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Kamran Faisal
Shahid Iqbal
Haider Ali
▸ Overview
▸ Why Equalization?
▸ What is Equalization?
▸ Equalization Types
▸ Equalization Algorithms
▸ Conclusion
2
Contents
Include
“In the middle of every difficulty lies
opportunity”.
“A person who never made a mistake never
tried anything new”.
“You never fail until you stop trying”.
Albert Einstein
3
Overview!
4
Why Equalization?
5
Why
Equalization?
▸ Growth in communication services
▹ Satellite and fiber optics.
▹ High bandwidth
▹ Variety of data
▸ Require transmission technique over communication
channels.
6
What is Equalization!
 Process of adjusting the balancce
between frequency components.
 Mitigate the effects of
 ISI (Inter Symbol Interference)
 Co-Channel Intrference
 Adjacent Channel Interference
 MultiPath Propagtion
7
What is Equalization!
 Used to remove ISI and noise effects
from the channel.
8
What is ISI?
9
What is ISI?
▸ Form of distortion of a signal
▹ One symbol interference with subsequent signals.
▸ Causes the errors at decision making device.
▸ Arises when data transmitted through the channel is
dispersive
▹ Received pulse is affected by the adjacent pulses
10
What is CCI?
11
What is
CCI?
▸ Occurs in cellular radio system
▸ Caused by
▹ Adverse Weather Conditions
▹ Poor Frequency planning
▹ Daytime vs Nighttime
12
What is ACI?
13
What is
ACI?
▸ Occurs in cellular radio system
▸ Caused by
▹ Extraneous power
▹ Inadequate filtering
▹ Improper tuning
14
Equalization Types
15
Equalization
Types
▸ Linear Equalizer
▹ Process the incoming signal with a linear filter
▸ Decision Feedback Equalizer
▹ Non-Linear equalizer that uses the previous detector decision to eliminate the
ISI on modulated pulses .
▸ Blind Equalizer
▹ Estimates the transmitted signal without knowledge of the channel statistics,
using only knowledge of the transmitted signal’s statistics.
16
Equalization Algorithms
17
Equalization
Algorithms
▸ LMS (Least Mean Square)
▹ Read the data signal.
▹ Calculate length of the data signal.
▹ Generate random noise and add it to data signal.
▹ Apply LMS Algorithm on noisy data signal.
▹ Filter output is y(n) = w(n) * x(n) where w(n) weight vector and x(n) is noise
data signal.
▹ Error e(n) = d(n) – y(n) Where d(n) is part of original data signal.
▹ Filter coefficient updating: w(n + 1) = w(n) + µx(n) e * (n)
▹ Update Filter Coefficient and minimize the error.
18
LMS Algorithm
Pros & Cons
19
Advantage
 Simplicity of
implementation.
 Not neglecting the
noise like Zero
Forcing Equalizer.
 Stable and Robust
performance against
different signal
conditions.
LMS
Algorithm
Pros and
Cons
Disadvantage
 Slow Convergence.
 Decreasing the
communication BW.
20
Conclusion
21
Conclusion
▸ Mandatory process for almost any modern digital
communication system.
▸ There is a variety of strategies
▹ Linear, Blind, etc.
▸ It is not a closed field, and it is subject to ongoing
research and improvements.
22
23
THANKS!
Any questions?
You can find me at
▸ @username
▸ user@mail.me

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Equalization (Technique on Receiver Side to remove Interferences)

  • 2. ▸ Overview ▸ Why Equalization? ▸ What is Equalization? ▸ Equalization Types ▸ Equalization Algorithms ▸ Conclusion 2 Contents Include
  • 3. “In the middle of every difficulty lies opportunity”. “A person who never made a mistake never tried anything new”. “You never fail until you stop trying”. Albert Einstein 3
  • 6. Why Equalization? ▸ Growth in communication services ▹ Satellite and fiber optics. ▹ High bandwidth ▹ Variety of data ▸ Require transmission technique over communication channels. 6
  • 7. What is Equalization!  Process of adjusting the balancce between frequency components.  Mitigate the effects of  ISI (Inter Symbol Interference)  Co-Channel Intrference  Adjacent Channel Interference  MultiPath Propagtion 7
  • 8. What is Equalization!  Used to remove ISI and noise effects from the channel. 8
  • 10. What is ISI? ▸ Form of distortion of a signal ▹ One symbol interference with subsequent signals. ▸ Causes the errors at decision making device. ▸ Arises when data transmitted through the channel is dispersive ▹ Received pulse is affected by the adjacent pulses 10
  • 12. What is CCI? ▸ Occurs in cellular radio system ▸ Caused by ▹ Adverse Weather Conditions ▹ Poor Frequency planning ▹ Daytime vs Nighttime 12
  • 14. What is ACI? ▸ Occurs in cellular radio system ▸ Caused by ▹ Extraneous power ▹ Inadequate filtering ▹ Improper tuning 14
  • 16. Equalization Types ▸ Linear Equalizer ▹ Process the incoming signal with a linear filter ▸ Decision Feedback Equalizer ▹ Non-Linear equalizer that uses the previous detector decision to eliminate the ISI on modulated pulses . ▸ Blind Equalizer ▹ Estimates the transmitted signal without knowledge of the channel statistics, using only knowledge of the transmitted signal’s statistics. 16
  • 18. Equalization Algorithms ▸ LMS (Least Mean Square) ▹ Read the data signal. ▹ Calculate length of the data signal. ▹ Generate random noise and add it to data signal. ▹ Apply LMS Algorithm on noisy data signal. ▹ Filter output is y(n) = w(n) * x(n) where w(n) weight vector and x(n) is noise data signal. ▹ Error e(n) = d(n) – y(n) Where d(n) is part of original data signal. ▹ Filter coefficient updating: w(n + 1) = w(n) + µx(n) e * (n) ▹ Update Filter Coefficient and minimize the error. 18
  • 20. Advantage  Simplicity of implementation.  Not neglecting the noise like Zero Forcing Equalizer.  Stable and Robust performance against different signal conditions. LMS Algorithm Pros and Cons Disadvantage  Slow Convergence.  Decreasing the communication BW. 20
  • 22. Conclusion ▸ Mandatory process for almost any modern digital communication system. ▸ There is a variety of strategies ▹ Linear, Blind, etc. ▸ It is not a closed field, and it is subject to ongoing research and improvements. 22
  • 23. 23 THANKS! Any questions? You can find me at ▸ @username ▸ user@mail.me

Editor's Notes

  1. Equalization is the process of adjusting the balance between frequency components. It is use to mitigate the effect of ISI (inter symbol interference), Co-Channel Interference and Adjacent Channel Interference that occurred in the signal from input to output.
  2. The growth in communication services during the past five decades has been phenomenal. Satellite and fibre opticnetworks provide high-speed communication services around the world. Currently, most of the wired line communicationsystems are being replaced by fibre optic cables which provide extremely high bandwidth and make possible thetransmission of a wide variety of information sources, including voice, data, and video. With the unimaginable developmentof Internet technologies, efficient high-speed data transmission techniques over communication channels have become anecessity of the day.
  3. Equalization is the process of adjusting the balance between frequency components. It is use to mitigate the effect of ISI (inter symbol interference), Co-Channel Interference and Adjacent Channel Interference that occurred in the signal from input to output.
  4. Equalization is the process of adjusting the balance between frequency components. It is use to mitigate the effect of ISI (inter symbol interference), Co-Channel Interference and Adjacent Channel Interference that occurred in the signal from input to output.
  5. It is a form of distortion of a signal in which one symbol interference with subsequent signals. It causes the errors at decision making device. ISI arrises when the data is transmitted through the channel is dispersive in which each Received pulse is affected by the adjacent pulses and due to which interference occurs in the transmitted signals. One major cause of distortion is Inter Symbol Interference (ISI). In digital communication, thetransmitted signals are generally in the form of multilevel rectangular pulses. The absolute bandwidth of multilevelrectangular pulses is infinity. If these pulses passes through a band limited communication channel, they will spread in timeand the pulse for each symbol maybe smeared into adjacent time slot and interfere with the adjacent symbol. This is referredas inter symbol interference (ISI). 
  6. Adverse weather conditions: During periods of uniquely high-pressure weather, VHF signals which would normally exit through the atmosphere can instead be reflected by the troposphere. Thistropospheric ducting will cause the signal to travel much further than intended; often causing interference to local transmitters in the areas affected by the increased range of the distant transmitter. Poor frequency planning: Poor planning of frequencies by broadcasters can cause CCI, although this is rare. A very localised example is Listowel in the south-west of Ireland. Daytime vs Nighttime: In the medium frequency portion of the radio spectrum where most AM broadcasting is allocated, signals propagate full-time via groundwave and, at nighttime, via skywaveas well. This means that during the nighttime hours, co-channel interference exists on many AM radio frequencies due to themedium waves reflecting off the ionosphere and being bounced back down to earth.
  7. Adjacent-channel interference (ACI) is interference caused by extraneous power from a signal in an adjacent channel. ACI may be caused by inadequate filtering (such as incomplete filtering of unwantedmodulation products in FM systems), improper tuning or poor frequency control (in the reference channel, the interfering channel or both).
  8. LINEAR EQUALIZER:- Aims at minimizing the difference between the transmitted data and the Equalizer output. DECISION FEEDBACK EQUALIZER:- It is a non linear equalizer that uses the previous detector decision to eliminate the ISI(Inter Symbol Interference) on pulses that are currently being modulated. Blind equalizer: estimates the transmitted signal without knowledge of the channel statistics, using only knowledge of the transmitted signal's statistics.