Computer Networks and basics for CSE students

1.2
1-1 DATA COMMUNICATIONS
The term telecommunication means communication at a
distance. The word data refers to information presented
in whatever form is agreed upon by the parties creating
and using the data.
▪ Components of a data communications system
▪ Data Flow
Topics discussed in this section:

1.4
Figure 1.1 Components of a data communication system

Data Representation
◼ Text: Unicode, ASCII
◼ Images: Pixels, Grayscale, RGB
◼ Audio
◼ Video
1.5

1.6
Figure 1.2 Data flow (simplex, half-duplex, and full-duplex)

1.7
1-4 PROTOCOLS
A protocol is synonymous with rule. It consists of a set of
rules that govern data communications. It determines
what is communicated, how it is communicated and when
it is communicated. The key elements of a protocol are
syntax, semantics and timing
▪ Syntax
▪ Semantics
▪ Timing

1.8
Elements of a Protocol
◼ Syntax
◼ Structure or format of the data
◼ Indicates how to read the bits - field delineation
◼ Semantics
◼ Interprets the meaning of the bits
◼ Knows which fields define what action
◼ Timing
◼ When data should be sent and what
◼ Speed at which data should be sent or speed at which it is being
received.

3.9
To be transmitted, data must be
transformed to electromagnetic signals.
Note

3.10
3-1 ANALOG AND DIGITAL
▪ Analog and Digital Data
▪ Analog and Digital Signals
▪ Periodic and Nonperiodic Signals

3.11
Analog and Digital Data
▪ Data can be analog or digital.
▪ Analog data are continuous and take
continuous values.
▪ Digital data have discrete states and
take discrete values.

3.12
Analog and Digital Signals
• Signals can be analog or digital.
• Analog signals can have an infinite
number of values in a range.
• Digital signals can have only a limited
number of values.

3.13
Figure 3.1 Comparison of analog and digital signals

3.21
3-2 PERIODIC ANALOG SIGNALS
In data communications, we commonly use periodic analog signals
and nonperiodic digital signals.
Periodic analog signals can be classified as simple or composite. A
simple periodic analog signal, a sine wave, cannot be decomposed
into simpler signals. A composite periodic analog signal is composed
of multiple sine waves.
▪ Sine Wave
▪ Wavelength
▪ Time and Frequency Domain
▪ Composite Signals
▪ Bandwidth

3.22
Figure 3.3 Two signals with the same phase and frequency,
but different amplitudes

3.23
Frequency and period are the inverse of
each other.
Note

3.24
Figure 3.4 Two signals with the same amplitude and phase,
but different frequencies

3.25
Table 3.1 Units of period and frequency

3.26
The power we use at home has a frequency of 60 Hz.
The period of this sine wave can be determined as
follows:
Example 3.1

3.27
The period of a signal is 100 ms. What is its frequency
in kilohertz?
Example 3.2
Solution
First we change 100 ms to seconds, and then we
calculate the frequency from the period (1 Hz = 10−3
kHz).

3.28
Frequency
• Frequency is the rate of change with
respect to time.
• Change in a short span of time means
high frequency.
• Change over a long span of
time means low frequency.

3.29
If a signal does not change at all, its
frequency is zero.
If a signal changes instantaneously, its
frequency is infinite.
Note

3.30
Phase describes the position of the
waveform relative to time 0.
Note

3.32
Figure 3.6 Wavelength and period

3.33
Figure 3.7 The time-domain and frequency-domain plots of a sine wave

3.34
A complete sine wave in the time
domain can be represented by one
single spike in the frequency domain.
Note

3.35
Figure 3.8 The time domain and frequency domain of three sine waves
The frequency domain is more compact and useful when we are dealing with more than one sine
wave. For example, Figure 3.8 shows three sine waves, each with different amplitude and
frequency. All can be represented by three spikes in the frequency domain.

3.36
Signals and Communication
◼ A single-frequency sine wave is not
useful in data communications
◼ We need to send a composite
signal, a signal made of many
simple sine waves.
◼ According to Fourier analysis, any
composite signal is a combination of
simple sine waves with different
frequencies, amplitudes, and
phases.

3.37
Composite Signals and
Periodicity
◼ If the composite signal is periodic, the
decomposition gives a series of
signals with discrete frequencies.
◼ If the composite signal is nonperiodic,
the decomposition gives a
combination of sine waves with
continuous frequencies.

3.38
Figure 3.9 shows a periodic composite signal with
frequency f. This type of signal is not typical of those
found in data communications. We can consider it to
be three alarm systems, each with a different
frequency. The analysis of this signal can give us a
good understanding of how to decompose signals.
Example 3.4

3.39
Figure 3.9 A composite periodic signal

3.40
Figure 3.10 Decomposition of a composite periodic signal in the time and
frequency domains

3.41
Figure 3.11 shows a nonperiodic composite signal. It
can be the signal created by a microphone or a
telephone set when a word or two is pronounced. In
this case, the composite signal cannot be periodic,
because that implies that we are repeating the same
word or words with exactly the same tone.
Example 3.5

3.42
Figure 3.11 The time and frequency domains of a nonperiodic signal

3.43
Bandwidth and Signal
Frequency
◼ The bandwidth of a composite signal
is the difference between the highest
and the lowest frequencies contained
in that signal.

3.44
Figure 3.12 The bandwidth of periodic and nonperiodic composite signals

3.45
If a periodic signal is decomposed into five sine waves
with frequencies of 100, 300, 500, 700, and 900 Hz,
what is its bandwidth? Draw the spectrum, assuming
all components have a maximum amplitude of 10 V.
Solution
Let fh be the highest frequency, fl the lowest frequency,
and B the bandwidth. Then
Example 3.6
The spectrum has only five spikes, at 100, 300, 500,
700, and 900 Hz (see Figure 3.13).

3.46
Figure 3.13 The bandwidth for Example 3.6

3.47
3-3 DIGITAL SIGNALS
In addition to being represented by an analog signal,
information can also be represented by a digital signal. For
example, a 1 can be encoded as a positive voltage and a 0 as zero
voltage. A digital signal can have more than two levels. In this
case, we can send more than 1 bit for each level.
▪ Bit Rate
▪ Bit Length
▪ Digital Signal as a Composite Analog Signal
▪ Application Layer

3.48
Figure 3.16 Two digital signals: one with two signal levels and the other
with four signal levels

3.49
A digital signal has eight levels. How many
bits are needed per level? We calculate the
number of bits from the formula
Example 3.16
Each signal level is represented by 3 bits.

3.50
A digital signal has nine levels. How many
bits are needed per level? We calculate the
number of bits by using the formula. Each
signal level is represented by 3.17 bits.
However, this answer is not realistic. The
number of bits sent per level needs to be
an integer as well as a power of 2. For this
example, 4 bits can represent one level.
Example 3.17

3.51
Assume we need to download text
documents at the rate of 100 pages per
sec. What is the required bit rate of the
channel?
Solution
A page is an average of 24 lines with 80
characters in each line. If we assume that
one character requires 8 bits (ascii), the bit
rate is
Example 3.18

3.53
A digitized voice channel, as we will see in
Chapter 4, is made by digitizing a 4-kHz
bandwidth analog voice signal. We need to
sample the signal at twice the highest
frequency (two samples per hertz). We
assume that each sample requires 8 bits.
What is the required bit rate?
Solution
The bit rate can be calculated as
Example 3.19

3.54
Figure 3.17 The time and frequency domains of periodic and nonperiodic
digital signals

3.55
Figure 3.18 Baseband transmission

3.56
A digital signal is a composite analog
signal with an infinite bandwidth.
Note

3.57
Figure 3.19 Bandwidths of two low-pass channels

3.58
Figure 3.20 Baseband transmission using a dedicated medium

3.59
Baseband transmission of a digital
signal that preserves the shape of the
digital signal is possible only if we have
a low-pass channel with an infinite or
very wide bandwidth.
Note

3.60
Figure 3.23 Bandwidth of a bandpass channel

3.61
If the available channel is a bandpass
channel, we cannot send the digital
signal directly to the channel;
we need to convert the digital signal to
an analog signal before transmission.
Note

3.62
3-4 TRANSMISSION IMPAIRMENT
Signals travel through transmission media, which are not
perfect. The imperfection causes signal impairment. This
means that the signal at the beginning of the medium is
not the same as the signal at the end of the medium. What
is sent is not what is received. Three causes of
impairment are attenuation, distortion, and noise.
▪ Attenuation
▪ Distortion
▪ Noise

3.63
Figure 3.25 Causes of impairment

3.64
Attenuation
◼ Means loss of energy -> weaker signal
◼ When a signal travels through a
medium it loses energy overcoming the
resistance of the medium
◼ Amplifiers are used to compensate for
this loss of energy by amplifying the
signal.

3.65
Measurement of Attenuation
◼ To show the loss or gain of energy the
unit “decibel” is used.
dB = 10log10P2/P1
P1 - input signal
P2 - output signal

3.67
Suppose a signal travels through a
transmission medium and its power is
reduced to one-half. This means that P2 is
(1/2)P1. In this case, the attenuation (loss
of power) can be calculated as
Example 3.26
A loss of 3 dB (–3 dB) is equivalent to
losing one-half the power.

3.68
Distortion
◼ Means that the signal changes its form or
shape
◼ Distortion occurs in composite signals
◼ Each frequency component has its own
propagation speed traveling through a
medium.
◼ The different components therefore arrive
with different delays at the receiver.
◼ That means that the signals have different
phases at the receiver than they did at the
source.

3.70
Noise
◼ There are different types of noise
◼ Thermal - random noise of electrons in the
wire creates an extra signal
◼ Induced - from motors and appliances,
devices act are transmitter antenna and
medium as receiving antenna.
◼ Crosstalk - same as above but between
two wires.
◼ Impulse - Spikes that result from power
lines, lighning, etc.

3.72
Signal to Noise Ratio (SNR)
◼ To measure the quality of a system the
SNR is often used. It indicates the
strength of the signal wrt the noise
power in the system.
◼ It is the ratio between two powers.
◼ It is usually given in dB and referred to
as SNRdB.

3.73
The power of a signal is 10 mW and the
power of the noise is 1 μW; what are the
values of SNR and SNRdB ?
Solution
The values of SNR and SNRdB can be
calculated as follows:
Example 3.31

3.74
The values of SNR and SNRdB for a
noiseless channel are
Example 3.32
We can never achieve this ratio in real life;
it is an ideal.

3.75
Figure 3.30 Two cases of SNR: a high SNR and a low SNR

3.76
3-5 DATA RATE LIMITS
A very important consideration in data communications is
how fast we can send data, in bits per second, over a
channel. Data rate depends on three factors:
1. The bandwidth available
2. The level of the signals we use
3. The quality of the channel (the level of noise)
Noiseless Channel: Nyquist Bit Rate
Noisy Channel: Shannon Capacity
Using Both Limits

3.77
Noiseless Channel: Nyquist Bit Rate
-Theorotical maximum bit rate
L=number of signal levels used to
represent data

3.78
Increasing the levels of a signal may
reduce the reliability of the system.
Note

3.79
Consider a noiseless channel with a bandwidth of 3000
Hz transmitting a signal with two signal levels. The
maximum bit rate can be calculated as
Example 3.34

3.80
Consider the same noiseless channel transmitting a
signal with four signal levels (for each level, we send 2
bits). The maximum bit rate can be calculated as
Example 3.35

3.81
Noisy Channel: Shannon Capacity
Theoretical data rate for a nosiy channel

3.82
Consider an extremely noisy channel in which the value
of the signal-to-noise ratio is almost zero. In other words,
the noise is so strong that the signal is faint. For this
channel the capacity C is calculated as
Example 3.37
This means that the capacity of this
channel is zero regardless of the
bandwidth. In other words, we cannot
receive any data through this channel.

3.83
We can calculate the theoretical highest bit rate of a
regular telephone line. A telephone line normally has a
bandwidth of 3000. The signal-to-noise ratio is usually
3162. For this channel the capacity is calculated as
Example 3.38
This means that the highest bit rate for a
telephone line is 34.860 kbps. If we want to
send data faster than this, we can either
increase the bandwidth of the line or
improve the signal-to-noise ratio.

3.84
We have a channel with a 1-MHz
bandwidth. The SNR for this channel is 63.
What are the appropriate bit rate and
signal level?
Solution
First, we use the Shannon formula to find
the upper limit.
Using both levels

3.85
The Shannon formula gives us 6 Mbps, the
upper limit. For better performance we
choose something lower, 4 Mbps, for
example. Then we use the Nyquist formula
to find the number of signal levels.
Example 3.41 (continued)

3.86
The Shannon capacity gives us the
upper limit; the Nyquist formula tells us
how many signal levels we need.
Note

3.87
3-6 PERFORMANCE
One important issue in networking is the
performance of the network—how good is it? In
this section, we introduce terms that we need for
future.
Bandwidth
Throughput
Latency (Delay)
Bandwidth-Delay Product

3.88
In networking, we use the term
bandwidth in two contexts.
❏ The first, bandwidth in hertz, refers
to
the range of frequencies in a
composite signal or the range of
frequencies that a channel can
pass.
❏ The second, bandwidth in bits per
Note

3.90
What is the propagation time if the
distance between the two points is 12,000
km? Assume the propagation speed to be
2.4 × 108 m/s in cable.
Solution
We can calculate the propagation time as
Example 3.45
The example shows that a bit can go over
the Atlantic Ocean in only 50 ms if there is
a direct cable between the source and the

Store-and-Forward Switching:
◼ Store-and-forward switching is a method of
switching data packets by the switching
device that receives the data frame and
then checks for errors before forwarding the
packets. It supports the efficient
transmission of non-corrupted frames. It is
generally used in telecommunication
networks.
1.91

Store-and-Forward Switching:
◼ In store-and-forward switching, the switching device waits
to receive the entire frame and then stores the frame in
the buffer memory. Then the frame is checked for errors by
using CRC(Cyclic Redundancy Check) if the error is found
then the packet is discarded else it is forwarded to the next
device.
1.92

Circuit switching Vs Packet
Switching
1.93

Reference:Chapter 7
Transmission Media

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