The document provides an overview of digital communication systems, focusing on the roles of source encoding, channel coding, modulation, and demodulation to ensure reliable data transmission despite the presence of noise. It discusses various parameters such as source entropy, average data rates, errors introduced in signals, and the importance of efficient coding techniques. Additionally, it highlights the differences between wired and wireless communication channels and their respective advantages and challenges.

1. Lecture 1

2. • Source and Destination
– Two physical separate points
– Noise interfere
– Error introduce in Rx signal
• Effect of noise
– Communication channel
limit the rate at which
signal can be transmitted
• Communication
– Analog or Digital possible
Modulation
De-Modulation
Communitcation
channel
Source
Destination
Noise
Basic Electronics
Communication Block
Diagram
Introduction

3. Importance of the subject
• Digital Communication
– Error free communication is not possible
• So we adding two more blocks in basic block diagram
which increase the reliability of data transmission
– Source coding and Channel Coding
How to evaluate this data transmission ?
• Probability of error and Transmission rate
– Performance measure of the digital Communication
system

4. Basic Electronics Communication
system Block Diagram
Source Modulator
Channel
Sink
De-
Modulator
NOISE

5. Communication system block Diagram
Source
Source
Encoder
Channel
Encoder
Modulator
Channel
Sink
Source
Decoder
Channel
Decoder
De-
Modulator
Source
Coding
Channel
Coding
NOISE

6. Elements of Digital
Communication system
• Information Source and Destination
• Source encoder and decoder
• Channel encoder and decoder
• Digital modulator and Demodulator
• Communication channel

7. Information signal in Communication
system
Source
Source
Encoder
Channel
Encoder
Modulator
Channel
Sink
Source
Decoder
Channel
Decoder
De-
Modulator
NOISE

8. Information Source
and Destination
• Originates messages
– Human voice, Teletype message, A Television
picture , Computer data
( Transducer Electrical form)
– Information
• Analog or Digital
– Digital information source
• Computers, Teletype, etc…. and Text is also Discrete
– Analog information source
• Transmitted to discrete signal by Sampling &
Quantization (Analog to Digital conversion )

9. Important parameter for Discrete
information sources
• Source alphabet :- Letters, Digitals or special characters
• Symbol Rate : - Rate at which information source generates
source alphabets (Symbols/sec.)
• Source alphabets probabilities : -
– Independent occurrence rate in the sequences
e.g. - Letters A,E,I etc. occurrence frequently in the
sequence
– Probability of the occurrence of each source alphabet
it’s important property in Digital communication
• Probabilistic dependence of symbols in sequence : -
– Information carrying capacity of each source alphabet
– Defines average information content of the symbols

10. Important parameter for Discrete
information sources (cont…)
• Probabilistic dependence of symbols in sequence (cont...) : -
– Entropy of a source (Source entropy) : - The average
information content per symbol in the long message
(Bits/symbol)
– Source information rate : - Product of symbol rate and
source entropy
Information Rate = Symbol Rate  Source Entropy
(Bits/sec) (Symbols/sec) (Bits/Symbol)
– Information rate represents minimum average data rate
required to transmit information from source to
destination

11. Source Coding in Communication
system
Source
Source
Encoder
Channel
Encoder
Modulator
Channel
Sink
Source
Decoder
Channel
Decoder
De-
Modulator
Source
Coding
NOISE

12. Source Encoder and Decoder
• Symbol cannot be transmitted directly.
• Converted into digital form (Binary 1’s and 0’s)
• The group of bits is called a codeword
• Assigns codeword to symbol (Unique)
• Codeword can be 4, 8 , 16 or 32 bits length
No. of bits  Symbols representation (codewords) 
e.g. 8 bits 28
= 256 codewords 256 symbols
16 bits 216
= 65536 codewords 65536 symbols
• If codeword length are same throughout , it is called Fixed
length coding (Efficient Equal Probabilities)
(Statistically Independent)

13. Source Encoder and Decoder (cont…)
• Practically, Symbols Statistically dependent
(Unequal Probabilit)
e.g. Symbols sequence represents the % marks of students
2 % , 8% , 20%, 98%, 99% etc.. Minimum Probability
60%, 55%,65%,70%, 75%, etc.. Maximum Probability
• For Such symbols normally we use variable length codewords
More length (bits) Frequently occurring symbols
Less length (bits) Rarely occurring symbols
• Examples of Source Encoder : -
Pulse code Modulators , Delta Modulators, Vector
quantizer s etc…

14. Important parameter
Source coder
• Block Size :-
– Maximum No. of distinct codewords
– Depends upon No. of bits in the codewords
e.g. Block size of 8 bits source coder have 256 codewords
• Codewode length :- Each codeword
e.g. 8 bits of every codewords
• Average Data rate :- Output bits/sec from source encoder
It assigns no. of bits to every input symbols
Data rate > Symbol rate
e.g. Symbol rate = 10 symbols/sec.
Code word length = 8 bits/symbols .
Data Rate = 80 bits/sec.

15. Important parameter
Source coder (cont…)
• Efficiency of the encoder : -
– Ratio of Minimum source information rate to actual output
rate of source encoder
• At Receiver Side : -
– Reverse operation of encoder
• Converts binary Symbol sequence
 Variable or Fixed length coding possible
 Decoders use the memory to store codewords
 Encoders and Decoders can be Synchronous or
Asynchronous

16. Channel Coding in Communication
System
Source
Source
Encoder
Channel
Encoder
Modulator
Channel
Sink
Source
Decoder
Channel
Decoder
De-
Modulator
Channel
Coding
NOISE

17. Channel Coding
• At this stage information signal in form bits
(1’s and 0’s)
• Communication channel adds noise and
interfere in transmission signal
• Error introduced in received binary sequence
Error Symbols
• To avoids errors, Channel coding is done.
• Adds Some redundant binary bits to input
sequence with properly defined logic

18. Channel Coding (cont…)
• Here, Channel Encoder add 4th
bit (1 or 0) for parity checking
at receiver side 4th
bit depends on parity of 3bit codeword
Output of Source
Encoder
Added bit
by channel
Encoder
Output of Channel Encoder
b3 b2 b1 b0 b3 b2 b1 b0
1 1 0 0 1 1 0 0
0 1 0 1 0 1 0 1
0 0 0 0 0 0 0 0
1 1 1 1 1 1 1 1
Channel
Coder
3 bits
codewords
4 bits
codewords

19. Channel Coding (cont…)
• Output of Channel encoder contains “even”
No. of 1’s
• At Rx, Odd No. of 1’s are detected,
Rx comes to know Error in received signal
• Channel Decoder Reconstruct error free accurate bit
sequence & reduces noise and distortion effects
• Reliability increases
• No. information carried by added extra bits
• Many advanced & efficient coding techniques available
• Needs Memory(storage) & processing device or circuits
Using (microcontroller and microprocessor ) complexity will
decreases

20. Important parameter
Channel coder
• Method of coding
• Coding rate  Redundant bits adder
• Error control Capabilities
• Complexity of Encoder and Decoder
• Time delay
Encoder
channel
output
at
rate
Data
input
at
rate
Data
Efficiency
Coding





21. Modulation and Demodulation
in Communication System
Source
Source
Encoder
Channel
Encoder
Modulator
Channel
Sink
Source
Decoder
Channel
Decoder
De-
Modulator
Modulation
Demodulation
NOISE

22. Digital modulators and
Demodulators
• Modulator and Demodulators required
• Modulation signal is discrete (bits), Digital
modulation techniques are used
• Carrier Continuously sinusoidal wave of
high frequency
• Modulator maps bits to analog signals
waveforms
f1 for 0 , f2 for 1 (FSK technique)
• Other techniques ASK , FSK ,BPSK ,QPSK

23. Digital modulators and
Demodulators(cont….)
• Suppose the codeword length = 2 bits and they are to
be transmitted at a time ,
M = 22 = 4 Distinct symbols (or codewords)
• For above, 4 codewords will require 4 distinct
waveforms for transmission
This types of modulators are called
M-ary Modulators
• Digital Demodulators Reverse process

24. Important Parameters
• Probability of Symbols or bit error
• Bandwidth needed to transmit signal
• Synchronous or Asynchronous methods
(detection)
• Complexity of implementations

25. NOISE
Communication channel
in Communication System
Source
Source
Encoder
Channel
Encoder
Modulator
Channel
Sink
Source
Decoder
Channel
Decoder
De-
Modulator

26. Communication channel
• Connection between Transmitter and Receiver
• Can be
– Wireless (Radio) Communication
– Wired (Line) Communication
• Line communication channels
- Two pair wired - Coaxial Cable
- Fiber Optics - Wave guide
• Radio Communication channels
- Free space ( e.g. Satellite, Microwave, Mobile)

27. Communication channel(cont…)
• Every Communication have some problems
• Problem associated with the channels
– Additive noise interference Due to solid state
devices
– Signal attenuation Internal Resister and fading of
signal
– Amplitude & Phase Distortion non linear
characteristic of channel
– Multipath distortion Signals coming from different
paths tend to interfere with each other

28. Communication channel(cont…)
• Two Resources with communication channel
– Channel Bandwidth : -
• Maximum possible range of frequency ( wireline <
fiber optic channel)
– Power in the transmitted signal
• Effect of noise can be minimized by increasing the
power
• Cannot be increased to very high value
• (Because of equipment and other constraints)
• Power in wireline channel is limited (cable)
• They limit the Data rate

29. Communication channel(cont…)
• Fiber optic communication
– Due to light signal transmission
( no current and metallic conductor )
– Advantages
 Large BW  Little loss
· EM waves absent  Small size and weight
· Ruggedness  Low cost & cheap
• Satellite communication
– Wireless
– Repeaters
– Advantages
· Broad area coverage  Less power (Solar Energy)
· Global Communication Possible  Minimum Interference