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2011 1st semesterommunca on ys ems
Kei Sakaguchi. . . .
May 31, 2011
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nd
Date Text Contents
#7 May 31 A-5 MIMO receiver
une - , ransm e
#9 J une 14 B-9 Adaptive commun. system
#10 J une 21 A-6, B-14 Multi-user MIMO
#11 J une 28 B-15, 16 Distributed MIMO networks
J uly 12 Final Examination
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Derive BER & throughput performances
o as c near non- near rece vers
MIMO receiver architecture
rame sync ronza on c anne es ma on
Linear MIMO detection algorithm Non- near MIMO etecton a gor t m
Measurement experiment
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Question 1escr e genera ze ma rx nverse
of non-square matrix by using SVD.H
Question 2
Prove t at t e o owng equaton o s.HH HHHH
1
Singular Value Decompositionmn
CH mn Non-square matrix:
H mn mm mm
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MIMO detectionx. , , -
OFDM
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anne estmaton
Decision feedback
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Preamble with repetition sequence
Training Data
pL
1
*p
)(
L
Litit yytP0
p
i
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Cyclic delay preamble
Tx #1
Tx #2
Tx #3
Tx #4
Without cyclic delay With cyclic delayNull beamforming effect Transmit delay diversity
)(
)(
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Ex eriment on MIMO S nchronization
Performance improvement owing to transmit & receive diversity
Performance of frame synch.
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h nn l E tim ti n
hAt each receive antenna
1s
Training signals
2h yny s
2sn
T
hs S
tMh
tMs
Training signal
nhSy
tp,,, 21pML
M C
tsssS
Channel estimation erro
pL
Channel estimation
pppp
nShySh
2
pp
22
ce E
1E
1
nShh
HH p1
ppp SSSS
1pp2
pp
2
TrTr SSSS H
H
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tt
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tim l Tr inin nChannel estimation error
1h1s
Training signals
1ppt
2
ce Tr
SSHM
2h y
2s
pS
Optimal training sequence
1Tr
SSH is minimal
tMh
tMs
t
t
p
pp M
H
M
PL ISS whenPL
M
p
2t2
ce
pL
Receive signal with channel estimation error
NHH MH
22
tE NN Effective noise
nsHnsNsHnHsy ~ ce
PLp
r
1~~E t2 MH M
Inn
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p
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Schemes Performance Complexity
LineaZF
Low Low
VBLASTHybrid
QRM-MLDMedium Medium
Non-linear MLD High High
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1st stream
rm
1111
Wys
rrtt mmmm yww 1Mt-th stream
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Interference Cancellation Detection
(Zero Forcing)ece ve s gna
nHsy
0dB 0dB -25dB 0dB
HH HHHHW 1
ZF weight
Estimated signal
~
Effective SNR for i-th stream
2~~E
HHnn
HH
Diversity orderZF
P
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12
ii
H
tM HH
trd
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Minimum Mean S uare Error Detection
Cost function0dB 0dB -25dB 0dB
2E WysW J
0
WJ
H
M
H MHIHHW
12
t
t
Effective SNR for i-th stream
11
2
MMSE
t
M
H
i
PIHH
Diversity order
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t iitr
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No diversity gain if tr MM
No performance gain of MIMO (moreover noise enhancement)
Noise
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High performance due to multiplexing gain at high SNR region
Multi lexingain
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Diversity order increases stage by stage
t
stageMM tr
vers y or e
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Diversity gain owing to successive interference cancellation
Diversity gain
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Diversity gain improves the throughput performance at lower SNR region
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Maximum likelihood detection
~
~minarg sHyss
2 Tx with QPSK signaling
Pair wise error probability
2
2)(
erfc1
)(ki
kipssH
ss
r2M
ikdP
1h 2Diversity order
t
24 M
Computational cost
rd
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t
ary combinations on r receiver branches
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-
Full receive diversity due to MLD at all receive branches
Full receive diversity
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-Maximal available throughput among all MIMO detection schemes
s compu a ona compex y s a mos pro e
Full receive diversity
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-QRM-MLD approaches the performance of MLD asymptotically
-
tmsrr 1111
ttt mmm sr00
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pper ranguar ecompos on:
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QRM-MLD achieves full receive diversity as with MLD
SNR penalty
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In IID, performance of VBLAST & QRM-MLD are almost the same
SNR penalty
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Com arison of MIMO Detection Schemes
Multi lexin ain Diversit ain
MMSE
VBLAST sta e
1tr MMtM
MLD
QRM-MLD tM rM
Complexity
MMSE
VBLAST
)((INV) rtOLO )(2(INV)
rttMMOLOM
MLD
QRM-MLD )2/)1(()QRD( ttrt MMMMMOLO)( taryrtO
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:L Number of symbols
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Measurement conditionMIMO structure 4 (Tx) x 4 (Rx)
linear array
MIMO receive scheme ZF, MMSE, VBLAST, MLD
, , ,
Frame structure IEEE802.11a based
Packet length 480 bits
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Slight spatial correlation will affect MIMO performance
Pathloss distribution Spatial correlation
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BER performance agrees with that in Rayleigh environment
Degradation of throughput performance is due toimperfection of frequency characteristics in RF transceiver
BER performance Throughput performance
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Performance de radation of BER is due to s atial correlation
RF impairment & spatial correlation degrades throughput performance
BER performance Throughput performance
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MIMO receiver architecture
ransmt rece ve vers ty on rame sync ronzaton
Orthogonal preamble sequences for MISO channel estimation
MIMO detection algorithm
Multi lexin ain to im rove throu h ut erformance
Diversity gain to improve BER performance Tradeoff between complexity & performance (diversity order)
near sc emes ,Non-linear schemes (VBLAST, MLD, QRM-MLD)
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