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Power Efficient Wireless Sensor Networks with Distributed Transmission-Induced

Space Spreading

Xiaohua (Edward) Li and N. Eva WuDepartment of Electrical and Computer Engineering

State University of New York at Binghamton{xli, evawu}@binghamton.edu

http://ucesp.ws.binghamton.edu/~xli

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Major Contributions

• Resolve the conflict between transmission energy efficiency and fault tolerance

• Propose distributed space-spreading for1. Efficient/robust blind signal detection

2. Transmission energy efficiency

3. Network reliability

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1.1. Sensor Network Challenges• How to improve transmission energy efficiency in deep-

faded near-ground communications?• How to improve fault tolerance and network reliability

with low cost sensors suffering from high failure rate?• How to resolve the conflict between energy efficiency

and fault tolerance? They have contradictory requirements on redundancy.

Multi-hop WirelessSensor Network

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1.2 Strategies for the Challenges

• Distributed multi-transmission with space-spreading– Transmission redundancy provides diversity for

energy efficiency– Transmission redundancy provides fault tolerance

Scrambled ParallelTransmission from

J Sensors

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• Why can we use multi-transmission?– Wireless transmission is broadcasting

• a data packet can be received/retransmitted by multiple sensors

– There are always multiple standby sensors ready for multi-transmission

• Energy in standby state is in the same level as in receiving state

• How to perform multi-transmission?– Distributed space-spreading: scrambled parallel

transmission (the above figure)– Distributed space-time coding: to appear in

Electronics Letters, 2003.

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2. Space Spreading and Blind Symbol Estimation

• Sensor j in cluster i transmits the same signal s(n) with different PN scrambling:

• A sensor in cluster i+1 receives (separately) signals from all sensors j:

)()0(

)()0(

fadingRayleigh :

),()()(

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1ˆ.,.,||)(||minarg

:jsensor each from signals ofon equalizati Blind

1.rank are and )()( because

],,,,,[

)],()()()([

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jJjjjjjj

iHijjji

dncndns

tsn

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xf

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RRRRR

xxR

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3. Energy Efficiency Analysis

• Transmission energy efficiency comes from the diversity of the scrambled parallel transmission

• Major results:

on.transmissi-single than SER same theachieve to

power lessmuch usecan or (SER), rate-error-symbol

lessmuch hason transmissi-multi ,1/][ If

.][ beon transmissi-multiin sensor each of

power theand ,][ bepower totalLet the 1.n Propositio

222

22

22

vsj

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].~[][

such that ~

exists thereon,transmissi-multiFor

on.transmissi-single ofpower thebe ]~[~

Let .2 Propostion

2

1

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APAP

E

J

jj

J

s

Power ratio of single-transmission to multi-transmission for15 dB SNR withProbability B.

Multi-transmission canbe more than 30 dBmore energy efficient.

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4. Fault-Tolerance Analysis

).( smallest

for the gprogrammin dynamic dconstraine Use

).( smallest thehas that Determine :Solutions

lifenetwork specified aat y probabilithighest the

achievescluster each such that ],,[

sensors active ofnumber select the cluster,each For :Problem

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)],(1[1)(

:yprobabilit failurenetwork hop-K

clustereach for Jnumber sensor active determine

network, overall for thety availabili signal maximize :Goal

max,min,

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0

1

tF

tFJ

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JJJ

etRtRtRr

JtF

tFtF

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Fii

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iii

k

r

tSnsrJSnsrrSnsriFi

Fi

Ki

F

ri

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• Example: For design life TD=2000 packets, J=2 is better and has reliability 0.89. However, for reliability 0.99, J=10 is better, though with a shorter design life TD=1000 packets.

0 200 400 600 800 1000 1200 1400 1600 1800 20000

0.05

0.1

0.15

0.2

0.25

Cumulative Distribution Function of the i-th Sensor Cluster (/Ii=0.0001 failures/packet)

Fa

ilure

pro

ba

bili

ty o

f th

e i

-th

se

ns

or

clu

ste

r

Number of transmitted packets through the i-th sensor cluster

1 participating sensor/packet transmission 2 participating sensors/packet transmission 10 participating sensors/packet transmission

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5. Simulations

Multi-transmission:New batch & adaptive algorithms: J=8 sensors.

Single-transmission:DSSS with Rake receiver: processing gain 8.

Blind CMA

Training MMSE equalization

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Compare space-spreading with spectrum-spreading (DSSS)

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• Transmission power (normalized with that of the new batch algorithm) required to achieve symbol-error-rate (SER) 0.01

• Multi-transmission-based space-spreading has higher energy efficiency, longer sensor lifetime, and higher reliability.

New

Batch

New

Adaptive

Training MMSE

Blind CMA

DSSS/Rake

Transmission Power

1 1.12 14.1 >89 7.1

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6. Conclusions

• Propose a new space-spreading scheme for wireless sensor networks to achieve– transmission energy efficiency – blind symbol estimation– transmission/network reliability

• Resolve the conflict between energy efficiency and fault tolerance via transmission redundancy