such as the ADS5270, the figure of merit (FOM) is approximately 1pJ/step and the power dissipation is 113mW. The use of an open-loop residue amplifier resulted in a FOM of 0.571pJ/step and a power dissipation of 11.2mW

Turbo Bayesian Compressed Sensing

Compressed sensing (CS) theory specifies a new signal acquisition approach, potentially allowing the acquisition of signals at a much lower data rate than the Nyquist sampling rate. In CS, the signal is not directly acquired but reconstructed from a few measurements. One of the key problems in CS is how to recover the original signal from measurements in the presence of noise. This dissertation addresses signal reconstruction problems in CS. First, a feedback structure and signal recovery algorithm, orthogonal pruning pursuit (OPP), is proposed to exploit the prior knowledge to reconstruct the signal in the noise-free situation. To handle the noise, a noise-aware signal reconstruction algorithm based on Bayesian Compressed Sensing (BCS) is developed. Moreover, a novel Turbo Bayesian Compressed Sensing (TBCS) algorithm is developed for joint signal reconstruction by exploiting both spatial and temporal redundancy. Then, the TBCS algorithm is applied to a UWB positioning system for achieving mm-accuracy with low sampling rate ADCs. Finally, hardware implementation of BCS signal reconstruction on FPGAs and GPUs is investigated. Implementation on GPUs and FPGAs of parallel Cholesky decomposition, which is a key component of BCS, is explored. Simulation results on software and hardware have demonstrated that OPP and TBCS outperform previous approaches, with UWB positioning accuracy improved by 12.8x. The accelerated computation helps enable real-time application of this work