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Ali Abedi, Ph.D, Assistant ProfessorMauricio P. da Cunha, Ph.D, Associate Professor

Electrical and Computer Engineering DeptUniversity of Maine, Orono

2007 NASA Fly-by-Wireless Workshop, Grapevine, TX, March 27-28

Hybrid Wireless Communications with Hybrid Wireless Communications with High Reliability and Limited Power High Reliability and Limited Power Constraints in Noisy EnvironmentsConstraints in Noisy Environments

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Problem Visualization

SS

S

S

S

S

Mesh Network:

Noise/InterferenceLimited Spectrum

FusionCenter

Power limitedWireless sensor

Reliable Data ?

VariousSensortypes

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Outline

Reliability Based CommunicationError Correction in Wireless SensorsSensor Capabilities at UMaine Hybrid Architecture

Research TeamCurrent Opportunities

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Outline

Reliability Based Communication

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Reliability Based Communication

Reliable communication is NOT possible w/oError Correction Codes [Shannon, 1948]

Problem: How to Design Codes?– Power efficient (Shannon Limit)– Spectrum efficient (Source Entropy)– Reliable (Achieve Desired BER)

Performance Evaluation of high reliability codes takes a long time

BER: Bit Error Rate

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Likelihood MethodReceived vector

Transmitted BitReliability value

Probability density of LLR Parameter estimation

``A New Method for Performance Evaluation of Bit Decoding Algorithms Using Statistics of the Log Likelihood Ratio,'' 4th International Symposium on Turbo-codes, April 2006, Munich, Germany

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Turbo Principle

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Accuracy AnalysisVariance and sample reduction gain

Gain=43 @ BER=10-6

Probability (∆Pe < ε )– 106 samples

• proposed method=0.97• MC method=0.95

– 104 samples• proposed method=0.93• MC method=0.33

MC: Monte-Carlo Simulation is used to generate enough samples and count number of errors.

SampleReduction

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Summary of Contributions

Analytical performance evaluation:– Accurate (compared to bounds)

– Fast– Low cost

Enabling technology– Code optimization (min BER)

– Power minimizationNear theoretical limit operation

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Outline

Reliability Based CommunicationError Correction in Wireless Sensors

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Wireless Standards

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Implementation

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Proposed Approach

3.5 dB gain

1000 timesMore reliable

Invited paper: ``A Simple Error Correction Scheme for Performance Improvement of IEEE 802.15.4,''IEEE International Conference on Wireless Networks, June 2007, Las Vegas, NV

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Outline

Reliability Based CommunicationError Correction in Wireless SensorsSensor Capabilities at UMaine

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Sensor Capabilities at UMaineLASST/UMaine: Laboratory for Surface Science

and TechnologyR&D Areas of Expertise– Physical, Chemical and Biological Sensors– High Temperature Materials– Micro/Nano Systems and Devices

Interdisciplinary Research Center – Faculty, students, staff, and industrial collaborators– Physics, Chemistry, Microbiology, Electrical Eng., Chemical

Eng., Bio Eng, Food Science, Computer Science– Collaborative high-tech projects with industries and national

partners & business incubator – Clean room, state-of-the-art microlithography, micro and nano

fab., thin film synthesis and characterization, sensor testing and evaluation, wireless syst. and dev.

– Strong commitment to education NSF IGERT, GK-12, RET, REU

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Materials/Thin Film Preparation & CharacterizationMaterials/Thin Film Preparation & Characterization

Sensor Fab: metallization, photolithography, micromachining, patterning/etching, dicing/bonding/packaging Sensor Testing: gas chromatograph/

mass spec, microwave test facilities/equipHall effect, impedance spectrosc., gas delivery

Crystals aligning, X-Ray anal, auger, XPSCutting, polishing, n& dev. fabr. & test New Crystals

Cutting, grinding and polishingX-Ray & Crystal Analysis Device design, fabrication, and Test

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Types of Sensor

0 50 100 150 200 250 300 350 400 450 500

-15

-10

-5

0

5

10

Time [min]

∠S

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• Biosensors (& micro fluidics)Gas SensorsHarsh Environment (↑ 1000 °C)Physical Sensors (acceleration, stress, strain, vibr., pressure, temp.)Protective film layers for harsh environmentPackaging

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Wireless Passive Acoustic Wave Physical / Gas Sensors

Work beyond device →reliable communication →code identification, test & selection MultipathDevice design and optimizationHarsh environment packaging

SAW Passive Sensor

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Device Device fabfab. at UMaine for MSGC/NASA. at UMaine for MSGC/NASA

Safety: Fuel leak detection, Fire detection, Hostile Environment DetectionEnvironment: fuel efficiency in rocket propulsion & jet engines (NASA & commercial aviation)Detection of H2 and CxHY, NOx gases from temperatures ranging from 250 to 550 °C

162 164 166 168 170 172 174-55

-50

-45

-40

-35

-30

-25

-20

Freq [MHz]

S21

Res

pons

e (d

B)

750 °C 25 °C500 °C

0 50 100 150 200 250 300 350 400-5

-4

-3

-2

-1

0

1

2

3

4

Time [min]

FRE

QU

EN

CY

VA

RIA

TIO

N [

Δ K

Hz]

1 2 3 4

5 6

7 8

H2 off / N2 on

N2 off / H2 on

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Outline

Reliability Based CommunicationError Correction in Wireless SensorsSensor Capabilities at UMaineHybrid Architecture

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Tails are important

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Integrated Design

Sensor Channel

Sensor ChannelChannel Encoder

Conventional design

Integrated design

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Lower tier

Upper tier

nodes

Super nodes

sources

NS )ˆ( NSg)ˆ( NSf

NS1S

Gateway

Wireless/Optical

Wireless

Microwave

Hybrid Architecture

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Turbo Principle

RecursiveConvolutional

Encoder

RecursiveConvolutional

Encoder

π

NS

)ˆ( NSg

)ˆ( NSf

NS

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Outline

Research TeamCurrent Opportunities

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Research Team

University of Maine, Orono, ME– PI: Prof. Ali Abedi

Director, WiSe-Net Lab– Co-PI: Prof. Mauricio P. da Cunha

Director, Microwave Lab

NASA Johnson Space Center– Dr. Patrick Fink

Deputy Chief, Electromagnetic Systems Branch

MainelyWired, Swanville, ME– Tristan Petersen, Chief Engineer

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Future opportunities

Collaboration– Mechanical/Civil Engineers at UMaine– NASA centers– Industrial partners

abedi@ieee.orgmdacunha@eece.maine.edu