Download module1 A Communications Model

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DATA COMMUNICATION
Data communication is the exchange of data between two devices via a transmission medium.
Data refers to information presented in whatever form is agreed upon by the parties creating and
using the data. The effectiveness of data communication system depends on four fundamental
characteristics :
1.
2.
3.
4.
Delivery – System must deliver data to the correct destination.
Accuracy – System must deliver accurate (correct) data to the destination.
Timeliness- System must deliver data in timely manner. Data delivered late is useless.
Jitter – Data must be transmitted without any jitter. Jitter refers to the variation in packet
arrival time.
A Communications Model
The fundamental purpose of a communications system is the exchange of data between two parties. The
key elements of this model are:
1.
Source – The device that generates data to be transmitted
Eg: Telephone, PC
2.
Transmitter – converts data into transmittable signals - The data generated by the source are not
transmitted directly in the form in which they are generated. The transmitter transforms and
encodes the information to produce electromagnetic signal, that can be transmitted.
Eg: MODEM
3.
Transmission System - carries data from source to destination - This can be a single
transmission line or a complex network connecting source and destination.
Receiver - converts received signal into data – Accepts the signal from the transmission system
and converts it into a form that can be handled by a destination device.
Eg : MODEM
4.
5.
Destination - Takes incoming data from the receiver.
Eg : PC
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Communications Tasks
The key tasks that must be performed in a data communications system are
1. transmission system utilization - need to make efficient use of transmission facilities
typically shared among a number of communicating devices
2. a device must interface with the transmission system
3. once an interface is established, signal generation is required for communication
4. there must be synchronization between transmitter and receiver, to determine when a
signal begins to arrive and when it ends
5. there is a variety of requirements for communication between two parties that might be
collected under the term exchange management
6. Error detection and correction are required in circumstances where errors cannot be
tolerated
7. Flow control is required to assure that the source does not overwhelm the destination by
sending data faster than they can be processed and absorbed
8. addressing and routing, so a source system can indicate the identity of the intended
destination, and can choose a specific route through this network
9. Recovery allows an interrupted transaction to resume activity at the point of interruption
or to condition prior to the beginning of the exchange
10. Message formatting has to do with an agreement between two parties as to the form of
the data to be exchanged or transmitted
11. Frequently need to provide some measure of security in a data communications system
12. Network management capabilities are needed to configure the system, monitor its
status, react to failures and overloads, and plan intelligently for future growth
Data Communications Model
We trace the details of this figure using electronic mail as an example. Assume a PC user wants to send
an email message m to another user.
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The process is modeled as follows:
•
•
•
•
•
•
user keys in message m comprising a sequence of bits g buffered in source PC memory
input data is transferred to I/O device (transmitter) as sequence of bits g(t) using voltage shifts
transmitter converts these into a signal s(t) suitable for transmission media being used
the transmitted signal s(t) presented to medium is subjected to a number of impairments, before
it reaches to the receiver. So received signal r(t) may differ from s(t)
receiver decodes signal recovering g’(t) as estimate of original g(t)
which is buffered in destination PC memory as bits g’ being the received message m’, usually be
an exact copy of the message m
Electric Signals
To be transmitted data must be transformed into signals.
Continuous and discrete signals
As a function of time electromagnetic signal can be either continuous or discrete.
A continuous signal is one in which the signal intensity varies in a smooth fashion over time.
A discrete signal is a sequence or a series of signal values defined in discrete points of time.
Analog and Digital Signals
Viewed as a function of time, an electromagnetic signal can be either analog or digital.
An analog signal is one in which the signal intensity varies in a smooth fashion over time.
Analog signal can have infinite number of values in a range
Eg: sine wave
A digital signal is one in which the signal intensity maintains a constant level for some period of
time and then abruptly changes to another constant level. A digital signal represents a sudden
jump from one value to another. A digital signal can be used to plot the absence or presence of
something (ie 0 or 1). Digital signal can have only a limited number of values.
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Periodic Signal
Both analog and digital signal can take one of the two forms – Periodic or aperiodic. Periodic
signal is a signal in which the same signal pattern repeats over time. A signal s(t) is periodic if
and only if
S(t+T) = s(t)
-∞<t<+∞
The sine wave is the fundamental periodic signal. A general sine wave can be represented by three
parameters:
•
•
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peak amplitude (A) - the maximum value or strength of the signal over time; typically measured
in volts.
frequency (f) - the rate [in cycles per second, or Hertz (Hz)] at which the signal repeats. An
equivalent parameter is the period (T) of a signal, so T = 1/f.
phase () - measure of relative position in time within a single period of a signal
A general sine wave can be written as
s(t)= A sin(2πft + Φ)
= A sin(2πt/T + C)
Where s – instantaneous amplitude, A – peak amplitude, f – frequency, T – time period and Φ is
the phase.
A aperiodic or nonperiodic signal changes constantly without exhibiting a pattern or cycle
that repeats over time
Period (T)
Period refers to the amount of time , in sec, a signal need to complete one cycle.
Frequency (f)
Frequency refers to the number of periods in one second.
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ie, f = 1/T and T= 1/f
Frequency is normally expressed in Hertz(Hz). Frequency is the rate of change with respect to
time. Change in short span of time means high frequency. Change over long span of time means
low frequency. If a signal does not change at all, its frequency is zero. If a signal changes
instantaneously, its frequency is infinity.
Phase (Φ)
Phase describes the position of the waveform relative to time 0(origin). Phase is measured in degrees or
radians.
A sine wave with
Phase Starting time
0
0
90
0
180
0
Amplitude
0
peak amplitude
0
Wavelength ()
wavelength () of a signal is the distance occupied by a single cycle, or, put another way, the distance
between two points of corresponding phase of two consecutive cycles. Wavelength binds the period or
frequency of a wave to the propagation speed of the medium.
Wave length = propagation speed x period = propagation speed / frequency
λ = c/f
Assume that the signal is traveling with a velocity v. Then the wavelength is related to the period as
follows:  = vT. Equivalently, f = v. Of particular relevance to this discussion is the case where v = c, the
speed of light in free space, which is approximately 3  108 m/s.
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Frequency Domain Concepts
To show the relationship between the amplitude and frequency, we can use frequency domain concepts.
A frequency domain plot is concerned with only the peak value and the frequency. The position
of the spike shows the frequency; its height shows the peak amplitude.
A complete sine wave in the time domain can be represented by one single spike in the
frequency domain.
Fourier series representation of Periodic Signals
A single frequency wave is not useful in data communications; usually send composite signals
(composite signal is a signal made of many simple sine waves).
According to Fourier analysis, any composite signal is a combination of simple sine waves with
different frequencies, amplitude, and phases. A composite periodic signal with period
T(frequency f) can be decomposed into a series of sine and cosine functions in which each
function is an integral harmonic of the fundamental frequency f of the composite signal. The
result is called Fourier series.
∞
∞
S(t)= A0 + Σ An cos(2πnft) + Σ Bn sin(2πnft)
n=1
n=1
Where A0 is the average value of the signal over a period, An is the coefficient of the nth cosine
component, Bn is the coefficient of the nth sine component
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Sin(x)
Sine(3x)
Sin(x) + 1/3 sin(3x)
sin x + (1/3) sin 3x + . . . + (1/21) sin 21x
tends to the square wave function.
Sine wave with frequency f is the same as that of the composite signal is called the fundamental
frequency or first harmonic. The period of the total signal is equal to the period of the
fundamental frequency.
Frequency, Spectrum and Bandwidth
The signal is a function of time, but it can also be expressed as a function of frequency; that is,
the signal consists of components of different frequencies. It turns out that the frequency
domain view of a signal is more important to an understanding of data transmission than a time
domain view.
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Addition of Frequency Components (T=1/f)
Time domain representation
The components of this signal are just sine waves of frequencies f and 3f, as shown in parts (a) and (b).
Frequency Domain Representations
Spectrum & Bandwidth
The spectrum of a signal is the range of frequencies that it contains.
The absolute bandwidth of a signal is the width of the spectrum
Most of the energy in the signal is contained in a relatively narrow band of frequencies known as the
effective bandwidth, or just bandwidth. The range of frequencies contained in a composite
signal is its bandwidth. The bandwidth of a composite signal is the difference between the highest
and the lowest frequencies contained in that signal.
The following figure shows the concept of bandwidth. The figure depicts two composite signals,
one periodic and the other nonperiodic. The bandwidth of the periodic signal contains all integer
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frequencies between 1000 and 5000 (1000, 1001, 1002, ...). The bandwidth of the nonperiodic signals
has the same range, but the frequencies are continuous.
If a signal includes a component of zero frequency, it is a direct current (dc) or constant component.
Data Rate and Bandwidth
Although a given waveform may contain frequencies over a very broad range, as a practical matter any
transmission system (transmitter plus medium plus receiver) will be able to accommodate only a limited
band of frequencies. This, in turn, limits the data rate that can be carried on the transmission medium.
A square wave has an infinite number of frequency components and hence an infinite bandwidth.
However, the peak amplitude of the kth frequency component, kf, is only 1/k, so most of the energy in this
waveform is in the first few frequency components.
In general, any digital waveform will have infinite bandwidth. If we attempt to transmit this waveform as
a signal over any medium, the transmission system will limit the bandwidth that can be transmitted. For
any given medium, the greater the bandwidth transmitted, the greater the cost. The more limited the
bandwidth, the greater the distortion, and the greater the potential for error by the receiver.
There is a direct relationship between data rate and bandwidth: the higher the data rate of a signal, the
greater is its required effective bandwidth.
DIGITAL SIGNALS
In addition to analog signal, information can also be represented by a digital signal. For example,
a 1 can be encoded as a positive voltage and a 0as zero voltage. A digital signal can have more
than two levels. In this case, we can send more than 1 bit for each level. Figure shows two
signals, one with two levels and the other with four.
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In general, if a signal has L levels, each level needs log2L bits.
Bit Rate
Most digital signals are nonperiodic, and thus period and frequency are not appropriate
characteristics. Instead of frequency bit rate is used to describe digital signals. The bit rate is the
number of bits sent in is, expressed in bits per second (bps).
Bit Length
The bit length is the distance one bit occupies on the transmission medium.
Bit length =propagation speed x bit duration
Digital Signal as a Composite Analog Signal
Based on Fourier analysis, a digital signal is a composite analog signal. The bandwidth is
infinite.
A digital signal, in the time domain, comprises connected vertical and horizontal line segments.
A vertical line in the time domain means a frequency of infinity (sudden change in time); a
horizontal line in the time domain means a frequency of zero (no change in time). Going from a
frequency of zero to a frequency of infinity (and vice versa) implies all frequencies in between
are part of the domain.
Fourier analysis can be used to decompose a digital signal. If the digital signal is periodic, which
is rare in data communications, the decomposed signal has a frequency domain representation
with an infinite bandwidth and discrete frequencies. If the digital signal is nonperiodic, the
decomposed signal still has an infinite bandwidth, but the frequencies are continuous.
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Transmission of Digital Signals
A digital signal can be transmitted by using baseband transmission or broadband transmission
(using modulation).
Baseband Transmission :- Baseband transmission means sending a digital signal over a channel
without changing the digital signal to an analog signal. Baseband transmission a low-pass
channel, a channel with a bandwidth that starts from zero. This is the case if we have a dedicated
medium with a bandwidth constituting only one channel.
Broadband Transmission (Using Modulation) :- Broadband transmission or modulation means
changing the digital signal to an analog signal for transmission. Modulation allows us to use a
bandpass channel-a channel with a bandwidth that does not start from zero. This type of channel
is more available than a low-pass channel. A low-pass channel can be considered a bandpass
channel with the lower frequency starting at zero.
Transmission Impairments
With any communications system, the signal that is received may differ from the signal that is transmitted
due to various transmission impairments. For analog signals, these impairments can degrade the signal
quality. For digital signals, bit errors may be introduced, such that a binary 1 is transformed into a binary
0 or vice versa.
Most significant impairments are
a. attenuation and attenuation distortion
b. delay distortion
c. noise
Attenuation
Attenuation is where the strength of a signal falls off with distance over any transmission medium. For
guided media, this is generally exponential and thus is typically expressed as a constant number of
decibels per unit distance. For unguided media, attenuation is a more complex function of distance and
the makeup of the atmosphere. Attenuation introduces three considerations for the transmission. First, a
received signal must have sufficient strength so that the electronic circuitry in the receiver can detect
the signal. Second, the signal must maintain a level sufficiently higher than noise to be received
without error. Third, attenuation varies with frequency. The first and second problems are dealt with by
attention to signal strength and the use of amplifiers or repeaters. The third problem is particularly
noticeable for analog signals. To overcome this problem, techniques are available for equalizing
attenuation across a band of frequencies. This is commonly done for voice-grade telephone lines by
using loading coils that change the electrical properties of the line; the result is to smooth out attenuation
effects. Another approach is to use amplifiers that amplify high frequencies more than lower
frequencies.
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Delay Distortion
Delay distortion occurs because the velocity of propagation of a signal through a guided medium varies
with frequency. For a band limited signal, the velocity tends to be highest near the center frequency and
fall off toward the two edges of the band. Thus various frequency components of a signal will arrive at the
receiver at different times, resulting in phase shifts between the different frequencies. Delay distortion is
particularly critical for digital data, because some of the signal components of one bit position will spill
over into other bit positions, causing intersymbol interference. This is a major limitation to maximum
bit rate over a transmission channel.
Noise
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 signasl, referred to as
noise, that are inserted somewhere between transmission and reception. Noise is a major limiting factor in
communications system performance. Noise may be divided into four categories.
Thermal noise is due to thermal agitation of electrons. It is present in all electronic devices and
transmission media and is a function of temperature. Thermal noise is uniformly distributed across the
bandwidths typically used in communications systems and hence is often referred to as white noise.
Thermal noise cannot be eliminated and therefore places an upper bound on communications system
performance, and. is particularly significant for satellite communication.
The amount of thermal noise in a bandwidth of 1Hz in any device or conductor is
N0=kT(W/Hz)
Where
N0 = noise power dnsity in W/1Hz
K = Boltzmann’s constant = 1.3803 X 10-23 J/ oK
T = Temperature in kelvin
Thermal Noise can be expressed as
N = kTB
= -228.6 dBW + 10 log T + 10 log B decibel watts
Intermodulation noise
When signals at different frequencies share the same transmission medium, the result may be
intermodulation noise. The effect of intermodulation noise is to produce signals at a frequency that is the
sum or difference of the two original frequencies or multiples of those frequencies, thus possibly
interfering with services at these frequencies. It is produced by nonlinearities in the transmitter, receiver,
and/or intervening transmission medium.
Cross talk
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Crosstalk is an unwanted coupling between signal path. It can occur by electrical coupling between
nearby twisted pairs or coaxial cables carry multiple signals, and can also occur when unwanted signals
are picked up by microwave antennas.
Impulse Noise
Impulse Noise is non-continuous irregular pulses or noise spikes of short duration and relatively high
amplitude. It is generated from external electromagnetic disturbances such as lightning, and fault and
flaws in communication system.
Channel Capacity
The maximum rate at which data can be transmitted over a given communication channel, under given
conditions, is referred to as the channel
relate to one another.
• Data
capacity. There are four concepts here that we are trying to
rate, in bits per second (bps), at which data can be communicated
• Bandwidth, as constrained by the transmitter and the nature of the transmission medium, expressed
in cycles per second, or Hertz
• Noise, average level of noise over the communications path
• Error rate, at which errors occur, where an error is the reception of a 1 when a 0 was transmitted or
the reception of a 0 when a 1 was transmitted
All transmission channels of any practical interest are of limited bandwidth, which arise from the physical
properties of the transmission medium or from deliberate limitations at the transmitter on the bandwidth
to prevent interference from other sources. Want to make as efficient use as possible of a given
bandwidth. For digital data, this means that we would like to get as high a data rate as possible at a
particular limit of error rate for a given bandwidth. The main constraint on achieving this efficiency is
noise.
Nyquist Bandwidth (noiseless channel)
Consider a noise free channel where the limitation on data rate is simply the bandwidth of the signal.
Nyquist states that if the rate of signal transmission is 2B, then a signal with frequencies no greater
than B is sufficient to carry the signal rate. Conversely given a bandwidth of B, the highest signal rate
that can be carried is 2B. This limitation is due to the effect of inter symbol interference, such as is
produced by delay distortion.
If the signals to be transmitted are binary (two voltage levels), then the data rate that can be supported by
B Hz is 2B bps. However signals with more than two levels can be used; that is, each signal element can
represent more than one bit. For example, if four possible voltage levels are used as signals, then each
signal element can represent two bits. With multilevel signaling, the Nyquist formulation becomes:
C = 2B log2 M,
where M is the number of discrete signal or voltage levels.
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So, for a given bandwidth, the data rate can be increased by increasing the number of different signal
elements. However, this places an increased burden on the receiver, as it must distinguish one of M
possible signal elements. Noise and other impairments on the transmission line will limit the practical
value of M.
Shannon Capacity Formula (noisy channel)
Consider the relationship among data rate, noise, and error rate. The presence of noise can corrupt one or
more bits. If the data rate is increased, then the bits become "shorter" so that more bits are affected by a
given pattern of noise. For a given level of noise, expect that a greater signal strength would improve the
ability to receive data correctly in the presence of noise. The key parameter involved is the signal-tonoise ratio (SNR, or S/N), which is the ratio of the power in a signal to the power contained in the noise
that is present at a particular point in the transmission. Typically, this ratio is measured at a receiver,
because it is at this point that an attempt is made to process the signal and recover the data. For
convenience, this ratio is often reported in decibels. This expresses the amount, in decibels, that the
intended signal exceeds the noise level. A high SNR will mean a high-quality signal and a low number of
required intermediate repeaters.
The signal-to-noise ratio is important in the transmission of digital data because it sets the upper bound on
the achievable data rate. Shannon's result is that the maximum channel capacity, in bits per second, obeys
the equation shown. C is the capacity of the channel in bits per second and B is the bandwidth of the
channel in Hertz. The Shannon formula represents the theoretical maximum that can be achieved. In
practice, however, only much lower rates are achieved, in part because formula only assumes white noise
(thermal noise).
SNRdb=10 log10 (signal/noise)
Capacity C=B log2(1+SNR)
Analog and Digital Data Transmission
Define data as entities that convey meaning, or information.
Signals are electric or electromagnetic representations of data.
Signaling is the physical propagation of the signal along a suitable medium.
Transmission is the communication of data by the propagation and processing of signals.
Analog Signals
In a communications system, data are propagated from one point to another by means of
electromagnetic signals. Both analog and digital signals may be transmitted on suitable transmission
media.
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An analog signal is a continuously varying electromagnetic wave that may be propagated over a
variety of media, depending on spectrum; examples are wire media, such as twisted pair and coaxial
cable; fiber optic cable; and unguided media, such as atmosphere or space propagation.
As the above figure illustrates, analog signals can be used to transmit both analog data represented by an
electromagnetic signal occupying the same spectrum, and digital data using a modem
(modulator/demodulator) to modulate the digital data on some carrier frequency.
However, analog signal will become weaker (attenuate) after a certain distance. To achieve longer
distances, the analog transmission system includes amplifiers that boost the energy in the signal.
Unfortunately, the amplifier also boosts the noise components. With amplifiers cascaded to achieve long
distances, the signal becomes more and more distorted. For analog data, such as voice, quite a bit of
distortion can be tolerated and the data remain intelligible. However, for digital data, cascaded amplifiers
will introduce errors.
Digital Signals
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A digital signal is a sequence of voltage pulses that may be transmitted over a wire medium; eg. a
constant positive voltage level may represent binary 0 and a constant negative voltage level may represent
binary 1.
As figure shows, digital signals can be used to transmit both analog signals and digital data. Analog data
can converted to digital using a codec (coder-decoder), which takes an analog signal that directly
represents the voice data and approximates that signal by a bit stream. At the receiving end, the bit stream
is used to reconstruct the analog data. Digital data can be directly represented by digital signals.
A digital signal can be transmitted only a limited distance before attenuation, noise, and other
impairments endanger the integrity of the data. To achieve greater distances, repeaters are used. A
repeater receives the digital signal, recovers the pattern of 1s and 0s, and retransmits a new signal. Thus
the attenuation is overcome.
Advantages & Disadvantages of Digital Signals
1.
2.
3.
4.
cheaper
less susceptible to noise
but greater attenuation
digital now preferred choice
The principal advantages of digital signaling are that it is generally cheaper than analog signaling and is
less susceptible to noise interference. The principal disadvantage is that digital signals suffer more from
attenuation than do analog signals. Above figure shows a sequence of voltage pulses, generated by a
source using two voltage levels, and the received voltage some distance down a conducting medium.
Because of the attenuation, or reduction, of signal strength at higher frequencies, the pulses become
rounded and smaller.
Which is the preferred method of transmission? The answer being supplied by the telecommunications
industry and its customers is digital. Both long-haul telecommunications facilities and intra-building
services have moved to digital transmission and, where possible, digital signaling techniques, for a range
of reasons.