Data Communication - PowerPoint Presentation

Slide1

Data Communication

Muhammad Waseem Iqbal

Lecture #

09

Spring

-2016Slide2

Acknowledgments

These Lecture slides contain material from Behrouz

A. Forouzan, Data Communications and Networks, 4th Editionn and William Stallings, Data & Computer Communication, 8

th edition

Slide3

Transmission Impairments

Signals travel through the transmission media, which are not perfect

The imperfections cause impairment in signalThis means that the signal at the beginning and end of the medium are not same

There are three types of impairment usually occur

Attenuation

Distortion

NoiseSlide4

Transmission Impairments

For analog signals, these impairments introduce various random modifications that degrade the signal quality

For digital signals, bit errors are introducedSlide5

Transmission

ImpairentsAttenuation

Attenuation means loss of energy (weak signal)It is the progressive reduction in amplitude of a signal as it travels farther from the point of

origin

When a signal travels through a medium, it loses some of its energy so that it can overcome the resistance of the medium

That is why a wire carrying electrical signals gets worm, if not hot, after a while

Some of the electrical energy in signal is converted to heat

To compensate for this loss, the amplifiers are used to amplify the

signalSlide6

Transmission

ImpairentsAttenuationSlide7

Transmission

ImpairentsAttenuationSlide8

Transmission

ImpairentsAttenuation

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

10log10

powerin

/

powerout

Pin = 100mW

Pout = 10mW

attenuation

= 10log

10

(100/10)

= 10

dBSlide9

Transmission

ImpairentsAttenuation

Suppose a signal travels through a transmission medium and its power is reduced to one-half. This means that Pout

is (1/2)Pin

In this case, the attenuation (loss of power) can be calculated

as;

A loss of 3 dB (–3 dB) is equivalent to losing one-half the

powerSlide10

Transmission

ImpairentsAttenuation

A signal travels through an amplifier, and its power is increased 10 times. This means that Pout

= 10Pin . In this case, the amplification (gain of power) can be calculated asSlide11

Transmission

ImpairentsDistortion

Distortion means that signal changes its form or shapeDistortion occurs in a composite signal that is made of different frequencies

Each signal component has its own propagation speed through a medium and, therefore its own delay in arriving at the final destination

That means that the signals have different phases at the receiver than they did at the sourceSlide12

Transmission

ImpairentsDistortion

The distortion is caused by the fact that the velocity of propagation of a signal through a medium varies with frequencyThus, 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 componentsSlide13

Transmission

Impairents

Noise is another problem occurred during the transmission of dataNoise is any signal that is not useful

Original Signal

Noise

Output SignalSlide14

Transmission

ImpairentsThere

are different types of noiseThermal:

The random motion of electrons in a wire which creates an extra signal not originally sent by the transmitter

Induced:

Noise that comes from motors and appliances, devices act are transmitter antenna and medium as receiving

antenna

Crosstalk:

It is the effect of one wire on other, it is same induced but between two

wires

Impulse:

Irregular disturbances, such as lightning or power line spikes etc. It is a primary source of error in digital dataSlide15

Signal to Noise Ratio

In analog and digital data communications, signal-to-noise ratio, often written S/N or SNR, is a measure of signal strength relative to background noise

The ratio is usually measured in decibels (dB)

If the strength of incoming

signal is P

and the

noise in the channel is N

then the signal-to-noise ratio, S/N,

is given by the formula;

S/N = Power/Noise

a

nd in decibels;

S/N = 10 log

10

(Power/Noise)Slide16

Signal to Noise Ratio

If Power = Noise, then S/N = 0;

In this situation, the signal borders on unreadable, because the noise level severely competes with itIn digital communications, this will probably cause a reduction in data speed because of frequent errors that require the source computer or terminal to resend some packets of data

If Power is less than Noise, then S/N is negative;

In this type of situation, reliable communication is generally not possible unless steps are taken to increase the signal level and/or decrease the noise level at the destination computer or terminal

Ideally, Power is greater than Noise, so S/N is positiveSlide17

Transmission

ImparientsThe

value of SNR for a noiseless channel is;

We can never achieve this ratio in real life; it is an

idealSlide18

Transmission

ImparientsAs an example, suppose that Power = 10 W and Noise = 1 W, then

S/N = 10log10(10/1) = 10dB

which results in the signal being clearly readable

If the signal is much weaker but still above the noise, say 1.30 W, then

S/N = 10log

10

(1.30) = 1.14 dB

which is a marginal situation, there might be some reduction in data speed under these conditionsSlide19

Shannon’s Bandwidth

If we had such a thing as an infinite-bandwidth, noise-free channel we could transmit unlimited amounts of error-free data over it per unit of time

However real life signals have both bandwidth and noise-interference limitations

In electronic communication channels, Shannon capacity is the maximum amount of information that can pass through a channel without error,

i.e., it is a measure of its "goodness" Slide20

Shannon’s Bandwidth

Shannon's Law says that the highest obtainable error-free data speed, expressed in bits per second (bps), is a function of the bandwidth and the signal-to-noise

ratioLet c be the maximum obtainable error-free data speed in bps that a communications channel can handle

Let b be the channel bandwidth in hertz

Let s represent the signal-to-noise ratio

Then Shannon's law is stated as follows:

c = b log

2

(1 + s)

The function log

2

represents the base-2 logarithm. All logarithms are exponents. The base-2 logarithm of a number x is the number y such that 2y = x.Slide21

Shannon’s Bandwidth

The telephone channel has a bandwidth of 3 kHz and a signal-to-noise ratio exceeding 30

dBThe maximum capacity error free data

rate a modem can produce for this channel

C = 3×10

3

log

2

(1+10

3

)

= 29.901

kbps

Thus

, the so-called

56

kbps

modems have this capacity limit