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Chapter 6:
Data Transmission
Business Data Communications, 4e
Electromagnetic Signals
Function of time
Analog (varies smoothly over time)
Digital (constant level over time, followed by a
change to another level)
Function of frequency (more important)
Spectrum (range of frequencies)
Bandwidth (width of the spectrum)
Periodic Signal Characteristics
Amplitude (A): signal value, measured in volts
Frequency (f): repetition rate, cycles per second
or Hertz
Period (T): amount of time it takes for one
repetition, T=1/f
Phase (f): relative position in time, measured in
degrees
Bandwidth
Width of the spectrum of frequencies that can
be transmitted
if spectrum=300 to 3400Hz, bandwidth=3100Hz
Greater bandwidth leads to greater costs
Limited bandwidth leads to distortion
Why Study Analog in a Data
Comm Class?
Much of our data begins in analog form; must
understand it in order to properly convert it
Telephone system is primarily analog rather
than digital (designed to carry voice signals)
Low-cost, ubiquitous transmission medium
If we can convert digital information (1s and 0s)
to analog form (audible tone), it can be
transmitted inexpensively
Data vs Signals
Analog data
Voice
Images
Digital data
Text
Digitized voice or images
amplitude (volts)
Analog Signaling
1 cycle
represented
by sine waves
phase
difference
time
(sec)
frequency (hertz)
= cycles per second
Voice/Audio Analog Signals
Easily converted from sound frequencies
(measured in loudness/db) to electromagnetic
frequencies, measured in voltage
Human voice has frequency components
ranging from 20Hz to 20kHz
For practical purposes, the telephone system
has a narrower bandwidth than human voice,
from 300 to 3400Hz
Image/Video: Analog Data to
Analog Signals
Image is scanned in lines; each line is
displayed with varying levels of intensity
Requires approximately 4Mhz of analog
bandwidth
Since multiple signals can be sent via the
same channel, guardbands are necessary,
raising bandwidth requirements to 6Mhz per
signal
amplitude (volts)
Digital Signaling
1 cycle
represented
by square waves or pulses
time
(sec)
frequency (hertz)
= cycles per second
Digital Text Signals
Transmission of electronic pulses
representing the binary digits 1 and 0
How do we represent letters, numbers,
characters in binary form?
Earliest example: Morse code (dots and
dashes)
Most common current form: ASCII
Digital Image Signals
Analog facsimile
similar to video scanning
Digital facsimile, bitmapped graphics
uses pixelization
Object-oriented graphics
image represented using library of objects
e.g. Postscript, TIFF
Pixelization and Binary
Representation
Used in digital fax, bitmapped graphics
1-bit code:
00000000
00111100
01110110
01111110
01111000
01111110
00111100
00000000
Transmission Media
the physical path between transmitter and
receiver (“channel”)
design factors affecting data rate
bandwidth
physical environment
number of receivers
impairments
Impairments and Capacity
Impairments exist in all forms of data
transmission
Analog signal impairments result in random
modifications that impair signal quality
Digital signal impairments result in bit errors
(1s and 0s transposed)
Transmission Impairments:
Guided Media
Attenuation
loss of signal strength over distance
Attenuation Distortion
different losses at different frequencies
Delay Distortion
different speeds for different frequencies
Noise
distortions of signal caused by interference
Transmission Impairments:
Unguided (Wireless) Media
Free-Space Loss
Signals disperse with distance
Atmospheric Absorption
Water vapor and oxygen contribute to signal loss
Multipath
Obstacles reflect signal creating multiple copies
Refraction
Noise
Types of Noise
Thermal (aka “white noise”)
Uniformly distributed, cannot be eliminated
Intermodulation
When different frequencies collide (creating
“harmonics”)
Crosstalk
Overlap of signals
Impulse noise
Channel Capacity
The rate at which data can be transmitted
over a given path, under given conditions
Four concepts
Data rate
Bandwidth
Noise
Error rate
Shannon Equation
C = B log2 (1 + SNR)
B = Bandwidth
C= Channel
SNR = Signal-to-noise ratio