Noise Cancelation for MIMO System

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Noise Cancelation for MIMO System
Prepared by Heba Hamad Rawia Zaid
Rua Zaid Supervisor
Dr.Yousef Dama
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Outline

• Aim and objectives

• Interference Cancellation Techniques

• SIC

• Optimal ordering with SIC

• ML
• Cancel the effect of the transmitted power using
  a feedback signal process
• 21 MIMO Using STC
• HIPERLAN/2

• Simulation and Results

• SWOT

• Recommendation for Future Works

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Aims and Objectives
Present a method to cancel the interference that
is caused by the transmitting antennas closely
spaced to the receive antennas of the MIMO
system.
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Interference Cancellation Techniques
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Zero Forcing
Generate random binary sequence of 1's and -1's.
Group them into pair of two symbols and send two
symbols in one time slot
Multiply the symbols with the channel and then
add white Gaussian noise.
Equalize the received symbols with Zero Forcing
criterion
ZF-SIC with optimal ordering
Type of method
ZF-SIC
Take the symbol from the second spatial
dimension, subtract from the received symbol
Find the power of received symbol from both the
spatial dimensions
Take the symbol having higher power, subtract
from the received symbol
Perform Maximal Ratio Combining for equalizing
the new received symbol
Perform hard decision decoding and count the bit
errors
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MMSE
Generate random binary sequence of 1's and -1's.
Group them into pair of two symbols and send two
symbols in one time slot
Multiply the symbols with the channel that add
with and then add white Gaussian noise.
Equalize the received symbols with MMSE criterion
MMSE-SIC with optimal ordering
Type of method
MMSE-SIC
Take the symbol from the second spatial
dimension, subtract from the received symbol
Find the power of received symbol from both the
spatial dimensions
Take the symbol having higher power, subtract
from the received symbol
Perform Maximal Ratio Combining for equalizing
the new received symbol
Perform hard decision decoding and count the bit
errors
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Noise
ZF equalization
MMSE equalization
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Maximum Likelihood
Generate random binary sequence of 1's and -1's.
Group them into pair of two symbols and send two
symbols in one time slot
Multiply the symbols with the channel and then
add white Gaussian noise.
Find the minimum among the four possible transmit
symbol combinations
Based on the minimum chose the estimate of the
transmit symbol
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• Cancel the effect of the transmitted power using
  a feedback signal process

• 21 MIMO Using STC

• HIPERLAN/2

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21 MIMO Using STC
Get the channel information of the users
Modulating the data of users and sending it by
using Alamouti method
Multiplying the send symbols by the channel
information
Feedback signal
Receiving the signal of both users during two
time slots according to Alamouti
Receiving the feedback from user 1
Subtracting the feedback signal from the receive
signal
Decoding the new signal to get the symbols of
user 2
End
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HIPERLAN/2 System
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Simulation and Results
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ZF _SIC with MMSE_SIC
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ZF _SIC ,MMSE_SIC with optimal ordering
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Maximum likelihood
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Cancel the effect of the transmitted power using
a feedback signal process

• 21 MIMO Using STC
• BER versus SNR when the transmitted power is
  changing

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Cont

• BER versus SNR when the received power is
  changing

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Cont

• BER versus SNR when the feedback mismatch is
  changing

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• HIPERLAN/2 HIPERLAN/2 using16-QAM with different
  distributions of antennas

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Cont

• HIPERLAN/2 performance when nTx2 and nRx1 for
  different modulation schemes

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Cont

• BER versus SNR when the transmitted power is
  changing

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Cont

• BER versus SNR when the received power is
  changing

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Cont

• BER versus SNR when the feedback mismatch is
  changing

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Cont

• BER versus SNR with and without noise
  cancelation
• BER versus SNR

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w s
T O

• Increasing the capacity.
• Enhancing the reliability.
• Improving the signal-to-noise ratio .
• Increasing the data rate of the wireless systems.

• The proposed methodology has not been implemented
  in reality.

• WiFi 802.11n
• WiMAX
• 3G
• 4G

• In practice its difficult to estimate the
  response of the channel, but in our project the
  channel is assumed to be known.

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Recommendation for Future Works

• The suggested methodology can be implemented in
  reality then measuring the results and comparing
  it with the simulated results.
• Studying the performance of the system with other
  types of channels and other type of diversity
  code.
• studying the other types of antennas
  distributions in both transmitting and receiving
  sides.

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