Building compressed sensing systems : sensors and analog-to-information converters
Name
834092434-MIT.pdf
Description
Full printable version
Size
12.42 MB
Format
Adobe PDF
Checksum (MD5)
e718a35203a30b57e02e30ab6995938f
Author(s)
Salehi-Abari, Omid
Advisor(s)
Vladimir Stojanović.
Alternative Title
Sensors and analog-to-information converters
Date Issued
2012
Publisher
Massachusetts Institute of Technology
Abstract
Compressed sensing (CS) is a promising method for recovering sparse signals from fewer measurements than ordinarily used in the Shannon's sampling theorem [14]. Introducing the CS theory has sparked interest in designing new hardware architectures which can be potential substitutions for traditional architectures in communication systems. CS-based wireless sensors and analog-to-information converters (AIC) are two examples of CS-based systems. It has been claimed that such systems can potentially provide higher performance and lower power consumption compared to traditional systems. However, since there is no end-to-end hardware implementation of these systems, it is difficult to make a fair hardware-to-hardware comparison with other implemented systems. This project aims to fill this gap by examining the energy-performance design space for CS in the context of both practical wireless sensors and AICs. One of the limitations of CS-based systems is that they employ iterative algorithms to recover the signal. Since these algorithms are slow, the hardware solution has become crucial for higher performance and speed. In this work, we also implement a suitable CS reconstruction algorithm in hardware.
Description
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 93-96).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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