1

Experimental Study of Concurrent Transmission in Wireless Sensor Networks

Dongjin Son, Bhaskar Krishnamachari (USC/EE),

and John Heidemann (USC/ISI)

2

Motivation• Prior work

– Understanding wireless propagation essentials

• Zhao, Ganesan, Aguayo, Cerpa, Woo, Lal, Zuniga, Son, etc.

– Only few consider concurrent packet transmission

• Whitehouse, Jamieson, Kochut

• Concurrent transmission is endemic in dense networks– Applications

• Event detection and target tracking • Code distribution and flooding for route discovery

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Research goals

Understanding concurrent packet transmissions !

– Systematic experimental study

– Single and multiple interferers

– Develop a better interference model

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Main findings

• Single Interferer effects– Capture effect is significant– SINR threshold varies due to hardware– SINR threshold does not vary with location– SINR threshold varies with measured RSS– Groups of radios show ~6 dB gray region– New SINR threshold (simulation) model

• Multiple interferer effects– Measured interference is not additive– Measured interference shows high variance– SINR threshold increases with more interferers

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Main findings

• Single Interferer effects– Capture effect is significant– SINR threshold varies due to hardware– SINR threshold does not vary with location– SINR threshold varies with measured RSS– Groups of radios show ~6 dB gray region– New SINR threshold (simulation) model

• Multiple interferer effects– Measured interference is not additive– Measured interference shows high variance– SINR threshold increases with more interferers

November 11, 2003 6

Part I: Single interferer

• Main research questions– Does concurrent transmission imply a

collision ?

– Can we identify a constant SINR threshold

(SINRӨ) for capture?

• Experiments– Two concurrent senders

• varying transmitter hardware and power

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Methodology

Sender1(SRC1)

Sender2(SRC2)

Receiver

Synchronizer(Sync)

Time

Sync

PC104

Mica2

Synchronizes the clocks of both senders

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Methodology

Receiver

Synchronizer(Sync)

Time

Sync SRC1

Measure the RSS of Sender1 (S1)

Measure an ambient Noise (N)

Sender1(SRC1)

Sender2(SRC2)

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Methodology

Receiver

Synchronizer(Sync)

Time

Sync SRC1 Sync SRC2

Measure the RSS of Sender2 (S2)

Measure the ambient Noise (N)

Sender1(SRC1)

Sender2(SRC2)

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Methodology

Receiver

Synchronizer(Sync)

Time

Sync

Sender1(SRC1)

Sender2(SRC2)

SRC1 Sync SRC2

Test the delivery of the sender’s packet under the CTX

Sync SRC1

SRC2

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Methodology

Receiver

Synchronizer(Sync)

Time

Sync

Sender1(SRC1)

Sender2(SRC2)

SRC1 Sync SRC2

Test the delivery of the sender’s packet under the CTX

Sync SRC1

SRC2

• Stronger packet ► Signal• Weaker packet ► Interference

Repeat this epoch and measure PRR

vary Tx power, hardware, location

epoch

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Power and PRR based regions

Gray10~90% PRR

Black< 10% PRR

White> 90% PRR

• Black-Gray-White due to power change• Prior work (Zhao, woo etc) use a distance based definition

• SINR threshold (SINRθ)

– SINR (Signal-to-interference-plus-noise) value which ensures reliable packet reception

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Capture effect

[Finding] Capture effect is significant & SINRθ is not constant

• Concurrent packet transmission does not always means packet collision (capture effect: recently studied by Whitehouse et al.)

• Systematically study capture effects and quantify the SINRθ value

White

White

Black

Gray

Gray

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Modeling SINR to PRR relationship

▪ ß0 changes the shape

(ß0 is set to 2.6 based on the empirical data)

▪ ß1 changes the location

f: frame size of the packet in bytesl: preamble size in bytes- Model based on the link layer model by Zuniga and Krishnamachari

ß0=2ß0=3

ß0=1

-1 0 1 2ß1

β0,β1

β0,β1

β0,β1

β0,β1

β0,β1

β0,β1

• Regression model for simple description of experimental data

)2(8)exp5.01( 10 lfSINRPRR

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Transmitter hardware effect

• How much SINR threshold change does transmitter hardware can make ? – Does hardware variation dominate other effects?

• E.g., compared to the location effect

• Experiments– Hold location constant– Swap one of the transmitter hardware

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Does transmitter hardware affect SINRӨ ?• Vary transmitter hardware (SRC1-SRC2, SRC1-SRC3)

while keeping the same receiver

[Finding] SINRӨ changes with different transmitter hardware

SRC1(with SRC2)

SRC1(with SRC3) SRC3

(with SRC1)

SRC2(with SRC1)

-1.7 dB+1 dB 5.3 dB3.4 dB

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Signal strength effect

• Is SINR threshold constant at different

signal (or interference) strength level? – I.e., Can we always identify a constant SINR

threshold for the same hardware pair ?

• Experiments– Hold location and use the same transmitter pair– Vary transmission power of both transmitters

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Does signal strength level affect SINRӨ?

• Same transmitter hardware, but vary both sender and interferer’s transmission power levels.

[Finding] SINRӨ changes at different signal strength levels

-74 -72 -70 -68 -66 -64 -62 -60 -58 -561

2

3

4

5

6

7

Received signal strength (dBm)

SIN

R th

resh

old

(dB

)

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Implications of findings

• Protocols based on constant SINR threshold assumption will fail– Power control protocol and capture-aware protocol

should consider variable SINRθ

– New interference model is necessary

Signal strength

(4.6 dB)

Hardware Signal strength+ Hardware(d

B)

November 11, 2003 20

Part II: Multiple interferers

• Main research questions– Textbook says “Interference is additive”, – How about the reality with low-power RF

transceiver ?

• Experiments– Empirically test the additive signal strength

assumption • Varying the number of interferers and Tx power

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Methodology

Sender

Interferer1

(IFR1)

Interferern

(IFRn)

Receiver

Synchronizer(Sync)

Time

Sync Sender

Measure the RSS of Sender (S)

Measure an ambient Noise (N)

PC104

Mica2

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Methodology

Sender

Interferer1

(IFR1)

Interferern

(IFRn)

Receiver

Synchronizer(Sync)

Time

Sync Sender Sync IFR1

Measure the RSS of Interferer1 (I1)

Measure an ambient Noise (N)

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Methodology

Sender

Interferer1

(IFR1)

Interferern

(IFRn)

Receiver

Synchronizer(Sync)

Time

Sync Sender Sync IFR1 Sync IFRn

Measure the RSS of Interferern (In)

Measure the ambient Noise (N)

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Methodology

Sender

Interferer1

(IFR1)

Interferern

(IFRn)

Receiver

Synchronizer(Sync)

Time

Sync Sender Sync IFR1 Sync IFRn Sync IFR1

IFRn

Measure the Joint Interference

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Methodology

Sender

Interferer1

(IFR1)

Interferern

(IFRn)

Receiver

Synchronizer(Sync)

Time

Sync Sender Sync IFR1 Sync IFRn Sync IFR1

IFRn

Test the delivery of the sender’s packet

Sync Sender

IFR1

IFRn

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Joint interference (JRIS) estimatorsTime

RIS RIS RIS

IFR1

IFR2

IFR3 IFR3

IFR2

IFR1

IFR1 IFR2 IFR3

Summation of independent interference measurement

Average of the actual joint interference measurements

Jointly Measured

Independently Measured

JRIS(e)

JRIS(m)

Textbook prediction!

Direct measurement!

expected

measured

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Does joint interference show additivity?

Comparison between JRIS(e) and JRIS(m) when two interferers (IFR1 and IFR2) have equivalent RISs at the receiver

[Finding] Measured interference is not additive• JRIS(e) is higher than JRIS(m) • Additive behavior is different at different signal strength levels

Individual RIS of IFR1 and IFR2 (dBm)

RIS

(d

Bm

)

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Joint Interference and SINRθ

SINR threshold measurements with different number of interferers

2 Interferer

3 Interferer

4 Interferer

JRIS(e)JRIS(m)

-73 dBm

-68.8 dBm -64.1 dBm

-73 dBm

-68.8 dBm -64.1 dBm

1 Interferer

[Finding] SINR threshold increases with more interferers

• SINR threshold changes with different number of interferers which changes the joint received interference strength

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Potential of capture-aware MAC

• Compare the number of CTXable (Concurrently Transmittable) links

• Methodology• Trace-based Simulation

• Uses real measured RSS• Without Tx power control• Assume red link Tx, who

can CTX together?

• Observation– More available links for the

capture-aware medium access

CTXable links with RTS/CTS based MAC

RTS/CTS based

CTXable links with capture-aware MAC

Capture-aware

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Generalized for all links in the testbed

Capture-aware

Capture-unaware

• The number of CTXable links comparison between traditional and capture-aware MAC

[Finding] Capture-aware MAC shows about 3 times more CTXable links on average

31USC ANRG: http://ceng.usc.edu/~anrg I-LENSE: http://www.isi.edu/ilense

Conclusion• Experimental results show

– the significance of capture effects as Tx power varies

– some of the theoretical assumption does not hold for the measurements

(1) SINR threshold varies (not constant)

(2) Multiple interference worse than addition (not additive)

– better understanding of single and multiple interference on

packet delivery

• Experimental results imply– need better SINR threshold simulation models

– more efficient use of wireless channel is possible with better understanding of concurrent packet transmission

E.g.,) Capture-aware medium access protocol