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Using LMS weighting value as the CSI for soft decision Viterbi decoder. Advisor : Yung-An Kao Student : Chi-Ting Wu 2005.01.28. Outline. Introduction Block diagram Formula computation Simulation results Conclusion. Introduction. - PowerPoint PPT Presentation
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Using LMS weighting value as the CSI for soft decision
Viterbi decoder
Advisor : Yung-An Kao
Student : Chi-Ting Wu
2005.01.28
Outline
• Introduction • Block diagram• Formula computation• Simulation results• Conclusion
Introduction
• For Viterbi decoder, we view different sub-carriers in the same channel condition
• Actually, different sub-carrier suffers different channel condition
• Using the CSI for each sub-carriers• long train symbol? What else?• equalizer weighting values !!
Block diagram
Convolutional Encoder
Random Data Bits
Interleaver Constellation mapping IFFT
Add cyclic prefix
Add preamble
Radio front
Channel
Sample(20 MHz)
Remove cyclic prefixFFT
Frequency domain
equalizer
Constellation demapping
De-interleaver
Viterbi Decoder
Received Data Bits
CSI from long train symbol
CSI from long train symbol
and LMS weighting value
Formula computation
• According to the Central Limit Theorem, after we transmit lots of symbols, they all seems like Gaussian distribution
• The likelihood function
will become
1 2 3( ) ( ; ) ( ; ) ( ; ) ( ; )nL f x f x f x f x
2
2
( )
21( )
2
x
f x e
22
1
1 1( ) ( ) exp{ ( ) }
22
nn
ii
L x
Formula computation
22
1
1 1ln ( ) ln( ) ( )
22
n
ii
L n x
,
,
2
2 2
2 2
2
k l
k l
jk
k k
k N
k Nk kj
k
H er s
H
Hr s
H e
,
, 2 2
k ljk
k l
k N
H ew
H
The received signal after phase compensation is
,
* *
*2 2
( )
( )k l
k k k k
jk
k k k
k N
w H S n
H eH S n
H
And we know that the weighting value is
Formula computation
kr
,* **
2 2
2
2 22 2
( )( ) ([ ( )] / )
k ljkk k k k
k k k kk k N
k k k
kk N k N
H ew H S nabs abs H S n S
S H
H H n
SH H
We want the same weighting value for
Therefore, we use the weighting value :
And we take the expected value
2 2
2 2 22 2 2[ ]k k kk
kk N k N k N
H H HnE
SH H H
Simulation ~ interleaver
500 symbols
100 times average
1:1:15 dB
CFO=0.01
No SFO
Trms=50ns
4 bit quantization
No weighting value
Simulation ~ quantization
100 symbols
100 times average
1:1:15 dB
CFO=0.01
No SFO
Trms=50ns
No weighting value
Simulation ~ weighted CSI
500 symbols
100 times average
1:1:15 dB
CFO=0.01
No SFO
Trms=50ns
4 bit quantization
With interleaver
Simulation ~ weighted CSI
1000 symbols
100 times average
1:1:15 dB
CFO=0.01
No SFO
Trms=50ns
4 bit quantization
With interleaver
Conclusion
• Weighting values added should has better performance
• Some dimension problems should take notice