Integrated Circuits and Systems for Sparse Signal Acquisition based on Asynchronous Sampling and Compressed Sensing.
Trakimas, Michael.
2011
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Abstract: This
dissertation builds on the recent theoretical and experimental work on asynchronous
sampling and compressed sensing. Our goal is to exploit the advances in the theory to
design practical data acquisition systems capable of directly acquiring sparse signals
at sub-Nyquist rates. We focus specifically on increasing the power efficiency and
decreasing the complexity of the signal ... read moreacquisition process compared to existing
conventional Nyquist rate solutions for biomedical sensor and wideband spectrum sensing
applications. The first half of the dissertation presents the design and implementation
of an adaptive resolution asynchronous ADC which achieves data compression for sparse
and burst like signals by the inherent signal dependent sampling rate of the
asynchronous architecture. The main contribution of this work is the implementation of
an adaptive resolution (AR) algorithm which varies the quantizer resolution of the ADC
with the slope of the input signal, in order to overcome the tradeoff between dynamic
range and input bandwidth typically seen in asynchronous ADCs. This allows the maximum
possible input bandwidth to be achieved regardless of the dynamic range requirement. By
reducing the quantizer resolution during periods of high input slope, further data
compression is also achieved. A prototype ADC was fabricated in a 0.18µm CMOS
technology and optimized for subthreshold operation in order to increase the power
efficiency for low-frequency biomedical sensor applications. The prototype ADC achieves
an equivalent maximum sampling rate of 50kS/s, an SNDR of 43.2dB, and consumes 25µW
from a 0.7V supply. The ADC is also shown to provide data compression for accelerometer
and ECG applications as a proof of concept demonstration. The second half of this
dissertation presents the design and implementation of a compressed sensing based
analog-to-information converter (AIC) for wideband spectrum sensing applications. The
core of the design is an ultra low power moderate rate ADC that randomly samples the
received signal at sub-Nyquist rates. In order to ensure proper functionality with the
random clock signal and to maximize power efficiency, a prototype edge-triggered
charge-sharing SAR ADC core was implemented in 90nm CMOS technology. The prototype SAR
ADC core achieves a maximum sample rate of 9.5MS/s, an ENOB of 9.3 bits, and consumes
550µW from a 1.2V supply. Measurement results of the compressed sensing AIC
demonstrate effective sub-Nyquist random sampling and reconstruction of signals with
sparse frequency support suitable for wideband spectrum sensing applications. When
accounting for the increased input bandwidth compared to Nyquist, the AIC achieves an
effective figure of merit (FOM) of
10.2fJ/conversion-step.
Thesis (Ph.D.)--Tufts University, 2011.
Submitted to the Dept. of Electrical Engineering.
Advisor: Sameer Sonkusale.
Committee: Timothy Hancock, Hwa Chang, and Valencia Joyner.
Keyword: Electrical Engineering.read less - ID:
- 9z903b186
- Component ID:
- tufts:21029
- To Cite:
- TARC Citation Guide EndNote
