DCN UNIT 2 QUESTION BANK

Q. Illustrate analog and digital signal

A. What is Signal?
A Signal is an electromagnetic wave that is used to communicate system-to-
system by sending data from one network to another network is basically
known as “Signal”.

In a computer network there are mainly two types of signals are:

1. Analog Signal
2. Digital Signal
What is Analog Signal?
An Analog signal is a signal which is continuous and has a time-varying
feature. It is a representation of time-varying quantity. For example, the
Human voice can be considered an analog signal because the signal of the
human voice flows in a continuous manner.

In other words, we can say that the analog signal is represented by the
continuous variable which transmits the information/data as a response to
physical phenomenon. It is known as an “Analog Signal”

Examples of digital signals are Temperature, Pressure, Flow Measurement,

etc.

Types of Analog Signal

1. Simple Analog Signal

2. Composite Analog Signal
What is Digital Signal?
As the word suggests “Digital” which means it describes the electronic
technology that generates signals. It is a physical signal that is represented by
two discrete values “0” & “1”, these discrete values are known as bitstream.

In simple words, we can say that the binary signals are known as “Digital
signals” where the signals are converted into a small bit form which is
represented by a series of “0” & “1”.

Examples of digital signals are Motor, Digital Phones, Digital pens, etc

Q. Define following terms: 1. Frequency 2. Wavelength 3. Bandwidth

A. . Frequency

Frequency refers to the number of cycles completed by the wave in one second.
Period refers to the time taken by the wave to complete one second.

Wavelength

The wavelength of a signal refers to the relationship between frequency (or period)
and propagation speed of the wave through a medium.

The wavelength is the distance a signal travels in one period.

It is given by Wavelength = Propagation Speed X Period OR Wavelength

=Propagation Speed X 1 / Frequency
It is represented by the symbol : λ (pronounced as lamda) It is measured in
micrometers

It varies from one medium to another.

Bandwidth can be defined as the portion of the electromagnetic spectrum occupied

by the signal

It may also be defined as the frequency range over which a signal is transmitted.

Different types of signals have different bandwidth. Ex. Voice signal, music signal,
etc

Bandwidth of analog and digital signals are calculated in separate ways; analog
signal bandwidth is measured in terms of its frequency (hz) but digital signal
bandwidth is measured in terms of bit rate (bits per second, bps)

Bandwidth of signal is different from bandwidth of the medium/channel

Q. Describe causes of transmission impairment.

A. 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:

 Means loss of energy -> weaker signal

 When a signal travels through a medium it loses energy overcoming the

resistance of the medium

 That is why a wire carrying electric signals gets warm, if not hot, after a while.
Some of the electrical energy in the signal is converted to heat.

 Amplifiers are used to compensate for this loss of energy by amplifying the
signal.

 To show the loss or gain of energy the unit “decibel” is used.

dB = 10log10P2/P1

P1 - input signal

P2 - output signal

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.

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, lightning, etc.

 Q. Describe following: 1. Nyquist’s theorem 2. Shannon’s theorem

A. 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)

Nyquist's Theorem:
 Definition: Nyquist's theorem, also known as the Nyquist-Shannon sampling
theorem, is a fundamental concept in signal processing. It provides a guideline
for the minimum sampling rate required to accurately reconstruct a
continuous signal from its sampled version.
 Statement: The theorem states that in order to accurately reconstruct a
signal, the sampling rate must be at least twice the highest frequency present
in the signal. Mathematically, the Nyquist sampling rate (Fs) is given by:
��≥2×Maximum Signal FrequencyFs≥2×Maximum Signal Frequenc
y
 Implications: If the sampling rate is less than the Nyquist rate, a phenomenon
known as aliasing occurs, where high-frequency components are
misrepresented as lower-frequency components. Nyquist's theorem is crucial
in digital signal processing and the design of systems such as audio and video
recording to ensure that the original signal can be faithfully reconstructed
from its digital representation.
 Nyquist theorem states that for a noiseless channel:

C = 2 B log2L

C= capacity in bps

B = bandwidth in Hz

Shannon's Theorem:
 Definition: Shannon's theorem, also known as the Nyquist-Shannon
communication theory, is a principle related to the transmission of
 information in communication systems. It establishes the maximum data rate
that can be achieved over a communication channel without error.
 Statement: Shannon's theorem states that the channel capacity (C), measured
in bits per second, is determined by the bandwidth (B) and the signal-to-noise
ratio (SNR) of the channel. Mathematically, the channel capacity is given by:
C=B×log2(1+SNR)
 Implications: The theorem indicates that for a given bandwidth, the capacity
of the channel can be increased by improving the signal-to-noise ratio. This
theorem is fundamental in the design and optimization of communication
systems, guiding engineers in maximizing data transmission rates while
dealing with the limitations imposed by the channel's bandwidth and noise.

Q. Consider a noiseless channel with a bandwidth of 3000 Hz

transmitting a signal with four signal levels. Calculate the
BitRate.

A.

Q. Consider a telephone line with a bandwidth of 3000. The signal-to-noise ratio is usually
3162. What is the capacity of channel?

A.

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.

Q. Define following terms: 1. Throughput 2. Latency 3. Bandwidth-Delay Product

1. A. Throughput:
 Definition: Throughput refers to the actual amount of data that can be
transmitted over a communication channel in a given amount of time. It
represents the effective data transfer rate, accounting for various factors such
as network congestion, protocol overhead, and retransmissions.
 Measurement: Throughput is typically measured in bits per second (bps),
kilobits per second (kbps), megabits per second (Mbps), or other similar units.
  Example: If a network connection has a theoretical bandwidth of 100 Mbps,
the actual throughput might be lower due to factors like network overhead
and congestion.
2. Latency:
 Definition: Latency, also known as delay, is the time it takes for a packet of
data to travel from the source to the destination in a network. It is often
broken down into different components such as transmission delay,
propagation delay, queuing delay, and processing delay.
 Components:
 Transmission Delay: Time taken to push all the packet's bits into the
link.
 Propagation Delay: Time taken for a signal to travel from the source
to the destination.
 Queuing Delay: Time spent in buffers waiting to be transmitted.
 Processing Delay: Time taken for the routers or switches to process
the packet.
 Example: If a packet takes 50 milliseconds to travel from the source to the
destination, the latency for that packet is 50 milliseconds.
3. Bandwidth-Delay Product (BDP):
 Definition: The Bandwidth-Delay Product is a measure used to assess the
amount of data that can be "in flight" in the network at a given time. It is the
product of the available bandwidth (measured in bits per second) and the
round-trip time (RTT) or latency (measured in seconds).
 Formula: BDP = Bandwidth × RTT
 Significance: The BDP helps in determining the optimal window size for data
transmission, balancing the amount of data in transit with the capacity of the
network. It is crucial in optimizing the performance of data transfers,
particularly in high-speed, high-latency networks.

Q. What is digital to digital conversion? Enlist various digital to digital conversion techniques

A. Data or information can be stored in two ways, analog and

digital. For a computer to use the data, it must be in discrete
digital form.Similar to data, signals can also be in analog and
digital form. To transmit data digitally, it needs to be first
converted to digital form.

Digital-to-Digital Conversion
This section explains how to convert digital data(Strings of 1’s
and 0’s) into digital signals. It can be done in two ways, line
coding and block coding. For all communications, line coding is
necessary whereas block coding is optional.

Line Coding
The process for converting digital data into digital signal is said to
be Line Coding. Digital data is found in binary format.It is
represented (stored) internally as series of 1s and 0s.

Block Coding
To ensure accuracy of the received data frame redundant bits are
used. For example, in even-parity, one parity bit is added to
make the count of 1s in the frame even. This way the original
number of bits is increased. It is called Block Coding.
Block coding is represented by slash notation, mB/nB.Means, m-
bit block is substituted with n-bit block where n > m. Block
coding involves three steps:

 Division,
 Substitution
 Combination.

After block coding is done, it is line coded for transmission.

Q. Explain line coding briefly. Enlist different line coding schemes.

A. Line Coding
The process for converting digital data into digital signal is said to
be Line Coding. Digital data is found in binary format.It is
represented (stored) internally as series of 1s and 0s.
Unipolar:

 All signal levels are on one side of the time axis - either
above or below. Only one voltage level other than zero.
 NRZ - Non Return to Zero scheme is an example of this
code. The signal level does not return to zero during a
symbol transmission.
 It is simple but costly in power consumption.

Unipolar encoding schemes use single voltage level to represent

data. In this case, to represent binary 1, high voltage is
transmitted and to represent 0, no voltage is transmitted. It is
also called Unipolar-Non-return-to-zero, because there is no rest
condition i.e. it either represents 1 or 0.
Polar: Polar encoding scheme uses multiple voltage levels to
represent binary values. Polar encodings is available in four
types:

 Polar NRZ: The voltages are on both sides of the time axis.
Two voltage levels other than zero.
 Polar NRZ scheme can be implemented with two voltages.
E.g. +V for 1 and -V for 0.
 There are two versions:
 NZR - Level (NRZ-L) - positive voltage for one symbol
and negative for the other
 NRZ - Inversion (NRZ-I) - the change or lack of change
in polarity determines the value of a symbol. E.g. a “1”
symbol inverts the polarity a “0” does not.
 It uses two different voltage levels to represent binary
values. Generally, positive voltage represents 1 and
negative value represents 0. It is also NRZ because there is
no rest condition.
 NRZ scheme has two variants: NRZ-L and NRZ-I

NRZ-L changes voltage level at when a different bit is

encountered whereas NRZ-I changes voltage when a 1 is
encountered.
For L->0=Hero and 1=zero

For I->0=No transition and 1= transition

Polar – RZ: Problem with NRZ is that the receiver cannot

conclude when a bit ended and when the next bit is started, in
case when sender and receiver’s clock are not synchronized.

RZ uses three voltage levels, positive voltage to represent 1,

negative voltage to represent 0 and zero voltage for none.
Signals change during bits not between bits.

 The Return to Zero (RZ) scheme uses three voltage values.

+, 0, -.
 Each symbol has a transition in the middle. Either from high
to zero or from low to zero.
 This scheme has more signal transitions (two per symbol)
and therefore requires a wider bandwidth.
 More complex as it uses three voltage level. It has no error
detection capability.
  Polar - Biphase: Manchester(Split Phase) and Differential
Manchester: Manchester
This encoding scheme is a combination of RZ and NRZ-L. Bit
time is divided into two halves. It transits in the middle of
the bit and changes phase when a different bit is
encountered.
 Differential Manchester
This encoding scheme is a combination
of RZ and NRZ-I. It also transit at the middle of the bit but
changes phase only when 1 is encountered.

 Manchester coding consists of combining the NRZ-L and RZ

schemes.
 Every symbol has a level transition in the middle: from
high to low or low to high. Uses only two voltage
levels.
 Differential Manchester coding consists of combining the
NRZ-I and RZ schemes.

Every symbol has a level transition in the middle. But the level at
the beginning of the symbol is determined by the symbol value.
One symbol causes a level change the other does not.
For Manchester-> 0= +ve to –ve and 1= -ve to +ve

For Diff. Man. -> 0=transition and 1=No transition

Bipolar Encoding

Bipolar encoding uses three voltage levels, positive, negative and

zero. Zero voltage represents binary 0 and bit 1 is represented by
altering positive and negative voltages.

 Code uses 3 voltage levels: - +, 0, -, to represent the

symbols (note not transitions to zero as in RZ).
 Voltage level for one symbol is at “0” and the other
alternates between + & -.
 Bipolar Alternate Mark Inversion (AMI) - the “0” symbol is
represented by zero voltage and the “1” symbol alternates
between +V and -V.
 Pseudoternary is the reverse of AMI.
For AMI-> 0= 0 line(flat) and 1= change polarity each time

Pseudoternary= opposite of AMI

Representing Multilevel Codes:

 We use the notation mBnL, where m is the length of the

binary pattern, B represents binary data, n represents the
length of the signal pattern and L the number of levels.
 L = B binary, L = T for 3 ternary, L = Q for 4 quaternary.
Q. Describe block coding digital to digital conversion technique

A. Block coding is a method used in digital electronics to encode data into a

specific format. The purpose of block coding is to add redundant information
to the data, which can be used to detect and correct errors that may occur
during transmission or storage. Block coding is often used in conjunction with
error correction codes (ECCs) to provide a more robust way of transmitting
and storing data.

In summary, block coding is a method used in digital electronics to encode

data into a specific format, adding redundant information to the data to detect
and correct errors that may occur during transmission or storage. There are
several types of block codes, including Hamming codes, Reed-Solomon
codes, and BCH codes, and they offer many benefits in terms of data
accuracy and reliability, but also come with some disadvantages, such as
increased complexity and overhead.
Conversion of Digital Data to Digital Signal involves three techniques:
1. Line Coding
2. Block Coding
3. Scrambling
Out of which Line coding is always needed, block coding and scrambling
may or may not be needed. Block coding helps in error detection and re-
transmission of the signal. It is normally referred to as mB/nB coding as it
replaces each m-bit data group with an n-bit data group (where n>m). Thus,
its adds extra bits (redundancy bits) which helps in synchronization at
receiver’s and sender’s end and also providing some kind of error detecting
capability. It normally involves three steps: division, substitution, and
combination. In the division step,a sequence of bits is divided into groups of
m-bits. In the substitution step, we substitute an m-bit group for an n-bit
group. Finally, the n-bit groups are combined together to form a stream
which has more bits than the original bits. Examples of mB/nB coding: 4B/5B
(four binary/five binary ) – This coding scheme is used in combination with
NRZ-I. The problem with NRZ-I was that it has a synchronization problem for
long sequences of zeros. So, to overcome it we substitute the bit stream
from 4-bit to 5-bit data group before encoding it with NRZ-I. So that it does
not have a long stream of zeros.

At the receiver, the NRZ-I encoded digital signal is first decoded into a
stream of bits and then decoded again to remove the redundancy
bits. Drawback – Though 4B/5B encoding solves the problem of
synchronization,it increases the signal rate of NRZ-L.Moreover,it does not
solve the DC component problem of NRZ-L.
Q. What is analog to digital conversion? Enlist various analog to digital conversion
techniques.

A. A digital signal is superior to an analog signal because it is more robust to noise and
can easily be recovered, corrected and amplified. For this reason, the tendency today is to
change an analog signal to digital data. In this section we describe two techniques, pulse
code modulation and delta modulation.

Analog data is a continuous stream of data in the wave form

whereas digital data is discrete. To convert analog wave into
digital data, we use Pulse Code Modulation (PCM).
The most common technique to change an analog signal to digital data is
called pulse code modulation (PCM). A PCM encoder has the following three
processes:
1. Sampling
2. Quantization
3. Encoding
Low pass filter : The low pass filter eliminates the high frequency
components present in the input analog signal to ensure that the input signal
to sampler is free from the unwanted frequency components.This is done to
avoid aliasing of the message signal

Sampling – The first step in PCM is sampling. Sampling is a process of

measuring the amplitude of a continuous-time signal at discrete instants,
converting the continuous signal into a discrete signal. There are three
sampling methods: (i) Ideal Sampling: In ideal Sampling also known as
Instantaneous sampling pulses from the analog signal are sampled. This is

an ideal sampling method and cannot be easily implemented. (ii) Natural

Sampling: Natural Sampling is a practical method of sampling in which
pulse have finite width equal to T.The result is a sequence of samples that
retain the shape of the analog signal.

 Ideal - an impulse at each sampling instant

 Natural - a pulse of short width with varying amplitude
 Flattop - sample and hold, like natural but with single
amplitude value

) Flat top sampling: In comparison to natural sampling flat top sampling can
be easily obtained. In this sampling technique, the top of the samples
remains constant by using a circuit. This is the most common sampling
method used.
Nyquist Theorem: One important consideration is the sampling rate or
frequency. According to the Nyquist theorem, the sampling rate must be at
least 2 times the highest frequency contained in the signal. It is also known
as the minimum sampling rate and given by: Fs =2*fh

1. Quantization – The result of sampling is a series of pulses with amplitude

values between the maximum and minimum amplitudes of the signal. The
set of amplitudes can be infinite with non-integral values between two
limits. The following are the steps in Quantization:
1. We assume that the signal has amplitudes between Vmax and Vmin
 2. We divide it into L zones each of height d where, d= (Vmax- Vmin)/ L

3. The value at the top of each sample in the graph shows the actual
amplitude.
4. The normalized pulse amplitude modulation(PAM) value is calculated
using the formula amplitude/d.
5. After this we calculate the quantized value which the process selects
from the middle of each zone.
6. The Quantized error is given by the difference between quantized
value and normalised PAM value.
7. The Quantization code for each sample based on quantization levels
at the left of the graph.
2. Encoding – The digitization of the analog signal is done by the encoder.
After each sample is quantized and the number of bits per sample is
decided, each sample can be changed to an n bit code. Encoding also
minimizes the bandwidth used. Note that the number of bits for each
sample is determined from the number of quantization levels. If the
number of quantization levels is L, the number of bits is n bit = log 2 L.
b. DELTA MODULATION :

Since PCM is a very complex technique, other techniques have been

developed to reduce the complexity of PCM. The simplest is delta
Modulation. Delta Modulation finds the change from the previous
value. Modulator – The modulator is used at the sender site to create a
stream of bits from an analog signal. The process records a small positive
change called delta. If the delta is positive, the process records a 1 else the
process records a 0. The modulator builds a second signal that resembles a
staircase. The input signal is then compared with this gradually made

staircase signal.
We have the following rules for output:
1. If the input analog signal is higher than the last value of the staircase
signal, increase delta by 1, and the bit in the digital data is 1.
2. If the input analog signal is lower than the last value of the staircase
signal, decrease delta by 1, and the bit in the digital data is 0.
Demodulator – The demodulator takes the digital data and, using the
staircase maker and the delay unit, creates the analog signal. The created
analog signal, however, needs to pass through a low-pass filter for
smoothing.

c. ADAPTIVE DELTA MODULATION:

The performance of a delta modulator can be improved significantly by

making the step size of the modulator assume a time-varying form. A larger
step-size is needed where the message has a steep slope of modulating
signal and a smaller step-size is needed where the message has a small
slope. The size is adapted according to the level of the input signal. This
method is known as adaptive delta modulation (ADM).

Pulse Amplitude Modulation (PAM) is a modulation technique used in signal processing and
telecommunications to encode analog information within digital signals. In PAM, the
amplitude of a series of pulses is varied in proportion to the amplitude of an analog signal
being transmitted.

Q. Describe different transmission modes in digital transmission.

A.