SlideShare uma empresa Scribd logo
1 de 26
DATA COMMUNICATIONS &
          NETWORKING
           LECTURE-08

         Course Instructor : Sehrish Rafiq
         Department Of Computer Science
                  University Of Peshawar
LECTURE OVERVIEW
   Conversion methods
   Line coding
   Characteristics of line coding
   Signal level & Data Level
   Pulse Rate & Bit Rate
   DC Component
   Self Synchronization
   Line coding Schemes
   Unipolar
   Polar
   NRZ
   RZ
   Manchester and Differential Manchester
   Bipolar
CONVERSION METHODS OR ENCODING &
          MODULATION
   How information is transformed depends on its original format and
    on the format used by the communication hardware.
   Conversion methods
   Digital-to-digital conversion or Line coding
   Analog-to-digital conversion or Sampling
   Digital -to- analog modulation
   Analog -to -analog modulation
LINE CODING
 Line coding is the process of converting binary data, a
  sequence of bits to a digital signal.
 In other words, line coding converts a sequence of bits to
  a digital signal.
 At the sender, digital data are encoded in to digital
  signal.
 At the receiver, the digital data are recreated by decoding
  the digital signal back in to digital data.
LINE CODING & DECODING
SIGNAL LEVEL & DATA LEVEL
   The number of values allowed in a particular signal is known
    as the number of signal levels.
   The number of values used to represent data is known as the
    number of data levels.
DATA ELEMENT VERSUS SIGNAL
             ELEMENT
 A data Element is the smallest entity that can
  represent a piece of information this is the bit.
 A signal element is the shortest unit time wise of
  a digital signal.
 In other words data elements are what we need
  to send.
 Signal elements are what we can send.

 Data elements are being carried, signal elements
  are the carriers.
 r is defined as the ratio which is the number of
  data elements carried by each signal element.
DATA ELEMENT VERSUS SIGNAL
         ELEMENT
DATA RATE VERSUS SIGNAL
             RATE
 The data rate is defined as the number of data elements
  sent in one second usually expressed in bps.
 Data rate is also called Bit rate.

 The signal rate is defined as the number of signal
  elements sent in one second.
 A signal rate is also called a pulse rate.

 A signal element is also called a symbol or pulse.

 One pulse or signal element can carry more than one bit.

 When a pulse or signal element carry only one bit then
  the bit rate and pulse rate/signal rate are same.
 The signal rate is sometimes called modulation rate or
  baud rate.
FORMULA FOR BIT RATE



Bit Rate=Pulse Rate x log2 L
Where L is the number of data Levels.
Example 1

A signal has two data levels with a pulse duration of 1
ms. We calculate the pulse rate and bit rate as follows:

Solution
Pulse Rate = 1/ 10-3= 1000 pulses/s
Bit Rate = Pulse Rate x log2 L = 1000 x log2 2 = 1000 bps
Example 2
A signal has four data levels with a pulse duration of 1
ms. We calculate the pulse rate and bit rate as follows:
 Solution
Pulse Rate = = 1000 pulses/s
Bit Rate = Pulse Rate x log2 L = 1000 x log2 4 = 2000 bps
DC COMPONENT
 When the voltage level is constant for a while very low
  frequencies are often created.
 These frequencies around zero are called DC or Direct
  Current components.
 This component is undesirable for two reasons.

 First if a signal has to pass through a system (e.g. a
    telephone line which does not allow frequencies below 200 Hz)
  which does not allow low frequencies to pass the signal
  is distorted and may create errors in the output.
 Second this component is extra energy residing on the
  line and is useless.
DC COMPONENT
SELF-SYNCHRONIZATION
 To correctly interpret the signals received from the
  sender, the receiver’s bit intervals must correspond
  exactly to the sender’s bit intervals.
 If the receiver’s clock is faster or slower, the bit intervals
  are not matched and the receiver might interpret the
  signals differently then the sender intended.
 A self synchronizing digital signal includes timing
  information in the data being transmitted.
 This can be achieved if there are transitions in the signal
  that alert the receiver to the beginning, middle or end of
  the pulse.
 If the receiver clock is out of synchronization, these
  alerting points can reset the clock.
LACK OF SYNCHRONIZATION
Example 3
In a digital transmission, the receiver clock is 0.1 percent
faster than the sender clock. How many extra bits per
second does the receiver receive if the data rate is 1
Kbps? How many if the data rate is 1 Mbps?

Solution
At 1 Kbps:
1000 bits sent 1001 bits received1 extra bps
At 1 Mbps:
1,000,000 bits sent 1,001,000 bits received1000 extra bps
LINE CODING SCHEMES
UNIPOLAR SCHEME
 Digital transmission systems work by sending voltage
  pulses along a medium link, usually a wire or cable.
 In many types of encoding, one voltage level stands for
  binary 0,another level stands for binary 1.
 The polarity of a pulse refers to whether it is positive or
  negative.
 Unipolar encoding is so named because it uses only one
  polarity.
 The polarity is assigned to one of the two binary states,
  usually the 1.
 The other state usually 0 is represented by zero voltage.
UNIPOLAR SCHEME
PROBLEMS USING UNI POLAR
             SCHEME
   DC Component
   The average amplitude of a unipolar encoded signal is non
    zero.
   This creates a DC component.

   Lack of synchronization
   If the data contain a long sequence of 0’s and 1’s there is no
    change in the signal during this duration that can alert the
    receiver to potential synchronization problems.
POLAR ENCODING SCHEMES
 Polar encoding uses two voltage levels, one positive and
  one negative.
 By using the two Levels, in most polar encoding
  methods the average voltage level on the line is reduced
  and the dc component problem seen in unipolar encoding
  is alleviated.
NRZ(NON RETURN TO ZERO)
           SCHEMES
 In NRZ encoding the value of the signal is always
  positive or negative.
 Two popular forms of NRZ are:

 NRZ-L(Non Return to Zero-Level)

 In NRZ-L the level of the signal depends on the type of
  bit that it represent.
 The positive voltage usually means a 0 while a negative
  voltage means the bit is a 1.
 Problem: Long stream of 0’s or 1’s may create
  synchronization problem.
NRZ(NON RETURN TO ZERO)
              SCHEMES
   NRZ-I(NRZ-Invert)
   In NRZ-I ,an inversion of the voltage level represents a 1 bit.
   It is the transition between a positive and negative voltage, not the
    voltage itself, that represents a 1 bit.
   A 0 bit is represented by no change.
   NRZ-I is superior to NRZ-L due to the synchronization provided by
    the signal change each time a 1 bit is encountered.
   The existence of 1’s in the data stream allows the receiver to
    synchronize its timer to the actual arrival of transmission.
   A string of 0’s can still cause problems but because they are not as
    Likely,they are less of a problem.
NRZ(NON RETURN TO ZERO)
       SCHEMES
THANKS!!   !

Mais conteúdo relacionado

Mais procurados

Packet switching
Packet switchingPacket switching
Packet switching
asimnawaz54
 

Mais procurados (20)

Digital modulation techniques sys
Digital modulation techniques sysDigital modulation techniques sys
Digital modulation techniques sys
 
Delta Modulation
Delta ModulationDelta Modulation
Delta Modulation
 
EEP306: Line coding
EEP306: Line codingEEP306: Line coding
EEP306: Line coding
 
Error control coding techniques
Error control coding techniquesError control coding techniques
Error control coding techniques
 
Unipolar Encoding Techniques: NRZ & RZ
Unipolar Encoding Techniques: NRZ & RZUnipolar Encoding Techniques: NRZ & RZ
Unipolar Encoding Techniques: NRZ & RZ
 
Digital communication system
Digital communication systemDigital communication system
Digital communication system
 
Adaptive equalization
Adaptive equalizationAdaptive equalization
Adaptive equalization
 
Pn sequence
Pn sequencePn sequence
Pn sequence
 
Physical Layer Numericals - Data Communication & Networking
Physical Layer  Numericals - Data Communication & NetworkingPhysical Layer  Numericals - Data Communication & Networking
Physical Layer Numericals - Data Communication & Networking
 
7. data link layer error detection and correction codes - parity and checksum
7. data link layer   error detection and correction codes - parity and checksum7. data link layer   error detection and correction codes - parity and checksum
7. data link layer error detection and correction codes - parity and checksum
 
How PSTN phone works?
How PSTN phone works?How PSTN phone works?
How PSTN phone works?
 
Packet switching
Packet switchingPacket switching
Packet switching
 
signal encoding techniques
signal encoding techniquessignal encoding techniques
signal encoding techniques
 
Number system in Digital Electronics
Number system in Digital ElectronicsNumber system in Digital Electronics
Number system in Digital Electronics
 
Error detection & correction codes
Error detection & correction codesError detection & correction codes
Error detection & correction codes
 
MINIMUM SHIFT KEYING(MSK)
MINIMUM SHIFT KEYING(MSK)MINIMUM SHIFT KEYING(MSK)
MINIMUM SHIFT KEYING(MSK)
 
Data Communication & Computer Networks : Serial and parellel transmission
Data Communication & Computer Networks : Serial and parellel transmissionData Communication & Computer Networks : Serial and parellel transmission
Data Communication & Computer Networks : Serial and parellel transmission
 
TWO STAGE NETWORKS
TWO STAGE NETWORKSTWO STAGE NETWORKS
TWO STAGE NETWORKS
 
Floating point representation
Floating point representationFloating point representation
Floating point representation
 
Floating point arithmetic operations (1)
Floating point arithmetic operations (1)Floating point arithmetic operations (1)
Floating point arithmetic operations (1)
 

Destaque

3.3. line coding (encoding)
3.3. line coding (encoding)3.3. line coding (encoding)
3.3. line coding (encoding)
trimba
 
Digital data transmission,line coding and pulse shaping
Digital data transmission,line coding and pulse shapingDigital data transmission,line coding and pulse shaping
Digital data transmission,line coding and pulse shaping
Aayush Kumar
 

Destaque (20)

05 signal encoding
05 signal encoding05 signal encoding
05 signal encoding
 
Line coding
Line codingLine coding
Line coding
 
Lecture 05
Lecture 05Lecture 05
Lecture 05
 
Lecture 09
Lecture 09Lecture 09
Lecture 09
 
Line codes
Line codesLine codes
Line codes
 
Line coding
Line codingLine coding
Line coding
 
Chapter 4 - Digital Transmission
Chapter 4 - Digital TransmissionChapter 4 - Digital Transmission
Chapter 4 - Digital Transmission
 
Chap 5
Chap 5Chap 5
Chap 5
 
Lecture 02
Lecture 02Lecture 02
Lecture 02
 
Lecture 04
Lecture 04Lecture 04
Lecture 04
 
line coding | Communication Systems
line coding | Communication Systemsline coding | Communication Systems
line coding | Communication Systems
 
Line Coding in OFC
Line Coding in OFCLine Coding in OFC
Line Coding in OFC
 
Lecture 10
Lecture 10Lecture 10
Lecture 10
 
3.3. line coding (encoding)
3.3. line coding (encoding)3.3. line coding (encoding)
3.3. line coding (encoding)
 
Encoding Techniques
Encoding TechniquesEncoding Techniques
Encoding Techniques
 
Ch 04
Ch 04Ch 04
Ch 04
 
Line coding
Line codingLine coding
Line coding
 
Lecture 07
Lecture 07Lecture 07
Lecture 07
 
Digital data transmission,line coding and pulse shaping
Digital data transmission,line coding and pulse shapingDigital data transmission,line coding and pulse shaping
Digital data transmission,line coding and pulse shaping
 
Media Access Methods
Media Access MethodsMedia Access Methods
Media Access Methods
 

Semelhante a Lecture 08

digital-analog_22222222222222222222222.pdf
digital-analog_22222222222222222222222.pdfdigital-analog_22222222222222222222222.pdf
digital-analog_22222222222222222222222.pdf
KiranG731731
 
Data communications 4 1
Data communications 4 1Data communications 4 1
Data communications 4 1
Raymond Pidor
 
Binary to digital encoding tbs 301
Binary to digital encoding tbs 301Binary to digital encoding tbs 301
Binary to digital encoding tbs 301
Bhupesh Rawat
 
Data Encoding
Data EncodingData Encoding
Data Encoding
Luka M G
 
base-band_digital_data_transmission-Line coding - Copy.ppt
base-band_digital_data_transmission-Line coding - Copy.pptbase-band_digital_data_transmission-Line coding - Copy.ppt
base-band_digital_data_transmission-Line coding - Copy.ppt
AbyThomas54
 

Semelhante a Lecture 08 (20)

Ch4 Data communication and networking by neha g. kurale
Ch4 Data communication and networking by neha g. kuraleCh4 Data communication and networking by neha g. kurale
Ch4 Data communication and networking by neha g. kurale
 
Chapter2-PhysicalLayer.ppt
Chapter2-PhysicalLayer.pptChapter2-PhysicalLayer.ppt
Chapter2-PhysicalLayer.ppt
 
digital-analog_22222222222222222222222.pdf
digital-analog_22222222222222222222222.pdfdigital-analog_22222222222222222222222.pdf
digital-analog_22222222222222222222222.pdf
 
Lecture 08
Lecture 08Lecture 08
Lecture 08
 
Data communications 4 1
Data communications 4 1Data communications 4 1
Data communications 4 1
 
line coding techniques, block coding and all type of coding
line coding techniques, block coding and all type of codingline coding techniques, block coding and all type of coding
line coding techniques, block coding and all type of coding
 
Line Coding.pptx
Line Coding.pptxLine Coding.pptx
Line Coding.pptx
 
CCN
CCNCCN
CCN
 
lec5_13.pptx
lec5_13.pptxlec5_13.pptx
lec5_13.pptx
 
Ch4 1 v1
Ch4 1 v1Ch4 1 v1
Ch4 1 v1
 
Data Communication And Networking - DIGITAL TRANSMISSION
Data Communication And Networking - DIGITAL TRANSMISSIONData Communication And Networking - DIGITAL TRANSMISSION
Data Communication And Networking - DIGITAL TRANSMISSION
 
Binary to digital encoding tbs 301
Binary to digital encoding tbs 301Binary to digital encoding tbs 301
Binary to digital encoding tbs 301
 
Data Encoding
Data EncodingData Encoding
Data Encoding
 
base-band_digital_data_transmission-Line coding - Copy.ppt
base-band_digital_data_transmission-Line coding - Copy.pptbase-band_digital_data_transmission-Line coding - Copy.ppt
base-band_digital_data_transmission-Line coding - Copy.ppt
 
DCN 5th ed. slides ch04 Digital Transmission.pdf
DCN 5th ed. slides ch04 Digital Transmission.pdfDCN 5th ed. slides ch04 Digital Transmission.pdf
DCN 5th ed. slides ch04 Digital Transmission.pdf
 
Signal encoding techniques
Signal encoding techniquesSignal encoding techniques
Signal encoding techniques
 
Data Communication & Computer Networks:Digital Signal Encoding
Data Communication & Computer Networks:Digital Signal EncodingData Communication & Computer Networks:Digital Signal Encoding
Data Communication & Computer Networks:Digital Signal Encoding
 
Digital Data, Digital Signal | Scrambling Techniques
Digital Data, Digital Signal | Scrambling TechniquesDigital Data, Digital Signal | Scrambling Techniques
Digital Data, Digital Signal | Scrambling Techniques
 
ch04-digital-transmission.ppt
ch04-digital-transmission.pptch04-digital-transmission.ppt
ch04-digital-transmission.ppt
 
Multi level multi transition
Multi level multi transitionMulti level multi transition
Multi level multi transition
 

Mais de Sehrish Rafiq

Data Communications and Networking Lecture 16
Data Communications and Networking Lecture 16Data Communications and Networking Lecture 16
Data Communications and Networking Lecture 16
Sehrish Rafiq
 

Mais de Sehrish Rafiq (20)

Introduction to Computers Lecture # 14
Introduction to Computers Lecture # 14Introduction to Computers Lecture # 14
Introduction to Computers Lecture # 14
 
Introduction to Computers Lecture # 13
Introduction to Computers Lecture # 13Introduction to Computers Lecture # 13
Introduction to Computers Lecture # 13
 
Introduction to Computers Lecture # 12
Introduction to Computers Lecture # 12Introduction to Computers Lecture # 12
Introduction to Computers Lecture # 12
 
Introduction to Computers Lecture # 11
Introduction to Computers Lecture # 11Introduction to Computers Lecture # 11
Introduction to Computers Lecture # 11
 
Introduction to Computers Lecture # 10
Introduction to Computers Lecture # 10Introduction to Computers Lecture # 10
Introduction to Computers Lecture # 10
 
Introduction to Computers Lecture # 9
Introduction to Computers Lecture # 9Introduction to Computers Lecture # 9
Introduction to Computers Lecture # 9
 
Introduction to Computers Lecture # 8
Introduction to Computers Lecture # 8Introduction to Computers Lecture # 8
Introduction to Computers Lecture # 8
 
Introduction to Computers Lecture # 7
Introduction to Computers Lecture # 7Introduction to Computers Lecture # 7
Introduction to Computers Lecture # 7
 
Introduction to computers Lecture # 4
Introduction to computers Lecture # 4Introduction to computers Lecture # 4
Introduction to computers Lecture # 4
 
Introduction to Computers Lecture # 5
Introduction to Computers Lecture # 5Introduction to Computers Lecture # 5
Introduction to Computers Lecture # 5
 
Introduction to Computers Lecture # 3
Introduction to Computers Lecture # 3Introduction to Computers Lecture # 3
Introduction to Computers Lecture # 3
 
Introduction to Computers Lecture # 2
Introduction to Computers Lecture # 2Introduction to Computers Lecture # 2
Introduction to Computers Lecture # 2
 
Introduction to Computers Lecture # 1
Introduction to Computers Lecture # 1Introduction to Computers Lecture # 1
Introduction to Computers Lecture # 1
 
Data Communications and Networking Lecture 16
Data Communications and Networking Lecture 16Data Communications and Networking Lecture 16
Data Communications and Networking Lecture 16
 
Lecture 24
Lecture 24Lecture 24
Lecture 24
 
Lecture 18
Lecture 18Lecture 18
Lecture 18
 
Lecture 21
Lecture 21Lecture 21
Lecture 21
 
Lecture 13
Lecture 13Lecture 13
Lecture 13
 
Lecture 12
Lecture 12Lecture 12
Lecture 12
 
Lecture 11
Lecture 11Lecture 11
Lecture 11
 

Último

Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Safe Software
 

Último (20)

Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
 
Apidays Singapore 2024 - Modernizing Securities Finance by Madhu Subbu
Apidays Singapore 2024 - Modernizing Securities Finance by Madhu SubbuApidays Singapore 2024 - Modernizing Securities Finance by Madhu Subbu
Apidays Singapore 2024 - Modernizing Securities Finance by Madhu Subbu
 
A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...
 
Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone ProcessorsExploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processors
 
Strategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a FresherStrategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a Fresher
 
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
 
AWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of TerraformAWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of Terraform
 
ICT role in 21st century education and its challenges
ICT role in 21st century education and its challengesICT role in 21st century education and its challenges
ICT role in 21st century education and its challenges
 
MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024
 
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt Robison
 
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, AdobeApidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
 
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemkeProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
 
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
 
GenAI Risks & Security Meetup 01052024.pdf
GenAI Risks & Security Meetup 01052024.pdfGenAI Risks & Security Meetup 01052024.pdf
GenAI Risks & Security Meetup 01052024.pdf
 
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWEREMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
 
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
 
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data DiscoveryTrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
 
Apidays Singapore 2024 - Scalable LLM APIs for AI and Generative AI Applicati...
Apidays Singapore 2024 - Scalable LLM APIs for AI and Generative AI Applicati...Apidays Singapore 2024 - Scalable LLM APIs for AI and Generative AI Applicati...
Apidays Singapore 2024 - Scalable LLM APIs for AI and Generative AI Applicati...
 

Lecture 08

  • 1. DATA COMMUNICATIONS & NETWORKING LECTURE-08 Course Instructor : Sehrish Rafiq Department Of Computer Science University Of Peshawar
  • 2. LECTURE OVERVIEW  Conversion methods  Line coding  Characteristics of line coding  Signal level & Data Level  Pulse Rate & Bit Rate  DC Component  Self Synchronization  Line coding Schemes  Unipolar  Polar  NRZ  RZ  Manchester and Differential Manchester  Bipolar
  • 3. CONVERSION METHODS OR ENCODING & MODULATION  How information is transformed depends on its original format and on the format used by the communication hardware.  Conversion methods  Digital-to-digital conversion or Line coding  Analog-to-digital conversion or Sampling  Digital -to- analog modulation  Analog -to -analog modulation
  • 4. LINE CODING  Line coding is the process of converting binary data, a sequence of bits to a digital signal.  In other words, line coding converts a sequence of bits to a digital signal.  At the sender, digital data are encoded in to digital signal.  At the receiver, the digital data are recreated by decoding the digital signal back in to digital data.
  • 5. LINE CODING & DECODING
  • 6. SIGNAL LEVEL & DATA LEVEL  The number of values allowed in a particular signal is known as the number of signal levels.  The number of values used to represent data is known as the number of data levels.
  • 7. DATA ELEMENT VERSUS SIGNAL ELEMENT  A data Element is the smallest entity that can represent a piece of information this is the bit.  A signal element is the shortest unit time wise of a digital signal.  In other words data elements are what we need to send.  Signal elements are what we can send.  Data elements are being carried, signal elements are the carriers.  r is defined as the ratio which is the number of data elements carried by each signal element.
  • 8. DATA ELEMENT VERSUS SIGNAL ELEMENT
  • 9. DATA RATE VERSUS SIGNAL RATE  The data rate is defined as the number of data elements sent in one second usually expressed in bps.  Data rate is also called Bit rate.  The signal rate is defined as the number of signal elements sent in one second.  A signal rate is also called a pulse rate.  A signal element is also called a symbol or pulse.  One pulse or signal element can carry more than one bit.  When a pulse or signal element carry only one bit then the bit rate and pulse rate/signal rate are same.  The signal rate is sometimes called modulation rate or baud rate.
  • 10. FORMULA FOR BIT RATE Bit Rate=Pulse Rate x log2 L Where L is the number of data Levels.
  • 11. Example 1 A signal has two data levels with a pulse duration of 1 ms. We calculate the pulse rate and bit rate as follows: Solution Pulse Rate = 1/ 10-3= 1000 pulses/s Bit Rate = Pulse Rate x log2 L = 1000 x log2 2 = 1000 bps
  • 12. Example 2 A signal has four data levels with a pulse duration of 1 ms. We calculate the pulse rate and bit rate as follows: Solution Pulse Rate = = 1000 pulses/s Bit Rate = Pulse Rate x log2 L = 1000 x log2 4 = 2000 bps
  • 13. DC COMPONENT  When the voltage level is constant for a while very low frequencies are often created.  These frequencies around zero are called DC or Direct Current components.  This component is undesirable for two reasons.  First if a signal has to pass through a system (e.g. a telephone line which does not allow frequencies below 200 Hz) which does not allow low frequencies to pass the signal is distorted and may create errors in the output.  Second this component is extra energy residing on the line and is useless.
  • 15. SELF-SYNCHRONIZATION  To correctly interpret the signals received from the sender, the receiver’s bit intervals must correspond exactly to the sender’s bit intervals.  If the receiver’s clock is faster or slower, the bit intervals are not matched and the receiver might interpret the signals differently then the sender intended.  A self synchronizing digital signal includes timing information in the data being transmitted.  This can be achieved if there are transitions in the signal that alert the receiver to the beginning, middle or end of the pulse.  If the receiver clock is out of synchronization, these alerting points can reset the clock.
  • 17. Example 3 In a digital transmission, the receiver clock is 0.1 percent faster than the sender clock. How many extra bits per second does the receiver receive if the data rate is 1 Kbps? How many if the data rate is 1 Mbps? Solution At 1 Kbps: 1000 bits sent 1001 bits received1 extra bps At 1 Mbps: 1,000,000 bits sent 1,001,000 bits received1000 extra bps
  • 19. UNIPOLAR SCHEME  Digital transmission systems work by sending voltage pulses along a medium link, usually a wire or cable.  In many types of encoding, one voltage level stands for binary 0,another level stands for binary 1.  The polarity of a pulse refers to whether it is positive or negative.  Unipolar encoding is so named because it uses only one polarity.  The polarity is assigned to one of the two binary states, usually the 1.  The other state usually 0 is represented by zero voltage.
  • 21. PROBLEMS USING UNI POLAR SCHEME  DC Component  The average amplitude of a unipolar encoded signal is non zero.  This creates a DC component.  Lack of synchronization  If the data contain a long sequence of 0’s and 1’s there is no change in the signal during this duration that can alert the receiver to potential synchronization problems.
  • 22. POLAR ENCODING SCHEMES  Polar encoding uses two voltage levels, one positive and one negative.  By using the two Levels, in most polar encoding methods the average voltage level on the line is reduced and the dc component problem seen in unipolar encoding is alleviated.
  • 23. NRZ(NON RETURN TO ZERO) SCHEMES  In NRZ encoding the value of the signal is always positive or negative.  Two popular forms of NRZ are:  NRZ-L(Non Return to Zero-Level)  In NRZ-L the level of the signal depends on the type of bit that it represent.  The positive voltage usually means a 0 while a negative voltage means the bit is a 1.  Problem: Long stream of 0’s or 1’s may create synchronization problem.
  • 24. NRZ(NON RETURN TO ZERO) SCHEMES  NRZ-I(NRZ-Invert)  In NRZ-I ,an inversion of the voltage level represents a 1 bit.  It is the transition between a positive and negative voltage, not the voltage itself, that represents a 1 bit.  A 0 bit is represented by no change.  NRZ-I is superior to NRZ-L due to the synchronization provided by the signal change each time a 1 bit is encountered.  The existence of 1’s in the data stream allows the receiver to synchronize its timer to the actual arrival of transmission.  A string of 0’s can still cause problems but because they are not as Likely,they are less of a problem.
  • 25. NRZ(NON RETURN TO ZERO) SCHEMES
  • 26. THANKS!! !