Data Communication & Computer Networks:Digital Signal Encoding

These slides cover the fundamentals of data communication & networking. It covers Digital signal Encoding which are used in communication of data over transmission medium. it is useful for engineering students & also for the candidates who want to master data communication & computer networking.

1. Introduction to Data communication
Topic : Digital Signal Encoding
Lecture #5

Dr Rajiv Srivastava
Director

Sagar Institute of Research & Technology (SIRT)
Sagar Group of Institutions, Bhopal
http://www.sirtbhopal.ac.in

2. Unit 1
Lecture 5

Digital Signal Encoding

A Digital To Digital Data Transmission Method
2

3. Coding
•Coding in communications & information processing is
system of rules to convert information - such as a letter,
word, sound, image, or gesture—into another form.
•A first example is the invention of language, which enabled
a person, through speech, to communicate what he or she
saw, heard, felt, or thought to others.
•Speech limits the range of communication to the distance a
voice can carry, and limits the audience to those present
when the speech is uttered.
•The invention of writing, which converted spoken language
into visual symbols, extended the range of communication
across space and time. 3

4. Encoding
•Encoding is the technical term used for coding
in data communication. Coding is changing
the form of data from one form to other.
•Encoding converts information from a source
into symbols for communication or storage.
•Decoding is the reverse process, converting
code symbols back into a form that the
recipient understands.

4

5. Morse Encoding
Morse code is a method of transmitting text
information as a series of on-off tones, lights, or clicks
that can be directly understood by a skilled listener or
observer without special equipment.
5

6. Different Conversion/Transmission Schemes
6
Before we discuss various line coding schemes, let us first
have an idea of different data conversion schemes.

7. •Digital to digital conversion
•Line Coding
•Block Coding
•Scrambling
•Analog to Digital Conversion
•PAM
•PCM
–Nyquist Theorem
•Digital To Analog Conversion
•ASK, FSK, PSK & QAM
–Constellation
•Analog to Analog Conversion
•AM, FM &PM

7
Different Techniques Used in Data Transmission/Conversion

8. 4.8
DIGITAL-TO-DIGITAL CONVERSION
•We know that data can be either digital or
analog.
•We know that signals that represent data can
also be digital or analog.
•The digital data can be converted & represented
into digital signals. This conversion can be done
by three techniques:
1.line coding
2.block coding &
3.Scrambling
Line coding is always needed; block coding and
scrambling may or may not be needed.

9. 4.9
Line Coding
•Line coding is the process of converting digital data
to digital signals.
• We assume that data, in the form of text, numbers,
graphical images, audio, or video, are stored in
computer memory as sequences of bits.
•Line coding converts a sequence of bits to a digital
signal. At the sender, digital data are encoded into a
digital signal; at the receiver, the digital data are
recreated by decoding the digital signal. Figure
shows the process.
•Line code is also called as digital baseband
modulation or baseband transmission.

10. Line coding and decoding
Codec

11. Codec
•A codec is a device or computer program capable of
encoding or decoding a digital data stream or signal. Codec
is a short word of coder-decoder or, less commonly,
compressor-decompressor.
•A codec encodes a data stream or signal for transmission,
storage or encryption, or decodes it for playback or editing.
Codecs are used in videoconferencing, streaming media
and video editing applications.
•A video camera's analog-to-digital converter (ADC) converts
its analog signals into digital signals, which are then passed
through a video compressor for digital transmission or
storage. A receiving device then runs the signal through a
video decompressor, then a digital-to-analog converter
(DAC) for analog display.
11

12. Some of the important characteristics of line coding are:

1.Signal element vs data element
2.Data rate vs Signal rate
3.Bandwidth
4.Baseline Wandering
5.DC Component
6.Self Synchronization
7.Built in Error Detection
8.Immunity to Noise & Interference
9.Complexity

12
Some Common Characteristics of line
coding

13. 1. Data Element Vs Signal Element
•Data is the smallest unit which can be sent & it is a
bit
•Signal is the smallest time wise unit of digital signal
•A signal only carries data element
•A single signal can carry one or multiple data
element as well
•We are also defining a ratio r which is no of data
element carried by each signal for the purpose of
understanding relation between data element &
signal element. So, r = data element/signal element.
13

14. Figure: Signal elements versus data elements

15. 2. Data Rate vs Signal Rate
The data rate defines the number of data elements (bits)
sent in 1s. The unit is bits per second (bps). The data rate
is sometimes called the bit rate also.
The signal rate is the number of signal elements sent in 1s.
The unit is the baud. The signal rate is sometimes called
the pulse rate, the modulation rate, or the baud rate.
S = N/r
S
avg = c x N/r
c is a case factor which is normally 1, it can have
other value
S = Signal rate in baud
N = data rate in bps

15

16. A signal is carrying data in which one data element is
encoded as one signal element (r = 1). If the bit rate is 100
kbps, what is the average value of the baud rate if c is
between 0 and 1?
Example 1
Solution
We assume that the average value of c is 1/2. The baud rate
is then
4.16
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17. 3. Bandwidth
•The actual bandwidth of a digital/data signal is
infinite
•The effective bandwidth of data signal is
found to be finite
•The minimum bandwidth is calculated as
B
min = c x N x (1/r)
•The maximum data rate of a channel is
calculated by Nyquist formula as below:
N
max = 2 x B x log
2 L
B = Bandwidth &
L = Levels of signals

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18. A signal has two data levels with a pulse duration of 1
ms. Calculate the pulse rate and bit rate.
Pulse Rate = 1/ 10
-3
= 1000 pulses/s

Bit Rate =

= 1000 x log
2 2
= 1000 bps
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Example 2
Pulse Rate x log
2 L
•If signal level is 2
then bit rate is
same as pulse
rate
•If signal is 4 then
bit rate is 2 times
to pulse rate
•If signal is 8 then
bit rate is 3 times
to pulse rate

19. A signal has four data levels with a pulse duration
of 1 ms. Calculate the pulse rate and bit.
Pulse Rate = = 1000 pulses/s
Bit Rate = PulseRate x log
2 L = 1000 x log
2 4 = 2000 bps
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Example 3

20. •Switch to lecture of channel capacity from
here.
20

21. The maximum data rate of a channel is
N
max = 2 × B × log
2 L (defined by the Nyquist formula).
Does this agree with the previous formula for N
max?
Solution
A signal with L levels actually can carry log2 L bits per
level. If each level corresponds to one signal element and we
assume the average case (c = 1/2), then we have
4.21
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Example 3

22. 4. Baseline wandering
In decoding a digital signal, the receiver calculates a
running average of the received signal power. This
average is called as baseline. The incoming signal
power is evaluated against this baseline to determine
the value of the data element. A long string of 0s or 1s
can cause a drift in the baseline (baseline wandering)
and make it difficult for the receiver to decode
correctly. A good line coding scheme needs to prevent
baseline wandering.
22

23. 5. DC Component
When the voltage level in a digital signal is constant for
a while, the spectrum creates very low frequencies
(results of Fourier analysis). These frequencies around
zero are called DC (direct-current) components which
present problems for a system that cannot pass low
frequencies or a system that uses electrical coupling
(via a transformer).
For example, a telephone line cannot pass frequencies
below 200 Hz. Also a long-distance link may use one or
more transformers to isolate different parts of the line
electrically. For these systems, we need a scheme with
no DC component.
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24. Figure DC component
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25. 6. 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 clock is faster or slower,
the bit intervals are not matched and the receiver might
misinterpret the signals. Figure shows a situation in which
the receiver has a shorter bit duration. The sender send
1011001, while the receiver receives 110111000011.
•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’s clock is out of synchronization, these points can
reset the clock.

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26. •In telecommunications, a self-synchronizing code,
or comma-free code, is a line code that can be
easily synchronized. Such line codes have the
property that the code which is made of a part of
the code word, or two overlapping code words is
not a valid code. An example, take the code words
11 and 00, and the code 11 00 00 11 00. The spaces
have been added to show the different words, and
are not really in the code.
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6. Self Synchronization

27. •Let's now assume that four letters (two code
words) are read. The code 1000 is not a valid
code, because 10 is not one of the two code
words defined. Similarly, 0001. Even though
00 is a valid word, 01 is not. The only valid way
to read two valid words from the example
given is by starting at the very beginning, or
just after one of the spaces, which have been
inserted for clarity only.
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28. 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, the receiver receives 1001 bps instead of 1000
bps.
At 1 Mbps, the receiver receives 1,001,000 bps instead of
1,000,000 bps.
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Example 4

29. 7.Built in Error Detection – It is desirable to have a built-
in-error-detecting capability in the generated code to
detect some of or all the errors that occurred during
transmission.

8.Immunity to Noise & Interference – Another desirable
code characteristic is code that is immune to noise
and other interferences.

9.Complexity – A complex scheme is more costly to
implement than a simple one. For example, a scheme
that uses four signal levels is more difficult to interpret
than one that uses only two levels.

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30. Thank You
Dr Rajiv Srivastava
Director

Sagar Institute of Research & Technology (SIRT)
Sagar Group of Institutions, Bhopal
http://www.sirtbhopal.ac.in