<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-09-19T14:25:54Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/68437" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/68437</identifier><datestamp>2022-01-13T07:54:29Z</datestamp><setSpec>com_1721.1_7582</setSpec><setSpec>com_1721.1_7581</setSpec><setSpec>col_1721.1_131022</setSpec></header><metadata><dim:dim xmlns:dim="http://www.dspace.org/xmlns/dspace/dim" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.dspace.org/xmlns/dspace/dim http://www.dspace.org/schema/dim.xsd">
   <dim:field mdschema="dc" element="contributor" qualifier="advisor" lang="en_US">Vladimir M. Stojanović and Anantha P. Chandrakasan.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Chen, Fred (Fred Fu-Chin)</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2012-01-12T19:27:36Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2012-01-12T19:27:36Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2011</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2011</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">http://hdl.handle.net/1721.1/68437</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">768861095</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Cataloged from PDF version of thesis. Page 184 blank.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (p. 171-183).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">Adoption of wireless sensor network (WSN) technology could enable improved efficiency across a variety of industries that include building management, agriculture, transportation, and health care. Most of the technical challenges of WSNs can be linked to the stringent energy constraints of each sensor node, where wireless communication and leakage energy are the doninant components of active and idle energy costs. To address these two limitations, this thesis adopts compressed sensing (CS) theory as a generic source coding framework to minimize the transmitted data and proposes the use of micro-electro-mechanical (MEM) relay technology to eliminate the idle leakage. To assess the practicality of adopting CS as a source coding framework we examine the inpact of finite resources, input noise, and wireless channel impairments on the compression and reconstruction performance of CS. We show that CS, despite being a lossy compression algorithm, can realize compression factors greater than loX with no loss in fidelity for sparse signals quantized to medium resolutions. We also model the hardware costs for implementing the CS encoder and results from a test chip designed in a 90 nm CMOS process that consumes only 1.9 [mu]W for operating frequencies below 20 kHz, verifies the models. The encoder is desioned to enable continuous, on-the-fly compression that is demonstrated on electroencephalography (EEG) and electrocardiogram (EKG) signals to show the applicability of CS. To address sub-threshold leakage, which limits the energy performance in CMOS-based sensor nodes, we develop design methodologies towards leveraging the zero leakage characteristics of MEM relays while overcoming their slower switching speeds. Projections on scaled relay circuits show the potential for greater than loX improvements in energy efficieicy over CMOS at up to 10-100 Mops for a variety of circuit sub-systems. Experimental results demonstrating functionality for several circuit building blocks validate the viability of the technology, while feedback from these results is used to refine the device design. Incorporating all of the design elements, w present simnulation results for our most recent test chip design which implements relay-based versions of the CS encoder circuits in a 0.25 jim lithographic process showing 5X improvement over our 90 nm CMOS design.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Fred Chen.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">Ph.D.</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">184 p.</dim:field>
   <dim:field mdschema="dc" element="language" qualifier="iso" lang="en_US">eng</dim:field>
   <dim:field mdschema="dc" element="publisher" lang="en_US">Massachusetts Institute of Technology</dim:field>
   <dim:field mdschema="dc" element="rights" lang="en_US">M.I.T. theses are protected by 
copyright. They may be viewed from this source for any purpose, but 
reproduction or distribution in any format is prohibited without written 
permission. See provided URL for inquiries about permission.</dim:field>
   <dim:field mdschema="dc" element="rights" qualifier="uri" lang="en_US">http://dspace.mit.edu/handle/1721.1/7582</dim:field>
   <dim:field mdschema="dc" element="subject" lang="en_US">Electrical Engineering and Computer Science.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">Energy-efficient wireless sensors : fewer bits, Moore MEMS</dim:field>
   <dim:field mdschema="dc" element="type" lang="en_US">Thesis</dim:field>
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   	&lt;Title>Energy-efficient wireless sensors : fewer bits, Moore MEMS&lt;/Title>
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   	&lt;PublicationDate>2011&lt;/PublicationDate>
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        	&lt;DisplayName>Chen, Fred (Fred Fu-Chin)&lt;/DisplayName>
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            &lt;DisplayName>Massachusetts Institute of Technology&lt;/DisplayName>
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    &lt;License>http://dspace.mit.edu/handle/1721.1/7582&lt;/License>
    &lt;Keyword>Electrical Engineering and Computer Science.&lt;/Keyword>
   	&lt;Abstract>Adoption of wireless sensor network (WSN) technology could enable improved efficiency across a variety of industries that include building management, agriculture, transportation, and health care. Most of the technical challenges of WSNs can be linked to the stringent energy constraints of each sensor node, where wireless communication and leakage energy are the doninant components of active and idle energy costs. To address these two limitations, this thesis adopts compressed sensing (CS) theory as a generic source coding framework to minimize the transmitted data and proposes the use of micro-electro-mechanical (MEM) relay technology to eliminate the idle leakage. To assess the practicality of adopting CS as a source coding framework we examine the inpact of finite resources, input noise, and wireless channel impairments on the compression and reconstruction performance of CS. We show that CS, despite being a lossy compression algorithm, can realize compression factors greater than loX with no loss in fidelity for sparse signals quantized to medium resolutions. We also model the hardware costs for implementing the CS encoder and results from a test chip designed in a 90 nm CMOS process that consumes only 1.9 [mu]W for operating frequencies below 20 kHz, verifies the models. The encoder is desioned to enable continuous, on-the-fly compression that is demonstrated on electroencephalography (EEG) and electrocardiogram (EKG) signals to show the applicability of CS. To address sub-threshold leakage, which limits the energy performance in CMOS-based sensor nodes, we develop design methodologies towards leveraging the zero leakage characteristics of MEM relays while overcoming their slower switching speeds. Projections on scaled relay circuits show the potential for greater than loX improvements in energy efficieicy over CMOS at up to 10-100 Mops for a variety of circuit sub-systems. Experimental results demonstrating functionality for several circuit building blocks validate the viability of the technology, while feedback from these results is used to refine the device design. Incorporating all of the design elements, w present simnulation results for our most recent test chip design which implements relay-based versions of the CS encoder circuits in a 0.25 jim lithographic process showing 5X improvement over our 90 nm CMOS design.&lt;/Abstract>
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