Graduate Thesis Or Dissertation
 

Limitations and optimization of a blind calibration algorithm for nonlinearity in analog to digital converters

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https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/9c67wr159

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  • Analog to digital converters (ADCs) are a critical part of communication between the physical world and the increasingly digital systems humans use every day. ADCs have inherent non-idealities that degrade performance. Nonlinearity is one of the most prevalent non-idealities that designers face. While calibration methods for nonlinearity exist in the analog domain, digital calibration is preferred since it typically takes less resources (chip area, power consumption) and can be implemented off chip if need be. A blind digital calibration algorithm for nonlinearity correction in ADCs was developed at Oregon State University that continuously corrects harmonic distortion using the concepts of downsampling and orthogonality of sinusoidal signals. It can calibrate for multiple harmonics simultaneously with no need for an external test signal. This work explores the blind calibration algorithm in order to determine some of the limitations inherent to both the theoretical design and with respect to a practical implementation in hardware. Based upon these limitations, various methods of algorithm optimization were characterized through discussion of design trade-offs and ways to improve performance.
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