View
194
Download
1
Category
Preview:
Citation preview
David Sabater Dinter Research Group for RF Communications 2003-5-26 1
Parallel interference cancellation in beyond 3G multi-user and multi-antenna OFDM systems
David Sabater Dinter University of Kaiserslautern
dinter@rhrk.uni-kl.de
Supervisor: A. Sklavos
David Sabater Dinter Research Group for RF Communications 2003-5-26 2
summary
• service area based system in the uplink• transmission model• subcarrierwise investigation• optimum and suboptimum linear detection• parallel interference cancellation • PIC with improved estimate refinement • simulation results• conclusions
David Sabater Dinter Research Group for RF Communications 2003-5-26 3
uplink transmission in a service area
MT
AP
CU
AP
AP
MT
MT
1d
2d
ˆ Kd
1d
2d
Kd
David Sabater Dinter Research Group for RF Communications 2003-5-26 4
B B
1,1 ,1
1, 2 , 2
1, , B
(1)
(2)
( )B
(1)
(2)
( )
(1)
(2)
( )
K
K
K K K K KK
H H
H H
H H
dd
d
nn
n
ee
e
transmission model
• Additive noise vector at AP :• Received signal vector at AP :
Bk
Bk
B B B F( ) ( ,1) ( , ) T( )k k k Nn nn B B B F( ) ( ,1) ( , ) T( )k k k Ne ee
B F FK N KN F 1KN B F 1K N B F 1K N
• data symbol vector sent by MT k: F( , )(k) ( ,1) T( )k Nkd dd
David Sabater Dinter Research Group for RF Communications 2003-5-26 5
subcarrierwise investigation
F
1
2
N
H 0 0
0 H 0H
0 0 H
B B B
1,1 2,1 ,1
1,2 2,2 ,2
1, 1, ,
K
K
K K K K
H H H
H H HH
H H H
B F F block diagonal matrixK N xKN
•conversion of totalsystem to smaller parallel systems•significant effort reduction in
•linear ZF, MMSE•non linear MLVE
FN
B F F matrixsparseK N xKN
David Sabater Dinter Research Group for RF Communications 2003-5-26 6
F
F
F FF F
2
all data vectors equiprobable and Gauss noise maximum likehood vector estimator (MLVE)
ˆ arg minn
n
K
n nn n
d
d
d e H d
D
optimum non-linear and suboptimum linear detector
F
F F Fˆ arg max |n
n n n
KP
dd d e
D
F F F( ) ( ) ( )ˆ .n n nd D e
F F F F1( ) ( )*T ( ) ( )*Tn n n n
D H H H
• Optimum multiuser detector,
• suboptimum linear detection
• Example: ZF criterion FF F( )( ) ( )
2min
nn n
e H d
David Sabater Dinter Research Group for RF Communications 2003-5-26 7
parallel interference cancellation
1*T
*T
diag
diag
F H H
R H H
*TH
e rF
R
pd
ˆ 1p d-bank
of MF
ˆ pu
iterative MUD
estim
ate
refin
emen
tan
d FE
C d
ecod
ing
• Forward matrix:
• Feedback matrix:
David Sabater Dinter Research Group for RF Communications 2003-5-26 8
no estimate refinement
F, , (non zero) eigenvalues of KN FR
• no estimate refinement,
• PIC convergent if
• convergence value
ˆ ˆd d
1 FR
d FECdemodd
u
d
estimate refinement and FEC decoding
spectral radius
FFR max , , KN
ZFˆ ˆ( )=d d
David Sabater Dinter Research Group for RF Communications 2003-5-26 9
spectral radius example
2,...,8K
P R
divergenceconvergence
• • exp. Channel snapshot
B 8K
R
David Sabater Dinter Research Group for RF Communications 2003-5-26 10
estimate refinement by hard quantization
d FECdemodd
u
d
estimate refinement and FEC decoding
• exploit knowledge of discrete
• quantization of to the modulation constellation
F( , )k nd Dd
F
2ˆ ˆarg min ( )KN
p
d
d d dD
D
David Sabater Dinter Research Group for RF Communications 2003-5-26 11
estimate refinement by soft quantization
d FECdemod u
d
estimate refinement and FEC decoding
2
min Ek
km md d
kmd must satisfy
estim.
2d
2dˆ2
tanh 2
sign
mod
ˆk km mL d d
David Sabater Dinter Research Group for RF Communications 2003-5-26 12
-10 -5 0 5 10 15 20
10-3
10-2
10-1
100
simulation results
F( ) 1n
• • • subc. • exp. channel • no quant.
4K B 4K
10 b 010log / / dBE N
bP
AWGN ZF
PICMF
David Sabater Dinter Research Group for RF Communications 2003-5-26 13
-10 -5 0 5 10 15 20
10-3
10-2
10-1
100
simulation results
F( ) 1n
10 b 010log / / dBE N
bP
• • • subc. • exp. channel• hard quant.
4K B 4K
AWGN
ZF
PICMF
David Sabater Dinter Research Group for RF Communications 2003-5-26 14
-10 -5 0 5 10 15 20
10-3
10-2
10-1
100
simulation results
F( ) 1n
10 b 010log / / dBE N
bP
• • • subc. • exp. channel • soft quant.
4K B 4K
AWGN
ZF
PICMF
David Sabater Dinter Research Group for RF Communications 2003-5-26 15
-10 -5 0 5 10 15 20
10-3
10-2
10-1
100
simulation results
bP
10 b 010log / / dBE N
• • • subc. • exp. channel • no quant.
2K B 4K
F( ) 1n
AWGN PIC(even iterations)
PIC(odd iterations)
ZF
David Sabater Dinter Research Group for RF Communications 2003-5-26 16
PIC with improved estimate refinement
*TH
e rF
1d
bank of MF
iterative MUD
first iterationsecond iterationthird iteration
*TH
e rF
R
2d
-bank of MF
iterative MUD
demod
ˆ 2u
ˆ 1d
*TH
e rF
R
3d
-bank of MF
iterative MUD
demod
ˆ 3u
ˆ 2dhard Q
or soft Q
• principle: input MAI-free at quantization process• starting estimate refinement at the third iteration, errors
introduced by quantization method can be reduced
d
David Sabater Dinter Research Group for RF Communications 2003-5-26 17
-10 -5 0 5 10 15 20
10-3
10-2
10-1
100
simulation results
10 b 010log / / dBE N
bP
• • • subc. • exp. channel • hard quant.• hard mod. quant.
2K B 4K
F( ) 1n
AWGN
MF
ZF
PICPIC mod
David Sabater Dinter Research Group for RF Communications 2003-5-26 18
-10 -5 0 5 10 15 20
10-3
10-2
10-1
100
simulation results
10 b 010log / / dBE N
bP
• • • subc. • exp. Channel• soft quant.• soft mod. quant.
2K B 4K
F( ) 1n
AWGN
MF
ZF
PICPIC mod
David Sabater Dinter Research Group for RF Communications 2003-5-26 19
-10 -5 0 5 10 15 20
10-3
10-2
10-1
100
simulation results
10 b 010log / / dBE N
bP
• • • • exp. Channel• hard quant.• hard mod. quant.
3K B 6K F 32N
AWGN
MF
ZF
PICPIC mod
David Sabater Dinter Research Group for RF Communications 2003-5-26 20
-10 -5 0 5 10 15 20
10-3
10-2
10-1
100
simulation results
10 b 010log / / dBE N
bP
• • • • exp. Channel• soft quant. • soft mod. quant.
3K B 6K F 32N
AWGN
MF
ZF
PIC modPIC
David Sabater Dinter Research Group for RF Communications 2003-5-26 21
conclusions
• PIC is a flexible JD scheme • PIC is not always convergent• performance improvement with modified estimate refinement• more investigation towards PIC necessary
Recommended