PPT On Energy Efficient Wireless Sensor Networks using Asymmetric Distributed Source Coding
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Energy Efficient Wireless Sensor Networks using Asymmetric Distributed Source Coding Presentation Transcript:
1.Energy Efficient Wireless Sensor Networks using Asymmetric Distributed Source Coding
2.OBJECTIVE Model WSN
Use Distributed Source Coding - Remove spatial redundancy
Reduce bandwidth, energy consumption
3.MOTIVATION
The MIT Technology Review - number one emerging technology
set of unique constraints and requirements.
Limited power – runs on battery
4.BACKGROUND
5.Background
Liveris - LDPC, near Slepian limit
DSC with WSN
Suggested - Xiong
Applied for analog data
– Chou et al
“Tracking and exploiting correlations in dense sensor networks,”
6.Our Solution
For binary Data
Use DSC for source coding
Use asymmetric chanel codes
move the complexity receiver
Govinda et al [1]
Simulation
7.Simulation Approach
Model Sources
spatial correlation
BSC between sources
Model WSN using Simulink
Apply DSC using Matlab
We have chosen BPSK as the modulation with RS(331,21) –[1]
Decode Jointly
8.DSC
Estimating Y with the knowledge of X
Algorithm
Create random binary X, create Y from passing X through BSC.
Encode X, Y with [n,k] code.
Send encoded X (n bits)and syndrome of Y (n-k) bits
Decode X
Decoded Y = decode(X+ syndrome(Y))
Calculate BER of Y
9.Mathematical Modelling
10.Energy Calculation
Energy saving ratio proportional to the no of bits saved
Download
Energy Efficient Wireless Sensor Networks using Asymmetric Distributed Source Coding Presentation Transcript:
1.Energy Efficient Wireless Sensor Networks using Asymmetric Distributed Source Coding
2.OBJECTIVE Model WSN
Use Distributed Source Coding - Remove spatial redundancy
Reduce bandwidth, energy consumption
3.MOTIVATION
The MIT Technology Review - number one emerging technology
set of unique constraints and requirements.
Limited power – runs on battery
4.BACKGROUND
5.Background
Liveris - LDPC, near Slepian limit
DSC with WSN
Suggested - Xiong
Applied for analog data
– Chou et al
“Tracking and exploiting correlations in dense sensor networks,”
6.Our Solution
For binary Data
Use DSC for source coding
Use asymmetric chanel codes
move the complexity receiver
Govinda et al [1]
Simulation
7.Simulation Approach
Model Sources
spatial correlation
BSC between sources
Model WSN using Simulink
Apply DSC using Matlab
We have chosen BPSK as the modulation with RS(331,21) –[1]
Decode Jointly
8.DSC
Estimating Y with the knowledge of X
Algorithm
Create random binary X, create Y from passing X through BSC.
Encode X, Y with [n,k] code.
Send encoded X (n bits)and syndrome of Y (n-k) bits
Decode X
Decoded Y = decode(X+ syndrome(Y))
Calculate BER of Y
9.Mathematical Modelling
10.Energy Calculation
Energy saving ratio proportional to the no of bits saved
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