LLR-based Distributed Detection for Wireless Sensor Networks

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LLR-based Distributed Detection for Wireless Sensor Networks 後後後後後後後 後後後後後後後後 2008/01/07

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LLR-based Distributed Detection for Wireless Sensor Networks. 後卓越進度報告 蔡育仁老師實驗室 2008/01/07. High LLR. Low LLR. Binary Hypothesis Testing. LLR: Log Likelihood Ratio The received signal Observation noise: assumed to be. Distributed Detection Depends on Likelihood Ratio. - PowerPoint PPT Presentation

Transcript of LLR-based Distributed Detection for Wireless Sensor Networks

Page 1: LLR-based Distributed Detection for Wireless Sensor Networks

LLR-based Distributed Detection for Wireless Sensor Networks

後卓越進度報告

蔡育仁老師實驗室2008/01/07

Page 2: LLR-based Distributed Detection for Wireless Sensor Networks

LLR: Log Likelihood Ratio The received signal

Observation noise: assumed to be

Binary Hypothesis Testing

2 2

1 0 1 01 12

0 0

2( | ) ( )ln ln

( | )

ii ii

i i n

yf y H f yDefine LLR Z

f y H f y

),(~)(

),(~)(2

00

211

ni

ni

Nyf

Nyf

0 1

Low LLR High LLR

0H 1H

0 0

1 1

:

:i i

i i

H y n

H y n

2~ (0, )i nn N

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Distributed Detection Depends on Likelihood Ratio

LLR can be treated as the reliability of a sample value Power allocation in WSNs

Power allocation in each sensor based on the instantaneous observed signal

Large absolute value of LLR High reliability Allocate more power; vice versa

Sequential detection in WSNs Can reduce the number of required transmission with t

he similar detection performance Ordering the message transmission based on the LLR

can further reduce the number of transmission Save more communication power

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0 0

1 1

( )

( )

P H

P H

2~ (0, )k nn N

k kp u

2 2p u

0 1/H H

1S

2S

……

NS

1y

2y

Ny

Fusion Center

1 1p u

= ,

1, 2,......k k k kr p u w

k N

2~ (0, )k ww N

Power Allocation Depends on Log Likelihood Ratio in WSNs

2

1 00 2 2

4Define the local observation quality SNR at each node as

n n

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Sequential Detection Depends on Log Likelihood Ratio in WSNs The thresholds ln(A) and ln(B) depend on the target false

alarm probability and miss detection probability

H1

NLLR

(N)

lnA

lnBH0

1 2 3 4 5 6 7 8

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Simulation – LLR-based Power Allocation

10-5

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Detection error probability

Req

uire

d po

wer

in p

erce

ntag

e

Scheme 1,o=4

Scheme 1,o=6

Scheme 1,o=8

Scheme 1,o=10

Scheme 2,o=4

Scheme 2,o=6

Scheme 2,o=8

Scheme 2,o=10

Scheme1 g

Scheme2 g

k k

k k k

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Simulation – LLR-based Sequential Detection

FSSReal Value T-SPRTOrdered Real Value T-SPRT

Detection error probability

Req

uire

d nu

mbe

r of

tra

nsm

issi

on

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Publications

Journal Paper Yuh-Ren Tsai, “Sensing Coverage for Randomly Distributed Wire

less Sensor Networks in Shadowed Environments,” IEEE Transactions on Vehicular Technology, vol. 57, no. 1, Jan. 2008. (SCI, EI)

Conference Paper Yuh-Ren Tsai, Kai-Jie Yang and Sz-Yi Yeh, “Non-uniform Node

Deployment for Lifetime Extension in Large-scale Randomly Distributed Wireless Sensor Networks,” in Proc. of IEEE International Conference on Advanced Information Networking and Applications (AINA2008), Okinawa, Japan, March 2008.

Yuh-Ren Tsai, and Jyun-Wei Syu, “Down-link CIR Spatial Correlation and CIR Prediction for CDMA Cellular Systems,” in Proc. of IEEE 2008 Vehicular Technology Conference (VTC-2008 Spring), Singapore, May 2008.