The document discusses various aspects of digital communication systems including: - Transformation of information to signals and the concepts of bandwidth, bit rate, and bit interval. - The advantages of digital signals over analog signals including their ability to withstand noise better and be coded for low error rates. - Elements of a basic digital communication system including the source of information, modulator, channel, demodulator, and use of information. - Popular digital modulation techniques like PSK, QAM, ASK and FSK and how they map binary data to symbols for transmission over the channel.

1. A.SANYSI RAO
AMIE; M.Tech; MISTE; MIETE
Assoc. Professor
Balaji Institute of Engineering & Sciences
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2. Transformation of Information to Signals
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3. Bandwidth
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4. Bit Rate and Bit Interval
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5. Corruption Due to Insufficient Bandwidth
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6. Objective To send information
•Reliability
•As fast as possible
Constraints Rules of the GAME
•Limited transmit power
•Limited Channel Bandwidth
In our control We get to DESIGN the
•Transmitter
•Receiver
as long they follow the rules of the GAME.
Major Tools
•Signals & Systems
•Probability Theory
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7. Analog versus Digital
It is harder to separate noise from an analog signal than it is to
separate noise from a digital signal.
Noise in a digital signal. You can still discern a high voltage from a low
voltage.
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9. Bandwidth for Telephone Line
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12. Parallel Transmission
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13. Serial Transmission
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14. Asynchronous Transmission
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15. Synchronous Transmission
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16. Ideal pulse shapes.
Non ideal pulse shape.
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17. A.S.Rao

18. Core Concepts of
Digital Communications
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19. Elements of a Digital Communication System
Source of Source Channel
Modulator
Information Encoder Encoder
Binary Stream Channel
Use of Source Channel
Demodulator
Information Decoder Decoder

20. Modified Diagram of a Digital Communication System
From other Sources
Source of Source Channel
Encryptor MUX Modulator
Information Encoder Encoder
Channel
Use of Source Channel DE-
Decryptor Demodulator
Information Decoder Decoder MUX
To other Sources
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21. • Can withstand channel noise and distortion much better as long
as the noise and the distortion are within limits.
• Regenerative repeaters prevent accumulation of noise along the
path.
• Digital hardware implementation is flexible.
• Digital signals can be coded to yield extremely low error rates,
high fidelity and well as privacy.
• Digital communication is inherently more efficient than analog in
realizing the exchange of SNR for bandwidth.
• It is easier and more efficient to multiplex several digital signals.
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22. • Digital signal storage is relatively easy and inexpensive.
• Reproduction with digital messages is extremely reliable without
deterioration.
• The cost of digital hardware continues to halve every two or
three years, while performance or capacity doubles over the
same time period.
Disadvantages
• TDM digital transmission is not compatible with the FDM
• A Digital system requires large bandwidth.
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23. PCM System
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26. •Quantization process
•Quantization Error
•Mean Square Value of Quantization Noise
•SNR of PCM system
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27. M  S   Q.E  n   S/N   BW 
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29.  Many signals such as speech have a nonuniform distribution.
– The amplitude is more likely to be close to zero than to be at higher levels.
 Nonuniform quantizers have unequally spaced levels
Output sample
6
4
2
-8 -6 -4 -2 2 4 6 8
-2
Input sample
-4
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31. Companding in PCM
•Non-uniform quantizers are expensive and difficult to make.
•An alternative is to first pass the speech signal through a non
linearity before quantizing with a uniform quantizer.
•The non linearity causes the signal amplitude to be compressed. So
the input to the quantizer will have a more uniform distribution.
•At the receiver, the signal is expanded by an inverse to the
nonlinearity.
•The process of compressing and expanding is called Companding.
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32. compression+expansion companding
ˆ
x
x(t ) y (t ) ˆ
y (t ) ˆ
x(t )
x ˆ
y
Compress Uniform Qauntize Expand
Transmitter Channel Receiver
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34. Telephones in US, Canada and Japan use -law Companding. (=255)
A-Law is used elsewhere to compress digital telephone signals.
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37. Digital Formats
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38. Differential PCM
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39. •PCM is powerful, but quite complex coders and decoders are
required.
•An increase in resolution also requires a higher number of bits per
sample.
•The Delta Modulation is the most economical form of Digital
Communication System since it requires only one bit per sample
(either low pulse or high pulse) transmitted through the line.
•Delta Modulation uses a single-bit PCM code to achieve digital
transmission of analog signals.
•Normally Sampled at high rate.
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40. 
When the step is decreased, ‘0’ is transmitted and if it
is increased, ‘1’ is transmitted.
Delta Modulation: Unique Features
1. No need for Word Framing because of one-bit code word.
2. Simple design for both Transmitter and Receiver.
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41. DM Transmitter
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42. DM Receiver
Limitations / Problems of DM system
•Slope over load error
•Granular error (or) Hunting
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43. Slope overload - when the analog input signal changes at a faster
rate than the DAC can maintain. The slope of the analog signal is
greater than the delta modulator can maintain and is called slope
overload.
Granular noise - It can be seen that when the original analog input
signal has a relatively constant amplitude, the reconstructed signal
has variations that were not present in the original signal. This is
called granular noise. Granular noise in delta modulation is
analogous to quantization noise in conventional PCM.
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46. M- ary Signaling
Multiple Signal Levels:
Why use multiple signal levels?
We can represent two levels with a single bit, 0 or 1.
We can represent four levels with two bits: 00, 01, 10, 11.
We can represent eight levels with three bits: 000, 001,
010, 011, 100, 101, 110, 111
Note that the number of levels is always a power of 2.
M=2n
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47. DIGITAL MODULATION
Input Binary
data
Output Symbol/waveform
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48. GOALS OF MODULATION TECHNIQUES
• Low cost and ease of implementation
• Low carrier-to-co channel interference ratio
• Low-Cost/Low-Power Implementation
• High Power Efficiency
• High Bit Rate
• High Spectral Efficiency
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49. Bit Rate Vs Baud Rate
Bit rate is the number of bits per second. Baud rate is the number of
signal units (symbols) per second. Baud rate is less than or equal to
the bit rate.
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50. Modulation Units Bits/Baud Baud rate Bit Rate
ASK, FSK, 2-PSK Bit 1 N N
4-PSK, 4-QAM Dibit 2 N 2N
8-PSK, 8-QAM Tribit 3 N 3N
16-QAM Quadbit 4 N 4N
32-QAM Pentabit 5 N 5N
64-QAM Hexabit 6 N 6N
128-QAM Septabit 7 N 7N
256-QAM Octabit 8 N 8N
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52. ASK
FSK
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53. PSK
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54. QPSK
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55. 8 PSK
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56. The 4-QAM and 8-QAM constellations
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57. Time domain representation for an 8-QAM signal
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58. 16-QAM constellations
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59. Detection
• Coherent Detection
• Non Coherent Detection
Bandwidth Efficiency
Data Transmission Rate , rb
 BW 
M inimum Bandwidth, B
2
B
TS
log 2 M
 BW 
2
M    BW 
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60. Matched Filter
The ultimate task of a receiver is detection, i.e. deciding between
1’s and 0’s. This is done by sampling the received pulse and
making a decision
Matched filtering is a way to distinguish between two pulses
with minimum error
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61. Im pulse response of the Matched Filter is
2K
h(t )  x(T  t )
N0
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63. Inter Symbol Interference
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64. • A sinc pulse has periodic zero crossings. If successive bits
are positioned correctly, there will be no ISI at sampling
instants.
Sampling Instants
ISI occurs but,
NO ISI is present at the
sampling instants
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65. Raised Cosine Filter
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66. EYE DIAGRAMS
The eye diagram provides visual information that can be useful
in the evaluation and troubleshooting of digital transmission
systems.
It provides at a glance evaluation of system performance and
can offer insight into the nature of channel imperfections,
Top: Undistorted eye diagram of a band limited digital signal
Bottom: Eye diagram includes amplitude (noise) and phase (timing) errors
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68. Eye Pattern formation
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69. Information Theory
• It is a study of Communication Engineering plus
Maths.
• A Communication Engineer has to Fight with
• Limited Power
• Inevitable Background Noise
• Limited Bandwidth
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70. P varies as e  KEb
e
S i  Eb Rb  Eb  Si / Rb
Eb   S i  or Rb   Eb 
Hartley Shannon has shown that
“If the rate of information from a source does not exceed
the capacity of a given communication channel, then there exists
a coding technique such that the information can be transmitted
over the channel with arbitrary small frequency errors, despite
the presence of noise.”
Information theory deals with the following three basic concepts:
•The measure of source information
•The information capacity of a channel
•Coding A.S.Rao

71. Information Sources:
•Analog Information Source
•Discrete Information Source
Information Measure
Consider two Messages
A Dog Bites a Man  High probability  Less information
A Man Bites a Dog  Less probability  High Information
Information α (1/Probability of Occurrence)
The basic principle involved in determining the information
content of a message is that “the information content of a
message increases with its uncertainty”
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72. Let I(mK) the information content in the Kth message.
I ( mk )  0 for PK 1
I ( mk )  I ( m j ) for PK  Pj 1
I ( mk )  0 for 0  Pk  1
I (mk and m j )  I (mk m j )  I (mk )  I (m j ) 2
 1 
I (mk )  log b 
P 

 k 
The quantity I(mk) is called the Self information of message mk.
1
The self information convey the message is I  log
P
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73. Coding
Why Coding?
• to achieve reliable data communication
• to achieve reliable data storage
• to reduce the required transmit power
• to reduce hardware costs of transmitters
• to improve bandwidth efficiency
• to increase channel utilisation
• to increase storage density
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74. • Source Coding
• Channel Coding
Source Coding
• Shannon Fano Code
• Huffman Code
Channel Coding
• Linear Block Codes
•Cyclic Codes
• Convolutional Codes
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75. Shannon Fano Source code
Algorithm.
Step 1: Arrange all messages in descending order of probability.
Step 2: Divide the Seq. in two groups in such a way that sum of
probabilities in each group is same.
Step 3: Assign 0 to Upper group and 1 to Lower group.
Step 4: Repeat the Step 2 and 3 for Group 1 and 2 and So on……..
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76. Messages
Pi Coding Procedure No. Of Code
Mi Bits
M1 ½ 0 1 0
M2 1/8/ 1 0 0 3 100
M3 1/8 1 0 1 3 101
M4 1/16 1 1 0 0 4 1100
M5 1/16 1 1 0 1 4 1101
M6 1/16 1 1 1 0 4 1110
M7 1/32 1 1 1 1 0 5 11110
m8 1/32 1 1 1 1 1 5 11111
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77. HUFFMAN CODING
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78. SHANNON HARTLEY CHANNEL CAPACITY THEOREM
 S
C  B log 2 1  
 N
Channel Capacity with Infinite Bandwidth
C
S
Lt C  1.44 1.44
S
B   
B
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