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New Approach of Implementing STBC Technique for MIMO system and MIMO-OFDM Channel Estimation. Prepared by: Duaa Waleed Rawya Deriah Walaa Hammoudeh Supervisor: Dr. Yousef Dama. Outline. OFDM Channel estimation LS and MMSE MIMO-OFDM channel estimation - PowerPoint PPT Presentation
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New Approach of Implementing STBC Technique for MIMO
system and MIMO-OFDM Channel
Estimation
Prepared by: Duaa Waleed Rawya Deriah Walaa Hammoudeh
Supervisor: Dr. Yousef Dama 1
2
Outline
• OFDM Channel estimation– LS and MMSE
• MIMO-OFDM channel estimation
– Weiner and Orthogonal Training Sequence
• QO-STBC and DHSTBC over OFDM for four, eight and sixteen transmitter antenna
3
Channel Estimation • It provides information about distortion of the
transmission signal when it propagates through the channel.
Types of Channel Estimation
Non-Data-Aided Data-Aided
4
OFDM channel estimation
5
Channel Estimation
Find
LS Estimator
MMSE Estimator
Find the estimated channel for the pilots
Applied FFT for the previous step to fined
Find the estimated data by divide the received ones on
Find the noise variance
Find auto correlation for
Find cross correlation
Find the estimated channel for the pilots
To be Count.
�̂�=𝑦 /𝐻𝑒𝑠𝑡
6
𝑀𝑆𝐸=|𝐻 𝑒𝑠𝑡
𝐻 |2Find the estimated data by divide the
received ones on
𝑀𝑆𝐸=||𝐻|−|h𝑒𝑠𝑡𝑝𝑖𝑙𝑜𝑡||𝐻| |
2
End
7
MIMO-OFDM Channel estimation
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1-D and 2-D channel estimation.
9
Methods for Channel Estimation In MIMO-OFDM
Channel Estimation
Wiener channel estimation
Orthogonal training sequence
10
Wiener
Stack the pilots indices down the frequency index first then across time
index
Generate some random data and pilots
FFT for the Channel Gain
Add noise to the received symbols
Initial channel estimate at the pilot symbol
Find the auto correlation matrix
Find the correlation matrix
Calculate the channel estimate at the data location
Calculate wiener filter coefficients
The 2-D Wiener filter coefficients are given by
11
Orthogonal training sequence
Generate the data, then split the data into two antennas
This method is applied on
MIMO-OFDM system
Generate orthogonal training sequence, sort them in odd indices, and in even
indices put the data
OFDM modulation
Interpolation to estimate the channel at data indices
Estimate channel at each orthogonal training symbol indices
Receive data and orthogonal training sequence at receiver side
OFDM Demodulation
12
Result of Channel Estimation
13
5 10 15 20 2510
-4
10-3
10-2
10-1
SNR in DB
Mean S
quare
d E
rror
SNR Vs MSE For an OFDM system with MMSE/ZF
MMSE
LSZF
OFDM Channel Estimation
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0 5 10 15 20 2510
-4
10-3
10-2
10-1
100
101
SNR
Bit
Err
or R
ate
BER Vs. SNR using ZF and Wiener estimation methods for MIMO-OFDM system
wiener filter
ZF
Wiener Filter Channel Estimation
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0 20 40 60 80 100 120 1400
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
Sub-carrier Index,k
|H11
[k]|
Absolute value of the sub-carrier channel:antenna 1 receiver 1
Actual Channel
Estimated Channel
0 20 40 60 80 100 120 1400.04
0.06
0.08
0.1
0.12
0.14
0.16
0.18
0.2
Sub-carrier Index,k
|H12
[k]|
Absolute value of the sub-carrier channel:antenna 1 receiver 2
Actual Channel
Estimated Channel
Orthogonal Training SequenceChannel Estimation
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0 20 40 60 80 100 120 1400
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
Sub-carrier Index,k
|H21
[k]|
Absolute value of the sub-carrier channel:antenna 2 receiver 1
Actual Channel
Estimated Channel
0 20 40 60 80 100 120 1400.06
0.08
0.1
0.12
0.14
0.16
0.18
0.2
0.22
Sub-carrier Index,k
|H22
[k]|
Absolute value of the sub-carrier channel:antenna 2 receiver 2
Actual Channel
Estimated Channel
Orthogonal Training Sequence
Channel Estimation
17
QO-STBC and DHSTBC
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QO-STBC over OFDM for 4,8and 16 transmitter antennas
• The encoding matrix for two (2 × 2) Alamouti codes are
to form
X 12=[ x1
− x2∗
x2
x1∗ ]
X ABBA=[ X12
X 34
X 34
X12 ]
19
• The Equivalent Virtual Channel Matrix (EVCM) can be written as:
• MRC can be done by multiplying the received vector Y with thus:
where
QO-STBC over OFDM, Cont…
20
• To diagonalize the detection matrix for QO-STBC scheme for four transmitter antennas eigenvalue eigenfunction is used
QO-STBC over OFDM, Cont…
D 4QO−STBC=[α+β000
0α+ β
00
00α−β
0
000
α− β]
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• A new channel matrix can be defined as:
QO-STBC over OFDM, Cont…
H 4QO−STBC=H vV 4QO−STBC
H 4QO−STBC=[ h1+h3
h2∗+h4
∗
h1+h3
h2∗+h4
∗
h2+h4
−h1∗−h3
∗
h2+h4
−h1∗−h3
∗
h3−h1
h4∗−h2
∗
h1−h3
h2∗−h4
∗
h4−h2
h1∗−h3
∗
h2−h4
h3∗−h1
∗ ]
22
DHSTBC over OFDM for 4,8 and 16 Transmit Antennas • The transmitted symbols are sorted to form a cyclic
matrices which are , and
• The Hadamard matix of order four
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• The resultant matrix is a DHSTBC over OFDM and hence, the overall expression is given by
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Result for QOSTBC and DHSTBC over OFDM
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0 5 10 15 20 25 30
10-2
10-1
100
SNR-dB
BE
RBER Vs. SNR for MISO-OFDM 16Tx x 1Rx and 8Tx x 1Rx and 4Tx x 1Rx QOSTBC
4Tx x 1Rx
8Tx x 1Rx16Tx x 1Rx
QO-STBC for 4,8 and 16 transmitter antennas
26
0 5 10 15 20 25 30 3510
-3
10-2
10-1
100
SNR-dB
BE
RBER Vs. SNR for MISO-OFDM 16Tx x 1Rx and 8Tx x 1Rx and 4Tx x 1Rx DHSTBC
4Tx x 1Rx
8Tx x 1Rx16Tx x 1Rx
DHSTBC for 4,8 and 16 transmitter antennas
27
0 5 10 15 20 2510
-3
10-2
10-1
100
SNR-dB
BER
BER Vs. SNR for MISO-OFDM 4Tx x 1Rx DHSTBC , Real STBC and QOSTBC
DHSTBC 4Tx x1Rx
Real STBC 4Tx x 1RxQOSTBC 4Tx x 1Rx
0 5 10 15 20 25 30 3510
-3
10-2
10-1
100
SNR-dB
BER
BER Vs. SNR for MISO-OFDM 8Tx x 1Rx DHSTBC , Real STBC and QOSTBC
DHSTBC 8Tx x1Rx
Real STBC 8Tx x 1RxQOSTBC 8Tx x 1Rx
0 5 10 15 20 25 3010
-3
10-2
10-1
100
SNR-dB
BER
BER Vs. SNR for MISO-OFDM 16Tx x 1Rx DHSTBC , Real STBC and QOSTBC
DHSTBC 16Tx x1Rx
Real STBC 16Tx x 1RxQOSTBC 16Tx x 1Rx
DHSTBC , QO-STBC and Real STBC Comparison
28
0 5 10 15 20 25 30 35 4010
-3
10-2
10-1
100
BER Vs. SNR for MISO-OFDM 4Tx x 1Rx QOSTBC
SNR-dB
BER
BPSK
QPSK
16QAM32 QAM
64 QAM
0 5 10 15 20 25 30 3510
-3
10-2
10-1
100
BER Vs. SNR for MISO-OFDM 8Tx x 1Rx QOSTBC
SNR-dB
BER
BPSK
QPSK
16QAM32 QAM
64 QAM
0 5 10 15 20 25 3010
-3
10-2
10-1
100
BER Vs. SNR for MISO-OFDM 16Tx x 1Rx QOSTBC
SNR-dB
BER
BPSK
QPSK
16QAM32 QAM
64 QAM
QO-STBC with different modulation scheme
29
0 5 10 15 20 25 30 35 4010
-3
10-2
10-1
100
BER Vs. SNR for MISO-OFDM 4Tx x 1Rx DHSTBC
SNR-dB
BER
BPSK
QPSK
16QAM32 QAM
64 QAM
0 5 10 15 20 25 3010
-3
10-2
10-1
100
BER Vs. SNR for MISO-OFDM 8Tx x 1Rx DHSTBC
SNR-dB
BER
BPSK
QPSK
16QAM32 QAM
64 QAM
0 5 10 15 20 25 30 35 40
10-2
10-1
100
BER Vs. SNR for MISO-OFDM 16Tx x 1Rx DHSTBC
SNR-dB
BER
BPSK
QPSK
16QAM32 QAM
64 QAM
DHSTBC with different modulation scheme
30
w s
T o Modernity of this topic in wireless communication world
Blind channel estimation was ambiguous to work on
Increasing the number of antennas
Computational complexity
The use of channel estimation is more practical than assumes the channel response known at the
receiver
New approaches of implementing STBC technique for 8 and 16
transmit antenna have been done for the first time
Improve the Quality of Service
Used in most of the wireless communication systems
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Recommendation for Future Works
• Implement a noise cancellation method as a feature inside the presented techniques in this project
• Move toward new methods which guarantee more error reduction
• Go through blind and semi-blind techniques
32
Questions are Guaranteed in Life Answers aren't
33