Seminar: ECE Faculty Candidate
Friday
March 3rd
11:00 - 11:50am
KEC 1005
Sebastian Hoyos
Postdoctoral Researcher
Berkeley Wireless Research Center
University of California, Berkeley
Transparent Electronics: Thin-Film Transistors and Integrated Circuits
The traditional approach to improve the performance of critical building
blocks has been the fine tuning of conventional architectures together
with the advantages provided by technology scaling. However, fundamental
limitations have arisen due to the technology scaling which require
innovative system level techniques instead of the traditional tweaking
of analog circuits. Moreover, all digital architectures do not provide a
solution to these limitations either since analog to digital and digital
to analog interfaces are unavoidable building blocks. This presentation
shows that the strategic coupling between analog and digital systems
combined with powerful signal processing tools is the most solid and
open-minded approach for pushing the performance envelop of critical
systems. In particular, the following two new analog to digital
converters schemes will be presented:
Analog to Digital Conversion via Signal Expansion: Analog to digital
conversion is one of the key elements that has enabled the development
and implementation of digital signal processing systems. However, the
progress in the development of ADCs with higher speeds and resolutions
is facing serious technological barriers. I believe that the further
development of ADCs need advance signal processing techniques that
couple analog and digital parts in an optimal fashion. At this end, I
have proposed during my Ph.D. dissertation an ADC approach based on the
quantization of coefficients obtained via the projection of a
continuous-time signal over a set of basis functions. This ADC framework
is motivated by the sampling of an input signal in domains which may
lead to significantly less demanding A/D conversion characteristics;
lower sampling rates and lower bit resolution requirements, which in
principle can lead to lower power consumption. The proposed system
efficiently parallelizes the ADC, which lowers the sampling rate
requirements by increasing the number of basis functions on which the
continuous time signal is projected, leading to a trade-off between
sampling rate reduction and system complexity This research takes into
consideration critical implementation issues in A/D converters providing
the possibility of circuit level implementation of the proposed
technique. A multicarrier receiver that couples the digital baseband
with the signal expansion ADC front-end will be explained in detail.
Digital Background Calibration Techniques of ADCs: Digital calibration
techniques arise as a potential solution to the multiple impairments of
analog circuits. These digital techniques are supported by their
inherent robustness and flexibility. Additionally, the very large
integration of digital circuits allows the implementation of complex
adaptive calibration techniques whose foundations have been solidified
by decades of research in signal processing. As an example of this,
during my postdoctoral research project, I worked on the implementation
of the Least-Mean-Square (LMS) algorithm for the calibration of a
pipeline ADC. The pipelined ADC when is clocked at high speeds degrades
its performance due mainly to device mismatches. It can be shown that
these impairments can be overcome by passing the corrupted digital data
through a linear filter. The optimum weights are found adaptively using
the LMS algorithm. The training data used in the adaptation process is
provided by a high resolution sigma-delta converter running at a
fraction of the Nyquist sampling rate. A chip on 0.13 um technology has
been taped-out to prove these ideas and although the silicon is not back
yet for testing, simulations and circuit details will be discussed.
Biography
Sebastian Hoyos received the B.S. degree from the Pontificia Universidad
Javeriana (PUJ), Bogota, Colombia in 2000, and the M.S. (2002) and Ph.D.
(2004) degrees from the University of Delaware, Newark DE, all in
electrical engineering. In the Fall of 2004, he enrolled in the
Department of Electrical Engineering and Computer Sciences at the
University of California, Berkeley, where he is a postdoctoral
researcher at the Berkeley Wireless Research Center. He has carried out
industrial consulting with Conexant Systems Inc., Red Bank, NJ. His
research interests include communication systems, wireless
communications, sensor network processing, robust signal processing, and
mixed-signal high-speed processing and circuit design.
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