positioning in ad-hoc networks a channel model for low power … · 2015. 5. 18. · and shad...

Positioning in Ad-Hoc Networks-

A Channel Model for Low Power Data Transmission

Jan BeutelComputer Engineering and Networks Lab

Swiss Federal Institute of Technology (ETH) Zurich

June 15, 2001

Computer EngineeringComputer Engineeringand Networks Laboratoryand Networks Laboratory

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Jan Beutel, June 15, 2001Jan Beutel, June 15, 2001

Outline

• Sensor Networks

• Radio Channel• Propagation Channel

• Simulation using ETH Raytracing Tool

• Some RSSI Sample Data• First Positioning Results

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Sensor Networks

• Ad-Hoc network of many sensors, monitors and actuators (>100 total)

• Vision of system on a chip• No infrastructure• Deployable in different

environments• Limited radio range• Node clusters and depletion

Goal: Ultra Low Power

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Radio Ranging Methods

TOA – time of arrival

Carrier phase

AOA – angle of arrival

Signal strength

TDOA – time distance of arrival

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Radio Frontend Requirements

• Simple direct down-conversion frontend

• Emphasis on digital processing (µJ vs. pJ per Bit)

• Mostly sleepy radio (receiver)• Tx power scalable (Wolisz et. al.)

• CMOS SOC’s -> 2.4 GHz / 5 GHz• PTx < 0 dBm

ReconfigurableDataPath

ReconfigurableState Machines Embedded uP

FPGA

DedicatedDSP

• RSSI used in transceivers for carrier sensing -> available at no cost

• Possibly separation of multi-path and multi-access through advanced baseband processing (RAKE)

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Propagation Channel in Mixed Environments

• Mechanism: Reflection, Diffraction, Scattering

• Transmission through a wall:– up to 6-10 dB at 2.5 GHz -> walls are not transparent

• Received signal strength for low power at 1/r3 to 1/r4. In commercial space, e.g., supermarkets, Lucent measured 1/r3.8 at 2.5 GHz. (Source G. Wright, Lucent)

• High impact of geometry on overall picture• Local impact of material fluctuates statistically

• Models are highly specific or give average overview

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Received Signal Strenght

• Multi-path vs. LOS components• Delay and AOA reflect geometry (large scale)• Fading• Amplitude influenced by dielectrics, angle of

incidence and polarization

• Multiple access interference, depending on CD/TDMA scheme

• Around λ/2 spacing, signal strength variation may be as high as 30-40 dB (small scale fading)

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Tools for Simulation: Raytracing

• Exact modeling of LOS path and reflections• Differentiating

– Order of reflections– Geometry– Material– Polarization– Delay and AOA– Amplitudes– Power Spectrum Densities

• Raytracing tool developed by J. Hansen

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Power Density: Polarization

• Transmitter located at ceiling• Arbitrary location receiver

Distance

Elevation

Distance

Elevation

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Power Density: Windows

• Small window (0.7 x 0.8) in wall• Windows behave like walls

Distance

Elevation

Distance

Elevation

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Power Density: Room Size and Layout

• Transmitter fixed in middle of Z axis• Guidance effect of very long room

Distance

Elevation

Distance

Elevation

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Bluetooth RSSI Samples Free Space

-25

-20

-15

-10

-5

0

5

10

15

201 30 59 88 117

146

175

204

233

262

291

320

349

378

407

436

465

494

523

552

581

610

639

668

697

726

755

784

813

842

871

900

929

958

987

1016

1045

Samples/Distance

RSS

I

Series1Series2

S

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Bluetooth RSSI Samples Office Space

-25

-20

-15

-10

-5

0

5

10

15

201 7 13 19 25 31 37 43 49 55 61 67 73 79 85 91 97 103

109

115

121

127

133

139

145

151

157

163

169

175

181

187

193

199

Samples/Distance

RSS

I

Series1Series2Series3

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Wavelan 802.11b RSSI Samples

-120

-100

-80

-60

-40

-20

0

20

40

60

80

-3 -2 -1 0 0 1 2 3 4 5 6 6 7 8 9 10 11 12 12 13 14 15 16 17 18 18 19 20 21 22

Distance [m]

Sign

al a

nd N

oise

Lev

el [d

Bm

]

LSNR Avg LSL Avg LNL Avg RSNR Avg RSL Avg RNL Avg Path Loss 1/r 2̂Path Loss 1/r 4̂

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Wavelan 802.11b Indoor Environment

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Redundant Triangulation

Iteration on 25 individual ranges with 50% each

0 0.5 10

0.2

0.4

0.6

0.8

1Delaunay Mesh of 25 Networked Nodes

x0 0.5 1

0

0.2

0.4

0.6

0.8

1Solution on 25 Ranges and 50% Error

x

0 0.5 10

0.2

0.4

0.6

0.8

150 Solutions and Mean

x0.4 0.45 0.5 0.55 0.6

0.4

0.45

0.5

0.55

0.6Zoom on Error

x

dx 0.0054dy 0.0058

1% error

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Triangulation on Real Data

• Application to Wavelan RSSI data shows good average

Solution• Iterative triangulation• Overload systems• Influence of

geometric DOP• Include environmental

information

Yielding sub meter DOP

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Literature• Jan Hansen. A novel stochastic millimeter wave indoor radio

channel model. Journal on Selected Areas in Communication, 2001.• Chris Savarese, Jan Beutel, and Rabaey Jan M. Locationing in

distributed ad-hoc sensor networks. In Proceedings of ICASSP, 2001.

• Jan M. Rabaey, Josie Ammer, Julio L. da Silva Jr., Danny Patel, and Shad Roundy. PicoRadio Supports Ad Hoc Ultra-Low Power Wireless Networking. IEEE Computer, 33(7):42-48, July 2000.

• Theodore S. Rappaport. Wireless Communications. Prentice Hall, 1996.

• Danny Patel. Energy in Ad-Hoc Networking for the PicoRadio. Master's thesis, University of California at Berkeley, 2000.

• Jean Pierre Ebert and Adam Wolisz. Combined tuning of rf power and medium access control for wlans. In Proceedings of 1999 IEEE International Workshop on Mobile Multimedia Communications, pages 47-82, November 1999.

• Kamilo Feher. Wireless Digital Communications: Modulation and Spread Spectrum Applications. Prentice Hall, 1995.

positioning in ad-hoc networks a channel model for low power … · 2015. 5. 18. · and shad...

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