Home / Study Materials / KTU B.Tech S5 Lecture Notes Data Communication

KTU B.Tech S5 Lecture Notes Data Communication

KTU B.Tech S5 Lecture Notes Data Communication




KTU B.Tech S5 Lecture Notes Data Communication


Simplex, Half duplex and Full Duplex Transmission Modes
There are three modes of transmission simplex, half duplex, and full duplex. Transmission mode describes the direction, of flow of signal between two connected devices. The main difference between simplex, half duplex, and full duplex is that in a simplex mode of transmission the communication is unidirectional whereas, in the half-duplex mode of transmission the communication is two directional but the channel is alternately used by the both the connected device. On the other hand, in the full duplex mode of transmission, the communication is bi-directional, and the channel is used by both the connected device simultaneously.
Let us study the difference between simplex, half duplex, and full duplex with the help of comparison chart shown below.
Comparison chart BASIS FOR COMPARISON SIMPLEX HALF DUPLEX FULL DUPLEX Direction of Communication Communication is unidirectional. Communication is two-directional but, one at a time. Communication is two directional and done simultaneously. Send/Receive A sender can send data but, can not receive. A sender can send as well as receive the data but one at a time. A sender can send as well as receive the data simultaneously. Performance The half duplex and full duplex yields better performance than the Simplex. The full duplex mode yields higher performance than half duplex. Full duplex has better performance as it doubles the utilization of bandwidth.

Example Keyboard and monitor. Walkie-Talkies. Telephone.
Definition of Simplex
In a simplex transmission mode, the communication between sender and receiver occur only in one direction. That means only the sender can transmit the data, and receiver can only receive the data. The receiver can not reply in reverse to the sender. Simplex is like a one-way road in which the traffic travels only in one direction, no vehicle from opposite direction is allowed to enter. The entire channel capacity is only utilized by the sender.
You can better understand the simplex transmission mode with an example of keyboard and monitor. The Keyboard can only transmit the input to the monitor, and the monitor can only receive the input and display it on the screen. The monitor can not transmit any information back to the keyboard.
Definition of Half Duplex
In a half-duplex transmission mode, the communication between sender and receiver occurs in both the directions but, one at a time. The sender and receiver both can transmit and receive the information but, only one is allowed to transmit at a time. Half duplex is still a one way road, in which a vehicle traveling in opposite direction of the traffic has to wait till the road is empty. The entire channel capacity is utilized by the transmitter, transmitting at that particular time.
Half duplex can be understood with an example of walkie-talkies. As the speaker at both the end of walkie-talkies can speak but they have to speak one by one. Both can not speak simultaneously.
Definition of Full Duplex
In a full duplex transmission mode, the communication between sender and receiver can occur simultaneously. Sender and receiver both can transmit and receive simultaneously at the same time. The full duplex transmission mode is like a two way road in which traffic can flow in both the direction at the same time. The entire capacity of the channel is shared by both the transmitted signal traveling in opposite direction. Sharing of the channel capacity can be achieved in two different ways. First, either you physically separate the link in two parts one for sending and other for receiving. Second, or you let the capacity of a channel to be shared by the two signals traveling in opposite direction.
Full duplex can be understood best, with an example of a telephone. When two people communicate over a telephone both are free to speak and listen at the same time.
Periodic Analog signals: Sine wave, phase, wavelength, time and frequency domain, bandwidth
 Both analog and digital signals can take one of two forms : periodic or non-periodic
 A Periodic signal complete a pattern within a measurable time span or time frame, and repeats that pattern over subsequent identical periods.
◦ Commonly used in analog signals, because they need
less bandwidth.
 A non-periodic signal changes without exhibiting a pattern or cycle that repeats over a time.
◦ Commonly used in digital signals, because they can represent variation in data.
A sine wave is the most fundamental form of
A Sine wave can be represented by three parameters:
•Peak Amplitude
•Phase Peak Amplitude
◦ The peak amplitude of a signal is the absolute value of its highest intensity, proportional to the energy it carries.
◦ Frequency refers to the number of period in 1sec.
◦ Formally expressed in Hertz(Hz), which is cycle per sec.
◦ Period refers to the amount of time , in seconds , a signal needs to complete 1 cycle.
◦ Period is the inverse of frequency and vice-versa.
a periodic analog signal

Normally measured in VOLTS.
Peak Amplitude
Time Time
◦ Phase describe the position of the waveform relative to time 0.
◦ Wave as something that can be shifted backward or forward along with time axis, phase describe the amount of that shift.
◦ Measured in degrees or radian A phase shift of 360 degree correspondence to a shift of a complete period.
A signal with frequency of 8 HZ
A signal with frequency of 3 HZ
 Wavelength binds the period or the frequency of a simple sine wave to the propagation speed of the medium
 It is the distance a simple signal can travel in one period
Wavelength=propagation speed*Period
Sine wave by using Time-Domain Plot
A sine wave in the time domain with peak value 5V and frequency 5Hz
Wave Length
Direction Propagation
Transmission medium at time t
Transmission medium at time
Frequency 5Hz
Peak Value: 5V
Sine wave by using Frequency-Domain Plot
 The range of frequencies contained in a composite signal is its bandwidth.
 It is normally a difference between two numbers.
◦ Example:
 If a composite signal contains frequencies between 1000 and 5000, its bandwidth is 5000-1000=4000
 The Bandwidth of a composite signal is the difference between the highest and the lowest frequencies contained in that signal.
Peak Value: 5V
A sine wave in the frequency domain with peak value 5V and frequency 5Hz
Bandwidth= 5000

Bandwidth= 5000

Transmission Impairment
This post is divided into two parts this is first part of this post to view second part click here.
With any communications system, it must be recognized that the received signal will differ from the transmitted signal due to various transmission impairments. For analog signals, these impairments introduce various random modifications that degrade the signal quality. For digital signals, bit errors are introduced: A binary 1 is trans- – formed into a binary 0 and vice versa. In this section, we examine the various impairments and comment on their effect on the information-carrying capacity of a communication link.
The most significant communication impairments are as shown in fig:
 Attenuation:
Attenuation means a loss of energy The strength of a signal falls off with distance over any transmission medium. For guided media, this reduction in strength, or attenuation, is generally logarithmic and is thus typically expressed as a constant number of decibels per unit distance. In fig. shows the effect of attenuation and amplification.
Fig-2: Attenuation
For unguided media, attenuation is a more complex function of distance and of the makeup of the atmosphere. Attenuation introduces three considerations for the transmission engineer. First, a received signal must have sufficient strength so that the electronic circuitry in the receiver can detect and interpret the signal. Second, the signal must maintain a level sufficiently higher than noise to be received without error. Third, attenuation is an increasing function of frequency.
 Distortion:
Distortion means that the signal changes its form or shape. Delay distortion is a phenomenon peculiar to guided transmission media. The distortion is caused by the fact that the velocity of propagation of a signal through a guided medium varies with frequency. For a bandlimited signal, the velocity tends to be highest near the center frequency and lower toward the two edges of the band.
Thus, various frequency components of a signal will arrive at the receiver at different times.
This effect is referred to as delay distortion, as the received signal is distorted due to variable delay in its components. The distortion effect as shown in fig-3.
Fig-3: Distortion
Delay distortion is particularly critical for digital data. Consider that a sequence of bits is being transmitted, using either analog or digital signals. Because of delay distortion, some of the signal components of one bit position will spill over into other bit positions, causing intersymbol interference, which is a major limitation to maximum bit rate over a transmission control. Equalizing techniques can also be used for delay distortion.
Noise is refers to any unwanted signal. For any data transmission event, the received signal will consist of the transmitted signal, modified by the various distortions imposed by the transmission system, plus additional unwanted signals that are inserted somewhere between transmission and reception; the latter, undesired signals are referred to as noise-a major limiting factor in communications system performance.
Fig-4: Noise
Channel capacity
 Definition: the rate at which data can be transmitted over a
given communication path, under given conditions
 Four important concepts in defining capacity
 Data rate
– In bits per second
– Rate at which data can be transmitted
 Bandwidth
– In Hertz
– Constrained by transmitter (regulations) and medium Noise
 Noise
 Bit Error Rate (BER
Nyquist formulation
 For noise-free channels:
C = 2W log 2 M
 W is the bandwidth, M is the number of
signaling levels
 Question: What is the capacity of a telephone
line modem that uses 8 signaling levels?
C = 2 ⋅ 3100 ⋅ 3 = 18600 bps
For a noiseless channel, Nyquist formula defines the theoretical maximum bit rate.
According to this formula, there are two means to enhance the data rate. First, if we use a large number of signaling levels M, the capacity increases logarithmically. But, there are practical limitations when choosing M. Thus, the receiver will decide much easier if it has to distinguish between only two signaling levels (M=2) than in the case of a much larger number of levels (e.g. M=64). By the other hand, another way to increase the data rate is by increasing the bandwidth. As already seen, bandwidth is always a scarce resource, limited by physical constraints and regulations.
Another example: We need to send information at a data rate of 256 kbps, over a
noiseless channel with 16KHz of bandwidth. How many signaling levels do we
Answer: log2 M=C/2W=256*103/2*16*103=8. It follows that M=28=256 levels.
Comment: This shows quite a large number of levels which are required, and the
receiver task is difficult. The reason behind is that, through quite a low bandwidth
we try to send a fairly high data rate.
Shannon’s Capacity formula.
One of the most important practical questions which arises when we are designing or using an information transmission or processing system is, “What is the Capacity of this system? — i.e. How much information can it transmit or process in a given time?” We formed a rough idea of how to answer this question in an earlier section of this set of webpages. We can now go on to obtain more well defined answer by deriving Shannon’s Equation. This equation allows us to precisely determine the information carrying capacity of any signal channel. Consider a signal which is being efficiently communicated (i.e. no redundancy) in the form of a time-dependant analog voltage, . The pattern of voltage variations during a specific time interval, T, allows a receiver to identify which one of a possible set of messages has actually been sent. At any two moments, & , during a message the voltage will be & . Using the idea of intersymbol influence we can say that since — there is no redundancy — the values of & will appear to be independent of one another provided that they’re far enough apart () to be worth sampling separately. In effect, we can’t tell what one of the values is just from knowing the other. Of course, for any specific message, both and are determined in advance by the content of that particular message. But the receiver can’t know which of all the possible messages has arrived until it has arrived. If the receiver did know in advance which voltage pattern was to be transmitted then the message itself wouldn’t provide any new information! i.e. the receiver wouldn’t know any more after its arrival than before. This leads us to the remarkable conclusion that a signal which is efficiently
communicating information will vary from moment to moment in an unpredictable, apparently random, manner. An efficient signal looks very much like random noise! This, of course, is why random noise can produce errors in a received message. The statistical properties of an efficiently signalled message are similar to those of random noise. If the signal and noise were obviously different the receiver could easily separate the noise from the signal and avoid making any errors. To detect and correct errors we therefore have to make the real signal less ‘noise-like’. This is what we’re doing when we use parity bits to add redundancy to a signal. The redundancy produces predictable relationships between different sections of the signal pattern. Although this reduces the system’s information carrying efficiency it helps us distinguish signal details from random noise. Here, however, we’re interested in discovering the maximum possible information carrying capacity of a system. So we have to avoid any redundancy and allow the signal to have the ‘unpredictable’ qualities which make it statistically similar to random noise. The amount of noise present in a given system can be represented in terms of its mean noise power
where R is the characteristic impedance of the channel or system and is the rms noise voltage. In a similar manner we can represent a typical message in terms of its average signal power
where is the signal’s rms voltage. A real signal must have a finite power. Hence for a given set of possible messages there must be some maximum possible power level. This means that the rms signal voltage is limited to some range. It also means that the instantaneous signal voltage must be limited and can’t be beyond some specific range, . A similar argument must also be true for noise. Since we are assuming that the signal system is efficient we can expect the signal and noise to have similar statistical properties. This implies that if we watched the signal or noise for a long while we’d find that
their level fluctuations had the same peak/rms voltage ratio. We can therefore say that, during a typical message, the noise voltage fluctuations will be confined to some range
where the form factor, , (ratio of peak to rms levels) can be defined from the signal’s properties as
When transmitting signals in the presence of noise we should try to ensure that S is as large as possible so as to minimise the effects of the noise. We can therefore expect that an efficient information transmission system will ensure that, for every typical message, S is almost equal to some maximum value, . This implies that in such a system, most messages will have a similar power level. Ideally, every message should have the same, maximum possible, power level. In fact we can turn this argument on its head and say that only messages with mean powers similar to this maximum are ‘typical’. Those which have much lower powers are unusual — i.e. rare. 8.2 Shannon’s Equation.
The signal and noise are uncorrelated — that is, they are not related in any way which would let us predict one of them from the other. The total power obtained, , when combining these uncorrelated, apparently randomly varying quantities is given by
i.e. the typical combined rms voltage, , will be such that
Since the signal and noise are statistically similar their combination will have the same form factor value as the signal or noise taken by itself. We can therefore expect that the combined signal and noise will generally be confined to a voltage
range . Consider now dividing this range into bands of equal size. (i.e. each of these bands will cover .) To provide a different label for each band we require symbols or numbers. We can therefore always indicate which band the voltage level occupies at any moment in terms of a b-bit binary number. In effect, this process is another way of describing what happens when we take digital samples with a b-bit analog to digital convertor working over a total range . There is no real point in choosing a value for b which is so large that is smaller than . This is because the noise will simply tend to randomise the actual voltage by this amount, making any extra bits meaningless. As a result the maximum number of bits of information we can obtain regarding the level at any moment will given by
which can be rearranged to produce
If we make M, b-bit measurements of the level in a time, T, then the total number of bits of information collected will be
This means that the information transmission rate, I, bits per unit time, will be
From the Sampling Theorem we can say that, for a channel of bandwidth, B, the highest practical sampling rate, , at which we can make independent measurements or samples of a signal will be
Combining expressions 8.11 & 8.12 we can therefore conclude that the maximum information transmission rate, C, will be
This expression represents the maximum possible rate of information transmission through a given channel or system. The maximum rate we can transmit information is set by the bandwidth, the signal level, and the noise level. C is therefore called the channel’s information carrying Capacity. Expression 8.13 is called Shannon’s Equation after the first person to derive it.
• Transmission Media
– Physical path between transmitter and receiver
– Guided or unguided (wireless)
– Communication is in the form of electromagnetic
– Characteristics and quality of data transmission
are determined by characteristics of medium and
– In guided media, medium characteristics is more
important, whereas in unguided media, signal
characteristics is more important
1. Guided Transmission Media
• Twisted Pair
– The oldest, least expensive, and mostcommonly used media
– Pair of insulated wires twisted together toreduce susceptibility to interference (two straight parallel wires tend to act as an antenna and pick up extraneous signals
– Quite highly susceptible to noise & interference
– Up to 250 kHz analog and few Mbps digitalsignaling ( for long-distance point-to-point signaling
– Need repeater every 2-3 km (digital), andamplifier every 5-6 km (analog)
– May be already installed (telephone usage)
– Much efforts are undergoing to use it for high-speed (10-100 Mbps) LAN
• Coaxial Cable
– Most versatile medium
• LANs, Cable TV, Long-distance telephones, VCR-
to-TV connections
– Noise immunity is good
– Very high channel capacity
• few 100 MHz / few 100 Mbps
– Need repeater/amplifier every few kilometer or so
about the same as with twisted pair
Point-to-point transmission characteristics of guided media
Total data rate
Twisted pair
Coaxial cable

• Optical Fiber
– Flexible, thin (few to few hundred
m), very pure
glass / plastic fiber capable of conducting optical
– Extremely high bandwidth: capable of

– Very high noise immunity, resistant to
electromagnetic interference
– Does not radiate energy/cause interference
– Very light
– Need repeaters only 10’s or 100 km apart
– Very difficult to tap
• Better security but multipoint not easy
– Need optical-electrical interface (more expensive
than electrical interface)
•Principle of optical fiber transmission
–Based on the principle of
total internal
Interface between
two media A and B
Incident light
Reflected light
Refracted light
, medium B (water) has a higher optical
density than medium A (air)
–Index of refraction is defined by cos
–In case the index of refraction < 1
is less than a certain critical angle, there is no
refracted light. I.e., all the light is reflected.
This is what makes fiber optics work.
–The cladding surrounding the core is also
glass but is optically less dense than the core
• Three types of fiber transmission
– Step index multimode
• Variety of angles that reflect. Each angle defines a
path or a mode
• Limited data rate due to the different path lengths
– Single mode
• The diameter of the core is reduced to the order of
wavelength s.t. only a single angle or mode can
• Superior performance
– Graded index multimode
• Use the fact that speed of light depends on the
medium; light travels faster through less optically
dense media
• The boundary between core and cladding is not
sharply defined; Moving out radially from the core,
the material becomes gradually less dense
A travels a greater distance
but faster than B
Typical fiber characteristics
2. Wireless Transmission
• (Terrestrial) Microwave
– Typically used where laying a cable is notpractical (No right-of-way needed)
– Parabolic dish shaped antenna ( ≈10 ft dia) transmits/receives electromagnetic waves in the
2-40 GHz range
– Travels in a straight line (line-of-sightpropagation)
– Maximum distance bet antenna in km
d = 7.14 (4 3)h h: antenna ht in meters
– High data rates: 100’s Mbps
– Attenuation (4 d) 2 d: distance
10 log dB
λ: wavelength
– Repeaters spaced 10 – 100 km apart
– Applications
• Long-distance telephone communication
Parabolic arc
Parabola’s focus
• Satellite Microwave (Cont’d)
– VSAT (Very Small Aperture System)
• For business data applications requiring high data
rates for short periods of time (National Weather
Service, news services, credit card verification,
automatic tellers, car rental agencies, …)
• Commonly connects a central location with many
remote ones
• Communication between two sites is via a satellite
and allows a low-cost small antenna dishes (

5 ft)
• (Broadcast) Radio
– Electromagnetic wave in the range 30MHz ~
– Omnidirectional
– As with microwave,
d = 7.14 (4 3)h h: antenna ht in meters
4 d) 2 d: distance Attenuation = 10 log dB
λ: wavelength
– Less attenuation than microwave since λ is larger
• Infrared
– For short-range communication
• Remote controls for TVs, VCRs, and stereos
• Indoor wireless LANs
– Do not pass through solid walls
• Better security and no interference (with a similar system in adjacent rooms)
– No government license is needed
– Cannot be used outdoors (due to the sunshine)
Space Waves, also known as direct waves, are radio waves that travel directly from the transmitting antenna to the receiving antenna. In order for this to occur, the two antennas must be able to ―see‖ each other; that is there must be a line of sight path between them. The diagram on the next page shows a typical line of sight. The maximum line of sight distance between two antennas depends on the height of each antenna. If the heights are measured in feet, the maximum line of sight, in miles, is given by:
Because a typical transmission path is filled with buildings, hills and other obstacles, it is possible for radio waves to be reflected by these obstacles, resulting in radio waves that arrive at the receive antenna from several different directions. Because the length of each path is different, the waves will not arrive in phase. They may reinforce each other or cancel each other, depending on the phase differences. This situation is known as multipath propagation. It can cause major distortion to certain types of signals. Ghost images seen on broadcast TV signals are the result of multipath – one picture arrives slightly later than the other and is shifted in position on the screen. Multipath is very troublesome for mobile communications. When the transmitter and/or receiver are in motion, the path lengths are continuously changing and the signal fluctuates wildly in amplitude. For this reason, NBFM is used almost exclusively for mobile communications. Amplitude variations caused by multipath that make AM unreadable are eliminated by the limiter stage in an NBFM receiver.
An interesting example of direct communications is satellite communications. If a satellite is placed in an orbit 22,000 miles above the equator, it appears to stand still in the sky, as viewed from the ground. A high gain antenna can be pointed at
the satellite to transmit signals to it. The satellite is used as a relay station, from which approximately ¼ of the earth‘s surface is visible. The satellite receives signals from the ground at one frequency, known as the uplink frequency, translates this frequency to a different frequency, known as the downlink frequency, and
retransmits the signal. Because two frequencies are used, the reception and transmission can happen simultaneously. A satellite operating in this way is known as a transponder. The satellite
has a tremendous line of sight from its vantage point in space and many ground stations can communicate through a single satellite.
Sky-Wave or Skip Propagation
Sky Waves
Radio waves in the LF and MF ranges may also propagate as ground waves, but suffer significant losses, or are attenuated, particularly at higher frequencies. But as the ground wave mode fades out, a new mode develops: the sky wave. Sky waves are reflections from the ionosphere. While the wave is in the ionosphere, it is strongly bent, or refracted, ultimately back to the ground. From a long distance away this appears as a reflection. Long ranges are possible in this mode also, up to hundreds of miles. Sky waves in this frequency band are usually only possible at night, when the concentration of ions is not too great since the ionosphere also
tends to attenuate the signal. However, at night, there are just enough ions to reflect the wave but not reduce its power too much.
Figure 14
The HF band operates almost exclusively with sky waves. The higher frequencies have less attenuation and less refraction in the ionosphere as compared to MF. At the high end, the waves completely penetrate the ionosphere and become space waves. At the low end, they are always reflected. The HF band operates with both these effects almost all of the time. The characteristics of the sky wave propagation depend on the conditions in the ionosphere which in turn are dependent on the activity of the sun. The ionosphere has several well-defined regions in altitude.
Figure 15
D-region: about 75-95 km. Relatively weak ionization. Responsible for strong absorption of MF during daylight E-region: 95-150 km. An important player in ionospheric scatter of VHF. Fregion: 150-400 km. Has separate F1 and F2 layers during the day. The strongest concentration of ions. Responsible for reflection of HF radio waves. Since the propagation characteristics depend on frequency, several key frequencies can de defined: Critical frequency: The minimum frequency that will penetrate the ionosphere at vertical incidence. The critical frequency increases during the daylight and decrease at night. At other angles, the wave will be reflected back. At frequencies above the critical frequency, some range of waves from vertical incidence and down will become space waves. This will cause a gap in coverage on the ground known as a skip zone. In figure xx, the skip zone extends to about 1400 miles. The transmitted frequency was 5 MHz and the critical frequency was 3 MHz in this example. Maximum Useable Frequency (MUF): defined for two stations. The maximum frequency that will reflect back to the receiving station from the transmitter. Beyond the MUF, the wave will become a space wave. At MUF the skip zone extends to just short of the receiver. In figure xx, the MUF for a receiver at 1400 miles is 5 MHz. Lowest Useable Frequency (LUF): again defined for two stations. At low frequencies, the signal will be attenuated before it can be reflected. The LUF increases with sunlight and is a
maximum near noon. Optimum Frequency for Traffic (OFT): for two stations, taking into account the exact conditions in the ionosphere, there will be the perfect frequency that gives the strongest signal. This can be predicted by powerful
modeling programs and is the best guarantee of success in HF. The diurnal variation if HF propagation is characterized a simple rule-ofthumb: the frequency follows the sun. At noon, the OFT is generally higher than at night.
Line of Sight
In the VHF band and up, the propagation tends to straighten out into line-of-sight(LOS) waves. However the frequency is still low enough for some significant effects.

KTU B.Tech S5 Lecture Notes Data Communication


Check Also


KTU B.Tech Lecture Notes WATER RESOURCES ENGINEERING   MODULE I Hydrologic cycle-precipitation-mechanism, ...

KTU B.Tech S5 Lecture Notes Geomatics

KTU B.Tech S5 Lecture Notes Geomatics CE307 Geomatics    CE 307  GEOMATICS  ...