validation of radio channel models using an anechoic chamber

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Validation of Radio Channel Models using an Anechoic Chamber Yuhao Zheng, David M. Nicol University of Illinois at Urbana-Champaign 1

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Validation of Radio Channel Models using an Anechoic Chamber . Yuhao Zheng , David M. Nicol University of Illinois at Urbana-Champaign. Outline. Introduction & anechoic chamber Experimental framework Radio channel models Experiment results Conclusions & future works. Introduction. - PowerPoint PPT Presentation

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Page 1: Validation  of Radio Channel Models using an Anechoic Chamber

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Validation of Radio Channel Models using an Anechoic Chamber

Yuhao Zheng, David M. NicolUniversity of Illinois at Urbana-Champaign

Page 2: Validation  of Radio Channel Models using an Anechoic Chamber

Outline

• Introduction & anechoic chamber• Experimental framework• Radio channel models• Experiment results• Conclusions & future works

2

Page 3: Validation  of Radio Channel Models using an Anechoic Chamber

Introduction

• Wireless network simulation is popular• Fidelity is a problem– Especially for radio channel model– Higher layers depend on physical layer

• Tradeoff: accuracy ↔ computational cost– Simple models: free space, two ray– Complex models: raytracing, Transmission Line

Matrix (TLM)

3

Page 4: Validation  of Radio Channel Models using an Anechoic Chamber

Our Focus

• Complex models: Raytracing, TLM– Received signal strength

• Sensitivity experiments– Small changes in environment– How does a model reflect this?

• Problems– Need accurate measured value for validation– Anechoic chamber

4

Tx

Rx

Page 5: Validation  of Radio Channel Models using an Anechoic Chamber

Anechoic Chamber

• Illinois Wireless Wind Tunnel (iWWT)

• Characteristics– No outside interferences– No inside reflections

• Ideal wireless testbed– “Free space” inside

5

Page 6: Validation  of Radio Channel Models using an Anechoic Chamber

record RSStransmit pkts

Experimental Framework

6

chamber wall

Soekris Engineering net4521wireless node

attenuator (directional)

reflector (material varies)

20 ft

11 ft

experiment measured

model predicted

compare& validate

Page 7: Validation  of Radio Channel Models using an Anechoic Chamber

Simple Raytracing Model

7

• Wireless node single point– Assumption: omnidirectional antenna

• Attenuator fixed pathloss coefficient– Depends on direction

• Reflector line– Material-dependent reflection rate, tuned offline

N

ai aedi

de

n points

k=1n ∗k ref∗ cos (a i−ae)∗pathloss (d i+de )

Contribution of this single reflection path:

a series of points

Page 8: Validation  of Radio Channel Models using an Anechoic Chamber

Advanced Raytracing Model

• Consider path loss & path delay– Revision to single reflection path

– Complex number addition

8

direct pathreflected path

Im

Re

• More general radio model– Single point point matrix

N

ai aedi

de

n points

Page 9: Validation  of Radio Channel Models using an Anechoic Chamber

Transmission Line Matrix Model

• Even-based Transmission Line Matrix [Nutaro’06]• Space cells displacement state• A cell can change state when– External event: from adjacent cells– Internal event: when not at equilibrium position

• Implementation details– Grid size = λ/D, D is tunable– Source: sinusoidal– RSS: average over time

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Page 10: Validation  of Radio Channel Models using an Anechoic Chamber

Experimental Results

10

20 ft

11 ft

large-scale movement

small-scale movement

direction A

direction B

Page 11: Validation  of Radio Channel Models using an Anechoic Chamber

Results – Large-scale Movement

11

0 2 4 6 8 10 12 14 16 18 20-60

-59

-58

-57

-56

-55

measured simplified RT normal RT event TLMX Position (ft)

Rece

ived

Sig

nal

Stre

ngth

(dBm

)

0 2 4 6 8 10 12 14 16 18 20-68-67-66-65-64-63-62

measured simplified RT normal RT event TLMX Position (ft)

Rece

ived

Sig

nal S

tren

gth

(dBm

)

direction A

direction B

can capture the peakbut not exact shape

~2dB error

Page 12: Validation  of Radio Channel Models using an Anechoic Chamber

Results – Small-scale Movement

12

120 122 124 126 128 130 132-64

-62

-60

-58

-56

-54

measured simplified RT normal RT event TLM

Y Position (in)Rece

ived

Sig

nal S

tren

gth

(dBm

)

120 122 124 126 128 130 132-70

-68

-66

-64

-62

measured simplified RT normal RT event TLM

Y Position (in)

Rece

ived

Sig

nal S

tren

gth

(dBm

)

direction A

direction B

cannot capture the shape~2dB error

Page 13: Validation  of Radio Channel Models using an Anechoic Chamber

Results – Radio Beamform

13

wireless box @rotating table

spectrum analyzer

Page 14: Validation  of Radio Channel Models using an Anechoic Chamber

Results – Radio Beamform

14

-180 -135 -90 -45 0 45 90 135 180-80

-70

-60

-50

-40

-30

VPol HPol Total

Angle

Pow

er L

evel

(dBm

)

up to 10dB variation!

Page 15: Validation  of Radio Channel Models using an Anechoic Chamber

Results – Resolution of Raytracing

15

120 122 124 126 128 130 132-69

-68

-67

-66

-65

-64

-63

measured RT n=9 RT n=25 RT n=49

Y Position (in)

Rece

ived

Sig

nal S

tren

gth

(dBm

)converged, n=9 is good

Page 16: Validation  of Radio Channel Models using an Anechoic Chamber

Results – Resolution of TLM

16

120 122 124 126 128 130 132-72-71-70-69-68-67-66-65-64-63-62-61-60

measured TLM D=1.5 TLM D=5 TLM D=8

Y Position (in)

Rece

ived

Sig

nal S

tren

gth

(dBm

)not converged, D=8 is the best

Page 17: Validation  of Radio Channel Models using an Anechoic Chamber

Conclusions & Future Works

• Conclusions– 2dB error of both raytracing & TLM– Model uncertainty > error eliminated by chamber– Validation outside the chamber may be okay

• Future works– Quantify the speed of different models– Consider the beamform of antenna

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Page 18: Validation  of Radio Channel Models using an Anechoic Chamber

Backup Slides

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Page 19: Validation  of Radio Channel Models using an Anechoic Chamber

Result – Antenna Shape

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120 122 124 126 128 130 132-67

-66

-65

-64

real point h-line v-line s-rect l-rect

Y Position (in)

Rece

ived

Sig

nal S

tren

gth

(dBm

)

Page 20: Validation  of Radio Channel Models using an Anechoic Chamber

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Page 21: Validation  of Radio Channel Models using an Anechoic Chamber

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