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The Impact of Directional Antenna Models on Simulation Accuracy - - PowerPoint PPT Presentation

The Impact of Directional Antenna Models on Simulation Accuracy Eric Anderson, Gary Yee, Caleb Phillips, Douglas Sicker, and Dirk Grunwald eric.anderson@colorado.edu University of Colorado Department of Computer Science 25 June 2009


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SLIDE 1
  • The Impact of Directional Antenna Models on

Simulation Accuracy

Eric Anderson, Gary Yee, Caleb Phillips, Douglas Sicker, and Dirk Grunwald eric.anderson@colorado.edu

University of Colorado Department of Computer Science

25 June 2009

Eric Anderson (CU Boulder) The Impact of Directional . . . WiOpt ’09 1 / 21

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SLIDE 2
  • Outline

1

Introduction Physical Layer Simulation Current Models of Directivity

2

EDAM – The Effective Directivity Antenna Model Error Idea Parameters

3

Case Study Overview Metrics Results

4

Conclusions

Eric Anderson (CU Boulder) The Impact of Directional . . . WiOpt ’09 2 / 21

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SLIDE 3
  • Phy-Layer Simulation Framework

Two−ray COST 231 ITU1238

Path Loss

... ...

Fading

Rician Rayleigh

Directivity Model

EDAM Antenna Gain Only None

Environmental Factors

In/Outdoors Line of Sight Motion In/Outdoors Terrain Line of Sight

Position Direction / Orientation Temporal Variation

Antenna Properties

Eric Anderson (CU Boulder) The Impact of Directional . . . WiOpt ’09 3 / 21

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SLIDE 4
  • Directivity – Current Models

Eric Anderson (CU Boulder) The Impact of Directional . . . WiOpt ’09 4 / 21

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SLIDE 5
  • Directivity – Current Models

Fading & path loss Node a gain Node b gain Prx = Ptx ∗ X ∗ fa(θ1) ∗ fb(θ2)

Eric Anderson (CU Boulder) The Impact of Directional . . . WiOpt ’09 4 / 21

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SLIDE 6
  • Example
  • Eric Anderson (CU Boulder)

The Impact of Directional . . . WiOpt ’09 5 / 21

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SLIDE 7
  • Example
  • fa(θ1)

fb(θ2)

Eric Anderson (CU Boulder) The Impact of Directional . . . WiOpt ’09 5 / 21

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SLIDE 8
  • Example
  • fa

( θ3 ) f

b

( θ

4

)

Eric Anderson (CU Boulder) The Impact of Directional . . . WiOpt ’09 5 / 21

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SLIDE 9
  • Example
  • Eric Anderson (CU Boulder)

The Impact of Directional . . . WiOpt ’09 5 / 21

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SLIDE 10
  • Outline

1

Introduction Physical Layer Simulation Current Models of Directivity

2

EDAM – The Effective Directivity Antenna Model Error Idea Parameters

3

Case Study Overview Metrics Results

4

Conclusions

Eric Anderson (CU Boulder) The Impact of Directional . . . WiOpt ’09 6 / 21

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SLIDE 11
  • How Bad Is It?

25 50 75 105 140 175 210 245 280 315 350 −50 −40 −30 −20 −10 10 Patch−Panel Antenna Angle, Degrees Counterclockwise dB Relative to Peak Mean

Patch−Outdoor−B Patch−Outdoor−A Patch−Indoor−A Reference

Eric Anderson (CU Boulder) The Impact of Directional . . . WiOpt ’09 7 / 21

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SLIDE 12
  • How Bad Is It?

21 50 76 106 140 171 205 236 270 301 335 −50 −40 −30 −20 −10 10 24dBi Parabolic Dish, Indoors Angle, Degrees Counterclockwise dB Relative to Peak Mean

Parabolic−Indoor−C Parabolic−Indoor−B Parabolic−Indoor−A Reference

Eric Anderson (CU Boulder) The Impact of Directional . . . WiOpt ’09 7 / 21

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SLIDE 13
  • EDAM – The Effective Directivity Antenna Model

Key Idea:

Model offset between the expected (“pure”) antenna gain and observed effect. Offset is environment-specific and impractical to compute

(but easy to measure)

Distribution of offsets can be predicted well. Construct distributions, sample, repeat.

Eric Anderson (CU Boulder) The Impact of Directional . . . WiOpt ’09 8 / 21

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SLIDE 14
  • EDAM Distribution Parameters

Mean offset is based on antenna gain and environment type. Offset variance and packet signal variance are based on environment type. See “Modeling environmental effects on directionality in wireless networks,”

WiNMee 2009 (tomorrow).

Eric Anderson (CU Boulder) The Impact of Directional . . . WiOpt ’09 9 / 21

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SLIDE 15
  • Outline

1

Introduction Physical Layer Simulation Current Models of Directivity

2

EDAM – The Effective Directivity Antenna Model Error Idea Parameters

3

Case Study Overview Metrics Results

4

Conclusions

Eric Anderson (CU Boulder) The Impact of Directional . . . WiOpt ’09 10 / 21

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SLIDE 16
  • Case Study: Data Striping for Security

Compare simulated and real results

(S. Lakshmanan et. al, 2008)

Propagation-sensitive system:

APs beam-form to client Packet must be received from all APs to decode.

Eric Anderson (CU Boulder) The Impact of Directional . . . WiOpt ’09 11 / 21

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SLIDE 17
  • Experimental Design

Directivity Path Loss Fading EDAM Two ray Log-normal Pure ITU-1238 Ricean None/Omni Implicit Gaussian None

Directivity Null Hypotheses

1 “Pure:” Antenna gain fully describes directional effects. 2 “None/Omni:” There is no predictable directional effect. (indoor) Eric Anderson (CU Boulder) The Impact of Directional . . . WiOpt ’09 12 / 21

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SLIDE 18
  • “Ground Truth” Measurement

5 10 15 20 25 30 5 10 15 20 25 30 35 Measurement Points x coordinate y coordinate X position 5 10 15 20 25 30 Y position 10 20 30 Signal strength, dBm −100 −80 −60 −40 −20 Signal strength from 192.168.99.2

foo

Eric Anderson (CU Boulder) The Impact of Directional . . . WiOpt ’09 13 / 21

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SLIDE 19
  • Application Performance: Vulnerability Area

Application goal: Minimize physical area of reception. Metric: Fraction of packets decodable at each location. Distribution, not scalar.

0.0 0.2 0.4 0.6 0.8 0.0 0.2 0.4 0.6 0.8 1.0 CDF of packet reception probability by location, outdoor Fraction of packets received completely Cumulative fraction of nodes Observed Sim: NA, NA, NA

Actual performance, outdoor test

Complete packet reception probability

x coordinate y coordinate

10 20 30 5 10 15 20 25 30 0.0 0.2 0.4 0.6 0.8 1.0

Eric Anderson (CU Boulder) The Impact of Directional . . . WiOpt ’09 14 / 21

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SLIDE 20
  • Simulation Accuracy: Distribution Similarity

Accuracy = similarity of application performance to reality. Kolmogorov-Smirnov (KS) test: Maximum divergence between distributions. Evaluation: Factorial ANOVA on KS test across all configurations.

0.0 0.2 0.4 0.6 0.8 1.0 0.0 0.2 0.4 0.6 0.8 1.0

CDF of packet reception probability by location, outdoor

Fraction of packets received completely Cumulative fraction of nodes Observed Sim: pure, two ray, lognormal

Eric Anderson (CU Boulder) The Impact of Directional . . . WiOpt ’09 15 / 21

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SLIDE 21
  • Results (subset)

EDAM Pure Gain Indoor Outdoor

Eric Anderson (CU Boulder) The Impact of Directional . . . WiOpt ’09 16 / 21

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SLIDE 22
  • 50% Vulnerability Region – Indoor

Directivity Model Area (points) Pure antenna 3 - 5 Measured 38 EDAM 54 - 79 Omni (no directionality) 83 (100%)

Eric Anderson (CU Boulder) The Impact of Directional . . . WiOpt ’09 17 / 21

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SLIDE 23
  • Outline

1

Introduction Physical Layer Simulation Current Models of Directivity

2

EDAM – The Effective Directivity Antenna Model Error Idea Parameters

3

Case Study Overview Metrics Results

4

Conclusions

Eric Anderson (CU Boulder) The Impact of Directional . . . WiOpt ’09 18 / 21

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SLIDE 24
  • Highlights

EDAM enables more accurate simulation and modeling of networks with directional antennas.

Dramatic improvement indoors Marginal improvement outdoors

Directional effects are significant – even in worst case. Determinants of accuracy: (indoor):

1 Directivity model ≫ 2 Path loss model ≫ 3 Fading model

(outdoor):

1 Path loss model > 2 Fading model ≫ 3 Directivity model. Eric Anderson (CU Boulder) The Impact of Directional . . . WiOpt ’09 19 / 21

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SLIDE 25

Thank you

Contact: eric.anderson@colorado.edu Simulation software (Qualnet 4.5.1 patch): http://systems.cs.colorado.edu/ Raw measurements: http://www.crawdad.org/cu/antenna

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SLIDE 26

KS−Test Statistic For all Configurations and Seeds

Kolmogorov−Smirnov Test Statistic

0.2 0.4 0.6 0.8 1.0 EDAM−ITU 1238−Ricean EDAM−ITU 1238−implicit Gaussian EDAM−ITU 1238−lognormal EDAM−two ray−Ricean EDAM−two ray−implicit Gaussian EDAM−two ray−lognormal

  • mni−ITU 1238−Ricean
  • mni−ITU 1238−lognormal
  • mni−ITU 1238−none
  • mni−two ray−Ricean
  • mni−two ray−lognormal
  • mni−two ray−none

pure−ITU 1238−Ricean pure−ITU 1238−lognormal pure−ITU 1238−none pure−two ray−Ricean pure−two ray−lognormal pure−two ray−none

indoor

0.2 0.4 0.6 0.8 1.0

  • utdoor