Data and Computer
Communications
Chapter 3 – Data Transmission
Tenth Edition
by William Stallings
Lecture slides by Lawrie Brown
Learning Objectives

After studying this chapter, you should be able to:
 Distinguish between digital and analog information
sources.
 Explain the various ways in which audio, data, image, and
video can be represented by electromagnetic signals.
 Discuss the characteristics of analog and digital
waveforms.
 Discuss the various transmission impairments that affect
signal quality and information transfer over communication
media.
 Identify the factors that affect channel capacity.
 The
Introduction
successful transmission of data depends
principally on two factors:
 the quality of the signal being transmitted and
 the characteristics of the transmission medium
 Either analog or digital data may be transmitted
using either analog or digital signals.
 Furthermore, it is common for intermediate
processing to be performed between source and
destination, and this processing has either an
analog or digital character.
Transmission Terminology
 data
transmission occurs between a
transmitter & receiver via some medium.
 Transmission media may be classified as :
 guided medium

eg. twisted pair, coaxial cable, optical fiber
 unguided

 In
/ wireless medium
eg. air, water, vacuum
both cases, communication is in the
form of electromagnetic waves.
Transmission Terminology
 direct

link
no intermediate devices other than amplifiers
or repeaters used to increase signal strength
 point-to-point


Provides a direct link between two devices
only 2 devices share link/medium
 multi-point

more than two devices share the link/medium
Transmission Terminology



Simplex Transmission
 Signal are transmitted in only one direction (one station
is transmitter and the other is receiver)
• eg. television
half duplex
 both stations may transmit, but only one at a time
 either direction, but only one way at a time
• eg. police radio
full duplex
 both directions at the same time (both stations may
transmit simultaneously, and the medium is carrying
signals in both directions at the same time).
• eg. telephone
Frequency, Spectrum and
Bandwidth

time domain concepts
 analog signal
• is one in which the signal intensity varies in a
smooth, or continuous, fashion over time.
• In other words, there are no breaks or
discontinuities in the signal

digital signal
• one in which the signal intensity maintains a
constant level then changes to another constant
level.
 periodic signal
• Same signal pattern repeated over time
 aperiodic signal
• pattern not repeated over time
Frequency, Spectrum and
Bandwidth

time domain concepts
 analog signal
• is one in which the signal intensity varies in a
smooth, or continuous, fashion over time.
• In other words, there are no breaks or
discontinuities in the signal

digital signal
• one in which the signal intensity maintains a
constant level then changes to another constant
level.
Analogue & Digital Signals
Analogue & Digital Signals
…….. Signal
……. Signal
Frequency, Spectrum and
Bandwidth





periodic signal
• Same signal pattern repeated over time
aperiodic signal
• pattern not repeated over time.
Periodic analog signals can be classified as
simple or composite.
A simple periodic analog signal, a sine wave,
cannot be decomposed into simpler signals.
A composite periodic analog signal is
composed of multiple sine waves.
Periodic Signals




Sine Wave
The sine wave is the fundamental periodic signal. A general
sine wave can be represented by three parameters:
peak amplitude (A)
 maximum value or strength of the signal over time
 Measured in volts
frequency (f)
 rate of change of signal ( i.e the rate [in cycles per second, or
Hertz (Hz)] at which the signal repeats)
 Hertz (Hz) or cycles per second
 An equivalent parameter is the period (T) of a signal
 period = time for one repetition (T)
 T = 1/f
and f=1/T
phase ()
 Is a measure of the relative position in time within a single
period of a signal.
Two signals with the same phase and
frequency,
but different amplitudes
Frequency
 Frequency is the rate of change with respect to time.
 Change in a short span of time means high frequency.
 Change over a 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
infinite
Two signals with the same amplitude and
phase,
but different frequencies
Unites of Period and frequency
Example 1
 The
power we use at home has a
frequency of 60 Hz. The period of this sine
wave can be determined as follows:
Example 2
 The
period of a signal is 100 ms. What
is its frequency in kilohertz?
Ans of Example 2
phase ()
 Phase
describes the position of the
waveform relative to time 0.
 Is a measure of the relative position in time
within a single period of a signal.
phase ()
 Three
sine waves with the same
amplitude and frequency, but different
phases
Example
A
sine wave is offset 1/6 cycle with
respect to time 0. What is its phase in
degrees and radians?
Solution
 We
know that 1 complete cycle is 360°.
Therefore, 1/6 cycle is
(2π radians = 360˚ = 1 period).
Varying Sine Waves
s(t) = A sin(2ft +)
Wavelength ()
 is
distance occupied by one cycle
 In another way, it is the distance between
two points of corresponding phase in two
consecutive cycles
 assuming signal is traveling with a velocity
v have  = vT
 or equivalently f = v
 especially when v=c

c = 3*108 ms-1 (speed of light in free space is 3
8
Frequency Domain Concepts
 signal
are made up of many frequencies
 components are sine waves
 By adding together enough sinusoidal
signals, each with the appropriate
amplitude, frequency, and phase, any
electromagnetic signal can be constructed
(figure 3.4 c).
 Fourier analysis can shown that any signal
is made up of component sine waves
 can plot frequency domain functions
Addition of
Frequency
Components
(T=1/f)
c
is sum of f & 3f
The time-domain and frequency-domain
plots of a sine wave
Note
A
complete sine wave in the time domain
can be represented by one single spike in
the frequency domain
Example
 The
frequency domain is more compact
and useful when we are dealing with more
than one sine wave.
 For example, Next Figure shows three
sine waves, each with different amplitude
and frequency. All can be represented by
three spikes in the frequency domain
Figure : The time domain and frequency domain of
three sine waves
Frequency
Domain
Representations

freq domain func of
Fig 3.4c
 freq domain func of
single square pulse
Spectrum & Bandwidth

spectrum


absolute bandwidth


width of spectrum
effective bandwidth
 often just bandwidth


range of frequencies contained in signal
narrow band of frequencies containing most energy of
the signal.
DC Component

If a signal includes a component of zero frequency, it
is a direct current (dc) or constant component.
Data Rate and Bandwidth






Any transmission system has a limited band of
frequencies
this limits the data rate that can be carried
A square wave have infinite number of
frequency components and hence an infinite
bandwidth
but most energy in first few 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.
Data Rate and Bandwidth
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.

Analog and Digital Data
Transmission

The terms analog and digital correspond, roughly,
to continuous and discrete, respectively.
 data
 entities that convey meaning or information
 signals & signaling
 electric or electromagnetic representations of
data, physically propagates along medium
 transmission
 communication of data by propagation and
processing of signals
Analog and digital Data
 Analog data:
 take on continuous values in some interval.
 For example, voice and video are continuously varying
patterns of intensity.
 Most data collected by sensors, such as temperature and
pressure, are continuous valued.
 Digital data:
 take on discrete values;
 examples are text and integers.
Analog and digital Data
 The most familiar example of analog data is audio, which, in
the form of acoustic sound waves, can be perceived directly
by human beings.
 Figure 3.9 shows the acoustic spectrum for human speech
and for music.
 Frequency components of typical speech may be found
between approximately 100 Hz and 7 kHz.
 Although much of the energy in speech is concentrated at the
lower frequencies, tests have shown that frequencies below
600 or 700 Hz add very little to the intelligibility of speech to
the human ear.
 Typical speech has a dynamic range of about 25 dB
(decibels) ;
 the power produced by the loudest shout may be as much as
300 times greater than the least whisper.
Acoustic Spectrum (Analog)
Audio Signals

freq range 20Hz-20kHz (speech 100Hz-7kHz)
 easily converted into electromagnetic signals
 varying volume converted to varying voltage
 can limit frequency range for voice channel to
300-3400Hz
Video Signals

USA - 483 lines per frame, at frames per sec


525 lines x 30 scans = 15750 lines per sec



have 525 lines but 42 lost during vertical retrace
63.5s per line
11s for retrace, so 52.5 s per video line
max frequency if line alternates black and white
 horizontal resolution is about 450 lines giving
225 cycles of wave in 52.5 s
 max frequency of 4.2MHz
Digital Data

A familiar example of digital data is text or character
strings
 as generated by computers etc.
 A commonly used signal for such data uses two constant
(dc) voltage levels, one level for binary 1 and one level for
binary bandwidth depends on data rate
Analog and Digital Signals
 In a communications system, data are propagated from
one point to another by means of electromagnetic signals.
 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.
 Digital signal is a sequence of voltage pulses that may be
transmitted over a wire medium; for example, a constant
positive voltage level may represent binary 0 and a
constant negative voltage level may represent binary 1.
Analog and Digital Signals
 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
Figure 3.10 Attenuation of Digital Signals
Analog and Digital Signals
 Because
of the attenuation, or reduction,
of signal strength at higher frequencies,
the pulses become rounded and smaller.
 It should be clear that this attenuation can
lead rather quickly to the loss of the
information contained in the propagated
signal.
Analog Signals
Analog Signals
Figure 3.11 Conversion of Voice Input to Analog
Signal
Digital Signals
Analog signals of analog and
digital data
Digital signaling of analog
and digital data
Analog and Digital
Transmission
Analog and Digital
Transmission
Advantages & Disadvantages
of Digital Signals
 digital
now preferred choice.
 Reasons:


Digital technology: The advent of large-scale integration
(LSI) and very-largescale integration (VLSI) technology
has caused a continuing drop in the cost and size of
digital circuitry.
Data integrity: With the use of repeaters rather than
amplifiers, the effects of noise and other signal
impairments are not cumulative. Thus, it is possible to
transmit data longer distances and over lower quality lines
by digital means while maintaining the integrity of the data
Advantages & Disadvantages
of Digital Signals



Capacity utilization: It has become economical to build
transmission links of very high bandwidth, including satellite
channels and optical fiber. A high degree of multiplexing is
needed to utilize such capacity effectively, and this is more
easily and cheaply achieved with digital (time division) rather
than analog (frequency division) techniques.
Security and privacy: Encryption techniques can be readily
applied to digital data and to analog data that have been
digitized.
Integration: By treating both analog and digital data digitally,
all signals have the same form and can be treated similarly.
Thus economies of scale and convenience can be achieved
by integrating voice, video, and digital data
Transmission Impairments
 signal
received may differ from signal
transmitted causing:


analog - degradation of signal quality
digital - bit errors
 most



significant impairments are
attenuation and attenuation distortion
delay distortion
noise
Attenuation

where signal strength falls off with distance
 depends on medium
 received signal strength must be:


strong enough to be detected
sufficiently higher than noise to be received without
error

so increase strength using amplifiers/repeaters
 is also an increasing function of frequency
 so equalize attenuation across band of
frequencies used

eg. using loading coils or amplifiers
Delay Distortion





only occurs in guided media because the velocity
of propagation of a signal through a guided medium
varies with frequency.
hence various frequency components arrive at
different times
particularly critical for digital data
since parts of one bit spill over into others
causing intersymbol interference
Noise


additional signals inserted between transmitter and
receiver
thermal





due to thermal agitation of electrons
It is present in all electronic devices and transmission media
and is a function of temperature
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.
Because of the weakness of the signal received by satellite
earth stations, thermal noise is particularly significant for
satellite communication
Noise

thermal

The amount of thermal noise to be found in a bandwidth of 1
Hz in any device or conductor is
Noise

thermal
Noise

thermal
Noise

intermodulation
 signals that are the sum and difference of original
frequencies sharing a medium.
 For example, if two signals, one at 4000 Hz and one
at 8000 Hz, share the same transmission facility, they
might produce energy at 12,000 Hz. This noise could
interfere with an intended signal at 12,000 Hz.
 Intermodulation noise is produced by nonlinearities in
the
transmitter, receiver,
and/or
intervening
transmission medium. Ideally, these components
behave as linear systems; that is, the output is equal
to the input times a constant
Noise


Crosstalk/ an unwanted coupling between signal paths
 a signal from one line is picked up by another
impulse
 irregular pulses or spikes
• eg. external electromagnetic interference
 short duration
 high amplitude
 It is generated from a variety of causes, including
external electromagnetic disturbances, such as
lightning, and faults and flaws in the communications
system
 a minor annoyance for analog signals
 but a major source of error in digital data
• a noise spike could corrupt many bits
Noise
Figure 3.15 Effect of Noise on a Digital Signal
Channel Capacity




max possible data rate on comms channel
is a function of

data rate - in bits per second (bps), at which data can be
communicated

bandwidth - The bandwidth of the transmitted signal as
constrained by the transmitter and the nature of the transmission
medium, expressed in cycles per second, or Hertz

noise - The 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.
limitations due to physical properties
want most efficient use of capacity
Nyquist Bandwidth






consider noise free channels 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
for binary signals, 2B bps needs bandwidth B Hz
can increase rate by using M signal levels
Nyquist Formula is: C = 2B log2M
so increase rate by increasing signals
 at cost of receiver complexity
 limited by noise & other impairments
Shannon Capacity Formula

consider relation of data rate, noise & error rate


faster data rate shortens each bit so bursts of noise
affects more bits
given noise level, higher rates means higher errors

Shannon developed formula relating these to
signal to noise ratio (in decibels)
 SNRdb=10 log10 (signal power/noise power)
 Capacity C=B log2(1+SNR)


theoretical maximum capacity
get lower in practise
Summary
 looked
at data transmission issues
 frequency, spectrum & bandwidth
 analog vs digital signals
 transmission impairments