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Please use this identifier to cite or link to this item: http://hdl.handle.net/1853/4773

Title: Design of Robust and Flexible On-chip Analog-to-Digital Conversion Architecture
Authors: Kim, Daeik D.
Electrical and Computer Engineering
Advisor: Committee Chair: Brooke, Martin; Committee Member: Cressler, John; Committee Member: Hasler, Paul; Committee Member: Kohl, Paul; Committee Member: Schimmel, David
Subjects : Front-end
Delta-sigma converter
Delta-sigma decoder
Sensors
System-on-a-chip
Analog-to-digital converters
Issue Date: 17-Aug-2004
Publisher: Georgia Institute of Technology
Abstract: This dissertation presents a comprehensive design and analysis framework for system-on-a-chip analog-to-digital conversion design. The design encompasses a broad class of systems, which take advantage of system-on-a-chip complexity. This class is exemplified by an interferometric photodetector array based bio-optoelectronic sensor that is built and tested as part of the reported work. While there have been many discussions of the technical details of individual analog-to-digital converter (ADC) schemes in the literature, the importance of the analog front-end as a pre-processor for a data converter and the generalized analysis including converter encoding and decoding functions have not previously been investigated thoroughly, and these are key elements in the choice of converter designs for low-noise systems such as bio-optoelectronic sensors. Frequency domain analog front-end models of ADCs are developed to enable the architectural modeling of ADCs. The proposed models can be used for ADC statistically worst-case performance estimation, with stationary random process assumptions on input signals. These models prove able to reveal the architectural advantages of a specific analog-to-digital converter schemes quantitatively, allowing meaningful comparisons between converter designs. The modeling of analog-to-digital converters as communication channels and the ADC functional analysis as encoders and decoders are developed. This work shows that analog-to-digital converters can be categorized as either a decoder-centered design or an encoder-centered design. This perspective helps to show the advantages of nonlinear decoding schemes for oversampling noise-shaping data converters, and a new nonlinear decoding algorithm is suggested to explore the optimum solution of the decoding problem. A case study of decoder-centered and encoder-centered data converter designs is presented by applying the proposed theoretical framework. The robustness and flexibility of the resulting analog-to-digital converters are demonstrated and compared. The electrical and optical sensitivity measurements of a fabricated oversampling noise shaping analog-to-digital converter circuit are provided, and a sensor system-on-a-chip using these ADCs with integrated interferometric waveguides for bio-optoelectronic sensing is demonstrated.
Type: Dissertation
URI: http://hdl.handle.net/1853/4773
Appears in Collections:Georgia Tech Theses and Dissertations
School of Electrical and Computer Engineering Theses and Dissertations

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