New Approach of Implementing STBC Technique for MIMO system and MIMO-OFDM Channel Estimation

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

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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

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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

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OFDM channel estimation

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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

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𝑀𝑆𝐸=|𝐻 𝑒𝑠𝑡

𝐻 |2Find the estimated data by divide the

received ones on

𝑀𝑆𝐸=||𝐻|−|h𝑒𝑠𝑡𝑝𝑖𝑙𝑜𝑡||𝐻| |

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End

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MIMO-OFDM Channel estimation

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1-D and 2-D channel estimation.

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Methods for Channel Estimation In MIMO-OFDM

Channel Estimation

Wiener channel estimation

Orthogonal training sequence

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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

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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

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Result of Channel Estimation

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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

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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 ]

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• 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…

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• 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

∗ ]

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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

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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

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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

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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

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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

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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

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Questions are Guaranteed in Life Answers aren't

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