Good day. In this third lecture we will be looking at Physical Medium. In the last lecture
we have seen two protocol stacks, we have seen OSI protocol stack in detail and we had
a look at its CPI pre reference stack. But whatever be the model, at the bottom-most
layer you have the physical medium because, after all, if two computers have to communicate,
there has to be some physical medium between them. So we will just look at some general
characteristics of physical medium and how data can travel along them, today. In the
next lecture we are going to look at some specific media which are used in networks.
As we talk about the Physical Medium, we have to talk about two different modes of communication,
so to say. One is Analog and the other is Digital, so you have before you that top one
is the analog signal; you can see that it can take any shape, and the digital signal
is some kind of signal, which represents a series of ones and zeros – stream of bits,
but analog signals of course can take any value in them.
And one important consideration for any medium is its bandwidth. Bandwidth is the capacity
of a media to carry information. Now, the total capacity may be divided into channels
– I mean there is one total capacity you can sort of divide it into channels – and
give different channels to different users; specific portion of the channel may not be
used for direct communication but for control purpose and other specific purpose. But whatever
it is, any particular medium and technology will have a certain capacity and this is really
important because, after all, your speed of communication will depend on the capacity
of the medium.
This inherent capacity of the medium is of course intermittently linked with the kind
of signal one particular channel can carry. For example, on the left-hand side, you see
some digital signal and just on its right you have something that looks like a barograph
– actually this is a representation of the same signal in a different way, what this
right-hand side says is basically if you have a series of a Sin x plus b sin 2x plus c sin
3x plus d sin 4x and so on Where a, b, c, d represent the values shown by the graph
on the right-hand side, if you sum all that sin values up, you will get the signal on
the left-hand side. So the channel, if it has to carry the digital signal, has to be
able to carry all these harmonics – harmonics means the sin x constant, sin 2x constant,
sin 3 etc. So all these harmonics it should be able to carry; whereas if you look at the
second figure b, it is a pure sin wave. So this just has one harmonic, a sin x or something
like that. This third figure has two harmonics, say a sin x plus b sin 2 x; so depending on
the complexity of the wave form that you want to carry, you want more and more bandwidth
for the channel.
Now for this we make a comparison of analog verses digital signals. Digital signals have
some basic advantages the most basic advantages is that it is that less error prone that means
if there is some kind of distortion in the signal between the source and destination
that can be rectified very easily and to limited extent errors can be corrected. Whereas if
you are talking about analog signal there is little control over signal distortion of
course this also old technology and this has got some limitations in technology in the
sense that how many people can use, etc. There are some limitations over here. So digital
signals are of course in general preferred, although analog signal still rules in some
niche areas So let us see what we mean by the statement that digital signals are less
error-prone.
In this figure we see in the left-hand side have some analog signal and then some noise
has come; that means, some distortion has come and the signal looks like the one below.
When noise affects an analog signal, it is hard to deduce the original signal from this
whereas the same kind of noise or a similar kind of noise if it is gets superimposed on
the digital signal as we see on the right, the signal gets distorted, but since we know
that the original signal was sort of square shaped, we can deduce the original signal
from the distorted signal. So, despite the noise, noise can be eliminated easily in digital
communication. That is the greatest advantage of the digital communication.
And so far as the bandwidth of a channel is concerned, suppose we know the bandwidth (H)
of the channel and the number of signal levels (V) being used, what is the maximum number
of bits that we could transmit? Suppose we are trying to transmit bits in terms of digital
signal; so there is a SyQuest limit. It says that Maximum bits per second is equal to 2
* H * log2 V for example if the bandwidth is 3100 Hz and we are using 16 level modulation
then the maximum number of bits per second is log2 (16) is four so 4 into 2 into 3100,
that is 24800 bps 24.8 kbps. So this is the maximum number of bits that we can send through
the channel of this particular bandwidth. So the higher the bandwidth of the channel,
the higher the number of bits that we can send through it, but depending on the bandwidth,
there is always a hard limit on how fast we can communicate.
Let us look at this regeneration of the digital signals once more. We say that it is reliable
because it can regenerate slightly damaged signals. Since there are only two states,
for example, this is the original signal, which is a square, and it is grossly distorted
as it is received. This becomes weaker in strength and the shape has also been deformed
but we can regenerate it since we know that the original shape of the signal must have
been a square one. So we regenerate it as a square one. If there are two states of a
voltage, let us say, plus 10 volts minus 10 volts and the signal is plus 8 volts, let
us say, then it is quite possible that this that this plus 8 volts is a result of noise,
which is superimposed on plus 10 volts rather than a result of noise superimposed on minus
10 volts.
So whenever you get PLUS8 volts simply make it 10 volts with some electronics and the
original signal will be restored. Of course I mean if the noise is very high, there is
a limit to how much you can restore. If the noise is very high then it will not be possible
then we will know because minus10 volts also becomes 8 volts in the case of a spike, and
then whatever restoration we do will be a wrong one. So we lose some information; there
will be some distortion and some loss of information will be there.
So there is always a limit but in the case of digital signals it is more fault-tolerant
or resistant to noise, more resilient compared to analog signals.
So we can correct errors in transmission – that is another advantage of digital signals. So
what we do is that we add a few bytes of error-checking information and can ask for retransmission
if an error is detected. I will give you a simple example: suppose we are sending groups
of 8 bits called bytes; now what we can do is that associated with each byte, we can
add an extra byte and this extra byte would make let us say the number of 1s in the whole
9 bits to be odd, this is an example of an odd parity.
Now, if at the receiver’s end, we find that the number of 1s have become even, we know
that some bit must have flipped. That means, some bit must have flipped; instead of a 0,
we got 1 and instead of a 1, we got a 0. It must have happened. Otherwise, because the
number of bits was supposed to be odd – and of course by adding 1, we can always dictate
the number of bits in the original that the sending station was odd – in that case the
receiver may request the sender to retransmit that whole bunch once again; hopefully there
will not be an error next time. This is of course a very primitive kind of error-checking;
there are more sophisticated error-checking methods employed in networks and communication.
So this error-checking and correction of error at the receiver’s end is possible if you
have adopted a very sophisticated coding technique. So that is possible in case of digital transmission;
this is not possible in analog transmission.
Another advantage is that a digital signal can be encrypted, which makes it possible
to carry sensitive information on the network. For example, e-banking is coming in vogue
– that means, somebody does a bank transaction on the network. Similarly e-commerce – that
means you want to buy something online and then pay through your credit card, etc. Online.
Now how does the transaction take place?
The point is that you are sending some information, may be your credit card number, may be some
password, etc. Somebody can snoop on you in-between, so they will know your secrets and use the
same set of numbers to may be buy something else, and the money will go from your bank
account; that is obviously not acceptable. In this case when we send it down the network,
we encrypt it in a way that even if somebody snoops and finds out the stream of bits that
is going, he will not be able to make out the original numbers from this current stream.
So this is encryption and this is a very important application these days.
So encryption is another advantage of digital transmission. Compression is another; that
means; we can compress a message before transmission and decompress it at the other end. So the overall load on the circuit and the network
is lighter; since the load is lighter it is less expensive. Sometimes when you compress
information there may be some loss of information; there are lossy compression techniques and
they are non-lossy compression techniques. Lossy compression technique is where you may
lose some information, but it may not matter.
For example let us say you want to send a digital photograph. A digital photograph may
have a very high resolution; if you compress it and decompress on the other end, you may
lose a few bits but the image that you get on the other end would still look almost as
good as the original one. Of course, trained persons can look at it and find out there
is something missing but it will almost serve the purpose. Sometimes loss compression is
acceptable and of course there is loss-less compression also. When you compress it and
send it, it is a less expensive way of sending. I mean you are sending the same information
but only your are taking less amount of space; of course you have to do the compression and
decompression at the two ends, so that is some kind of overhead on the two sides. Suppose
we have some data; how do we encode this digitally? Well, the simplest way, of course, is by the
presence or absence of a signal.
Let us say a positive voltage might represent a binary zero or a binary one or vice versa.
Maybe if you have high voltage, you say that is I will interpret that is as one being sent
and if I have a low voltage I interpret this as a zero being sent. Of course, when I am
saying voltage, I am assuming that we are having some kind of electrical signal traveling;
that is not always the case. For example, if you are using light for communication the
presence of light may indicate one and the absence of light may indicate zero. So whatever
we code it, whatever be the medium, this is the simplest wave to encode data into a digital
form. The current state indicates the value of
the data.
If your signal is digital, sometimes you are forced to send some digital signal by analog
transmission, but this is usually not preferred. Analog signal will transmit whatever signal
comes regardless of whether it represents digital or analog data. So it uses amplifiers.
Other than the kind of regeneration that is possible in digital voice, the trouble with
amplifiers is that it also boosts noise, whereas in the digital case we could take out the
noise and regenerate the original shape of the signal. Here we can amplify it, so that
if a signal becomes weak we can make it stronger; but whatever noise is coming with the signal
that also gets amplified. This is okay for voice, but for digital data using analog transmission
usually is not done because we have so little control over the correctness of whatever we
are sending.
Digital transmission is concerned with the content of the signal; it uses repeaters which
recover the pattern of zeros and ones and then retransmits. This can be used with analog
signal if it carries digital data. You know sometimes analog signal carries digital data;
it recovers the digital data from the analog signal, generates new clean analog signal.
This is becoming more standard; for example, when you are connecting to the network, to
the internet, from your home computer you may have used the modem and the telephone
connection. Now what is happening over here is that the telephone line is essentially
an analog medium;
So an analog signal will go over there on that, but whatever is coming out of your computer
is digital. So what you do is that you make this digital data ride on some analog signals
to this modem pairs so that it reaches the telephone exchange. At the telephone exchange
it is converted back to digital data and the backbone and the core of the telephony system
is purely digital.
So there are various ways in which you can encode digital information in the analog domain.
One is the amplitude shift keying, which means the two binary numbers 0 and 1 are represented
by two different amplitudes of carrier waves. This is not very efficient; uses up to 1.2
kbps on voice grade lines; and is used to transmit digital data over optical fiber.
In the amplitude shift keying, although the signal is analog we know that there are only
two levels, which this signal is supposed to take, i.e., two amplitudes: low amplitude
and high amplitude. It may be 0 and some amplitude.
If a 1 is to be transmitted may be we give this high amplitude and if a 0 is to be transmitted,
we may use a low amplitude analog signal. You may say this is the kind of thing which
is done in the optical domain; but in the electrical domain this is not very efficient.
More common is the so-called frequency shift keying. In frequency shift keying, we use
the two binaries; that means we use two different frequencies for the two binary digits, 0 and
1. So this is less susceptible to error than amplitude shift keying, and again, it sends
up to 1.2 kbps on voice grade lines and is commonly used for high-frequency radio. Another
way of encoding is the so-called phase shift keying.
Two binary numbers may be represented by phase shift of carrier wave; so this is more efficient
and noise resistant than FSK; this is PSK. It can be raised up to 9.6 kbps (kilo bits
per second) on a voice grade line. This is for a simple phase shift keying; of course,
we use more complex phase shift keying with other techniques in order to achieve even
higher data rates nowadays.
These techniques can be combined. So it is common to combine phase shift and amplitude
shift keying so we can get about 56 kbps on a voice grade line. The modems that we buy
usually are all 56 kbps, connected with some technique called multilevel signaling. Each
signal represents more than one bit. So this is also possible. One is the signal, which
indicates the level of the voltage or whatever it is, the phase or frequency, the level of
the signal; the other is the bit or bits that it may represent.
So, for example, if you have a simple technique, it will represent a 0 or a 1 by the current
level of the signal, which is the simplest kind of technique, these two are the same.
One is the bit rate, that is, the number of bits of information that you are sending;
the other is the baud rate, that is, the number of times the signal will change per second
– the maximum number of times the signal will change per second. So in the simplest
case, baud rate and bit rate may be the same but that is not always the case.
So we look at the other side of the coin, which is the digital encoding of analog information.
And a very common case is the telephones. For example, as I just now told you, the heart
of the telephone exchanges and the telephone switches and the trunk exchanges and the core
network of the telephone system are nowadays entirely digital. Whereas our voice, of course,
is analog. By the way, the real world, in which we move around, is mostly analog. Now
this digital is something that we adopt in-between in order to get these advantages of robustness,
resiliency, error correction, etc. our voice is analog, but the core telephone system is
digital. So at some point, our voice, an analog signal, has to be converted into a digital
signal. Of course, our handsets also are mostly analog.
So they are going to be carried may be in this analog fashion right up to the nearest
exchange; but there, there will be a set of codecs, coders and decoders, which will convert
this analog voice signal to a digital signal. Now, what kind of digital signal will a voice
give? The calculation is something like this: the voice data in a telephone system is limited
to a maximum of 4 KHz. this telephone is a very good quality, the first so-called gold
quality but this is not high fidelity kind of sound. It is less than high fidelity, but
very clear, for all practical purposes for the telephone at least. If I limit the bandwidth
to 4 KHz, we get some distortion, but nothing very noticeable.
So voice is still very clear. We have to send this 4 KHz of analog signal, whatever information
is there, within 4 KHz bandwidth. We have to send this analog signal to the other side
in a digital form; that is, we have to digitize it. There is a Nyquist rate, which is like
the Nyquist limit that we have seen some time back. Nyquist rate, which says that if we
sample any analog signal at double the maximum frequency that the particular analog signal
has, then essentially we will have all the information that is needed to fully reconstruct
the original analog signal from this sample. So if you have 4 KHz of signal, 4 KHz of bandwidth,
we require 8000 samples per second. Let us say you have this analog voice; so per second
we will take 8000 samples, sample values at different points.
So, of course, at some points my voice may be low so I may have small amplitude; at some
point my voice may be very high so I can have large amplitude. Now that we break up each
of these into a code of 8 bits, the point is that with the 8 bits, you can really distinguish
between 256 levels. And our assumption is that from the 0 level to the highest level
that is admissible, we take it; whatever it is, if you break it up in to 256 parts, that
is good enough for capturing how high or low the volume is. So a level of 256 is really
quite a lot. We require 8 bits for each of the sample and we require 8000 samples. That
makes it 8 into 8, that is, 64 kilo bits per second, 64 Kbps. Please remember this rate
– 64 kilo bits per second – it is the fundamental unit on which a whole lot of all
other technology, etc. has been built. And basically, it has come especially from telephony,
because the telephone people had the first network and 64 kbps happened to be the rate
which was set for a voice.
So naturally, of course, if you want to carry 1 voice channel, we will have a 64 kbps. If
you want to carry 1000 voice channels, you will require 64 kbps into 1000, that is, 64
mbps capacity. So they planned their network depending on how many voice channels they
want to carry where; but 64 kbps is the basic unit in most places in telecommunications.
Now let us take a quick look at how data is encoded. The simplest one is of course using
the level of the voltage; for example, over here this is the non return to zero level,
the so-called NRZ encoding. It uses two different voltage levels to represent 0s and 1s; typically
negative voltage equals 1 and positive voltage equals 0 and the signal never returns to 0
voltages. So it flips flops between a negative voltage and a positive voltage.
The value during bit time is a level voltage; that means, during the duration of a bit 0
or 1 the voltage really remains the same. So there is a transition at the boundaries
of bit and of course, if there are two 1s then there will be no transition as we can
see; if there are two 0s consecutively, then there will be no transition. So the number
of transition is much less and it is a very simple kind of scheme. This has some problem.
We will come to that later on; but let us look at another variant of this non return
to zero, which is NRZI. That means non return to zero and invert on 1s.That means once again
we keep constant voltage during bit time – no transition represents 0 and transition from
low to high or from high to low is a 1. So the same bit pattern, 0 0 1 1 0 1 is represented
by a different voltage pattern over here. There is no transition 0 0 and then there
is a 1, so there is a transition; there is another 1, there is a transition; 0 no transition;
then again the 1, then another transition.
So this is another way of encoding. Now the trouble with these encodings is that suppose
you have a large number of 0s, a large train of 0s, there is no transition really. By the
way, there is one point – the reason they use the positive voltage and negative voltage
rather than a positive voltage and zero voltage or zero voltage and negative voltage is that
you want to distinguish between a 0 being sent and no signal being sent. So that is
one point and the other point is that as I was saying if there is a constant train of
0s in the original data then we will have a constant level signal in the system.
Now if that be so, the synchronization of the clocks between the sender and the receiver
tends to drift off and then the receiver, I mean in the worst case, the signal may go
one off or it may interpret the signal in a very wrong fashion. So this is the problem
of this NRZ and NRZI, which is taken care of by some other kind of encoding; we will
come to that later on. So this is a just a quick look at the disadvantages of NRZ code
– hard to tell where one bit ends or starts; with long string of 0s or 1s, any drift between
timing of transmitter and receiver results in errors. So there is a bit phase encoding,
which uses the least transition per bit time.
So if you use at least one transition per bit time, what would happen is that the sender
and the receiver clocks can remain in very close synchronization with each other – that
is a nice property – and there is predictable bit transition during each bit time. So an
absence of a transition indicates an error. So two examples are Manchester and differential
Manchester’s so this is Manchester encoding. You see that at the middle of each bit 0 or
1, there is a transition. Now, low to high transition means 1 and high to low transition
means 0. So the same pattern – 0 0 1 1 0 1 – is there for each bit; you will see
there is a transition in-between, and low to high transition is 1 and high to low transition
is a 0. So this is the encoding, which is used in Ethernets and many LANS
There is another variant of this called differential Manchester; in this, the midbit transmission
is really for clock synchronization purposes. They do not represent either 0 or 1. So what
it does is that transition at the beginning of a bit period is equal to 0 and the absence
of a transition is bit period 1. So 0 0 – when this 0 starts, there is a transition. Transition
at the beginning of the bit period is a 0; but when the 1 starts, there is no transition.
There is a transition in the middle anyway; that is for clocking purpose. Then at the
next level, once again if there is no transition if there is a second one coming, there is
no transition and so on. This was used in token ring networks; of course token ring
networks are becoming less popular these days but anyway, this is another one. There are
other kinds of encoding techniques, but these are the common ones. So you see that there
are different ways of encoding the digital data into these different signal levels.
Signal levels and bit rates are different. The rate at which the signals change is the
baud rate, and the rate at which bits are sent is the bit rate. The other thing we can
consider is the analog encoding of analog information. Of course, this does not come
too much in computer networks, but this is an important area in communications in general.
So of course, if you have an analog signal, it can directly be sent. Sometimes it is sent
in the raw form; sometimes that is not very practical, so we have to convert this to an
analog signal maybe at higher frequency, and the most common example of this is the radio.
For example, a radio is carrying voice or may be some sound, etc.
The voice, as you know, is only 4 KHz, but if you take a 4 KHz signal and try to send
it over the atmosphere, it will not reach any where, excepting in its close vicinity.
So, in order to reach out to all these different locations, you have to send your radio signal
at a very high frequency; but the information that is it carrying is still at that 4 KHz
bandwidth. So this 4 KHz bandwidth is sort of translated; so there is a very high-frequency
so-called carrier wave, which is carrying this 4 KHz of signal if it is only voice.
Of course if it is music, etc., you may like to have a somewhat higher bandwidth also;
but anyway, that is also analog signal and this is also analog signal.
So one analog signal is carrying the other analog signal and there are various ways of
doing this so-called modulation. The three most common ones are amplitude modulation,
frequency modulation, and phase modulation. So we will not talk much about this because
in amplitude modulation as you can understand, the amplitude of the carrier wave is changed
according to the signal; similarly, in frequency modulation the frequency of the carrier wave
is changed according to the signal; and then in PM the phase is changed according to the
signal.
So this is another picture of digital signaling so called current state; that means zero represents
the low voltage one is represented by the high voltage and digital signaling and state
transition; so if there is no transition that is zero if there is a transition that is the
one so these are all different examples of Encoding.
As I was telling, the bit rate and the baud rate are different. The maximum number of
times a signal can change in a second is called the baud rate and the number of bits, 1s and
0s transmitted in a second is called the bit rate. In the examples we have seen so far,
the bit rate and baud rate are the same; this is not always the case.
The bit rate can be higher than the baud rate if we use more than two signal levels; and
the other one is also possible: the bit rate may be lower than the baud rate.
Now let us look at some of the inherent trouble with all these physical media. That means,
when we are throwing some signal, when we are trying to send some signal down some transmission
medium – it may be a piece of wire it may be this whole atmosphere or it may be a fiber
optic cable – there will be some kind of distortion, some kind of change in the original
signal, that will inevitably come into play. So we will look at some of these; we have
to really take care of all these. These signals and these kinds of effects cannot be eliminated.
I mean the world is not perfect and they are basic properties of the medium so we will
have to design our systems in such a way that in spite of all these efforts the whole communication
will still go on very correctly. As a signal propagates, the signal changes as it travels;
so the receiver may not be able to recognize it as such. For example, this shows an example
of an original signal and the final signal. This kind of change and distortion etc. May
be attributed to the following effects: the first one, the very first one, is attenuation.
A signal get weaker as it propagates; attenuation becomes greater with distance naturally, and
of course, finally, the signal will become too weak to recognize. So the original signal
strength is something but as the distance grows signals become weaker and weaker. For
example, let us say this kind of weakening is dependent on the property of the medium;
it also depends on the kind of frequency you are using for sending. For example, let us
say an AM signal will not be received at a very large distance, whereas a short wave
signal may travel some other way and come over here.
Similarly, if you take a local area network or a cable, then if you make the cable very
long – there are other technical problems for making cable very long – but even from
the signal propagation point of view, the signal will get weaker and weaker. Because
there will be leakage currents in the cable, current will leak out, etc. Finally, the signal
that we will get will be very weak. So this is a very fundamental property of any medium.
Similarly, if you take an optical medium and if you send a light pulse through it, as it
travels, the light pulse will get weaker – that is one of the effects. There are other effects,
but this is one of the major effects.
Apart from attenuation, there is distortion. That means, the signal changes shape as it
propagates. Now if it changes shapes in this way, the adjacent bits may overlap, may make
recognition impossible for the receiver, so what might happen if the signal changes shape?
Why does it change the shape? If you remember in the very beginning I had shown you one
slide of a square wave kind and we talked about some harmonics. So the square wave may
be looked upon as a sum of all these harmonics, a sum of all these sign waves. Now all the
harmonics or sign waves are of different frequencies – we had talked about the sin x sin 2 x
and sin 3 x and so on – so they are of different frequencies.
Now signals of different frequencies change or get affected by the medium differently.
So a signal of a particular frequency may be attenuated less; the signal at a much higher
frequency may be attenuated much more or vice versa. The point is that signals at different
frequencies will get affected by the medium in different ways. So finally, the relative
strengths of the different frequencies will be different when you go to the far end; that
means, when you go to the receiving end, when you add that all up, you will get a different
shape. You will not get the old square shape or whatever shape you have sent; you will
not get that back. So this is called distortion.
Then, of course, it is going to pick up noise. There is thermal energy in wire, which is
everywhere. So this energy is some kind of inherent noise that will always come; then
there will be random signals. So spikes may sometimes occur; say, some car is starting
somewhere so there will be some static discharge; the lightning strikes somewhere, there is
somebody running a motor, somebody is running a washing machine, all these things add to
the general noise in our atmosphere and this medium, which is carrying a signal, will also
catch some of this noise. Sometimes of course, the noise is so sharp that it may change the
transmission in such a manner that you will not get the original signal back. So sometimes
such a thing may happen.
What we want is a high signal-to-noise ratio in order to distinguish between the signal
and the noise. If the noise is very low and the signal is high, we can still distinguish
at the receiving end between what is a signal and what a noise is and take the signal out,
take out the noise. But for this we want a high signal-to-noise ratio. Signal strength
divided by the average noise strength is the SNR and as SNR falls, error will increase.
So in this figure, you can see that as the signal becomes weaker and weaker and touches
the noise floor may be goes below it.
When it goes below it, the noise becomes more than the signal; then no meaningful communication
can be carried out. So in general, we want a strong signal-to-noise ratio. So one thing
we might do quite often is that suppose we do have to send a signal to a very long distance, the signal will naturally
get weak. So in-between, we will put some amplifiers or repeaters or regenerators, which
will take the signal, try to filter out the noises as much as possible, then amplify the
signal and make it stronger, and then push it for the next span. So after some distance,
again another repeater will take it up and regenerate the signals. We have to go on doing
that so that I maintain an acceptable signal-to-noise ratio even at the receiving end.
Then of course, as I said that, there is interference. That means energy from outside the wire adds
to signal, like noise, which is often intermittent, and is very hard to control or diagnose. One
important point is that a very strong interference can occur at cable termination. So there are
two things: first of all, if two cables are running in parallel, what might happen is
the signal in one may affect the signal in the other.
So there is some kind of linkage between the two the so-called cross talk – that is one
thing. This is more pronounced at the termination end; at the termination end, if you do not
terminate the thing properly, if you just leave it like this, the kind of distortion
and the kind of noise that will be introduced will be much more. So whenever we are putting
some wired kind of network infrastructure, we have to be very careful about the termination,
because that is where a lot of noise can come in. So often there will be multiple wires
in a bundle; each radiates some of its signal, causes interference in nearby wires and this
is especially bad at terminations where wires are unwound and are parallel.
Finally I just mentioned this, that when carrying digital data over analog lines, we require
modems. Modem stands for modulation and demodulation. This is used to connect a digital computer
to an analog phone system usually, but modems can also be used elsewhere. It can be installed
internally or a card inserted into the motherboard or can be connected to the serial port, etc.
So now we understand why modems are required because essentially, digital data will have
to be carried on the analog system. The field of communication, as you know, is a very interesting
field and we could not go too much into the details of communications. But we have just
talked about the very basics of communications used in computer networks, because remember
computer network or some computers or some network nodes are connected via some communication
lines. So communication is absolutely important; it is all-important in this; so we have talked
about this. In the next lecture, we will look at some of the medium that is actually used
or deployed in common networks. Thank you.
Today we will have the second lecture on the physical media in the last lecture we have
seen the different ways the digital signals and analog signals, etc how they can be used
for communication how digital data or analog data can be encoded and some of the general impairments
of physical medium. In this lecture we are going to look at specific media which are
used in networking.
So there are basically two types of media which are used for communication one is cable
I mean they are two different classes are together so one is a cable now this cable
could be some copper cable they could be coaxial cable or twisted pair or shielded twisted
pair so the twisted pair I mean we sometimes there actually unshielded twisted pair or
UTP sometimes we simply called them twisted pairs since they are more common there are
shielded twisted pairs also and then of course the one of the most important cables these
days is the fiber optic these are the different types of cables that we use in networks. Similarly
we can also communicate without the use of any cables by simple electromagnetic radiation
and this radiation could be in different ranges of the frequencies like they could be infrared
or microwave or radio or satellite. Etc so we will look at all these one by one.
First let us look at the kind of media that we use in a LAN. LAN as you remember is a
local area network and a local area network could vary from let us say one meter to one
kilometer so it is local strictly by some means of size in some way so one meter means
two computer connected siding on the same table connected side by side it could be all
the computer in one building and all the computers in several buildings and so on so that is
the kind of range that we have for LAN. And the medium that we use for LAN they could
be coaxial cables, UTP, fibers, wireless so you would note that basically most of the
types of cables that we talk about find their way in some ways or other in local area networks.
And of course UTP or unshielded twisted pairs are of different varieties or categories so
that cat is for categories so we could have cat3 cable cat 5cable, cat 5e cable, cat 6
cable, cat 7 cable and so on .You must have seen cat 3 cable if you looked all your telephones
that is the landline phones they are connected by unshielded twisted pair cables of categories
three. For computer networking I mean cat three cables could also be used for LAN although
we usually prefer cat five onwards. The kind of things that are on the network that could
be PBX, PBX is your local telephone exchange that could also have some digital ports etc.
Ethernet is one technology which is used in LAN ATM is also used, FDDI is sometimes used
FDDI if you remember is fiber distributed that is the FDDI ring kind of structure. So
there are some networks even smaller than LAN. They have called personal area networks
some networks so I may have been varying three or four computers and them or connected in
a network on my body. We will come to pan later on but going on the other side of the
spectrum that means from LAN to a bigger network this is man that is a metropolitan area network.
Typically one campus or one city may be several small towns which are closed together they
would come under the preview of the MAN, so MAN by ballpark figure man would be extent
of about 10 kilometers, so it could be 5 kilometers or it could be 20 kilometers so something
in that range.
And the kind of medium that we use for a metropolitan area networks coaxial cables both base band
and broadband, we will come to this what they are. sometime UTP are used but that is not
very preferred way of connecting although UTP are used one way UTP is definitely used
are when you try to network to telephone lines. That is I mean telephone linesi told you they
use UTP. It could be a hybrid kind of system, some part of it could be coaxial some part
of it could be UTP and some part of it could be fiber. Fiber means, fiber optic cables.
and kind of things of course that kind of technology that goes into a MAN would be PBX
different kinds of modems for example if you are using a broad band coaxial cable you might
use something what is known as a cable modem . then you have this long Ethernet that means
on the Ethernet on the over may be some lines cable tv DSL digital subscriber lines or it
could be wireless. One issue which is important in MAN is the issue of access alright that
means how do you reach to each individual users.
I mean think of a town or a city so you really have to in order to network the entire town
you have to reach to each individual residence and reaching to each individual residence
involves cost ok, if it is a small building like in a LAN you can take very good say UTP
cable to his room now there are problems of taking UTP cable to each individual house
I mean there could be I mean electromagnetic disturbance and things like that but apart
from that there is a question of cost. Ok if you are trying to build so much copper
into that is quite costly. So how to access to users who are distributed over somewhat
wide area in the sense of several kilometers that is an issue in metropolitan area networks
Finally at the extreme of the spectrum we have WAN that is wide area network so they
may stretch from ten kilometers to may be 10000 kilometers, so 10000 kilometers almost
to the other side of the globe. So they can involve very long distance. medium is usually
fiber or satellite and the kind of technology that is used in WAN are SONET or SDH that
the almost similar technology ATM IP that is the internet protocol, DWDM dense wavelength
division multiplexing, Geo and Leo Geo stands for Geostationary satellite is a short form
of Geostationary satellite and Leo is low art orbiting satellite. 477