Multiplexing : Sharing a Medium

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Data Communications and Computer Networks A
Business Users Approach

• Chapter 5
• Multiplexing Sharing a Medium

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Introduction Under the simplest conditions, a
medium can carry only one signal at any moment in
time. For multiple signals to share one medium,
the medium must somehow be divided, giving each
signal a portion of the total bandwidth. The
current techniques that can accomplish this
include frequency division multiplexing, time
division multiplexing, and code division
multiplexing.
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Frequency Division Multiplexing Assignment of
non-overlapping frequency ranges to each user
or signal on a medium. Thus, all signals are
transmitted at the same time, each using
different frequencies. A multiplexor accepts
inputs and assigns frequencies to each device.
The multiplexor is attached to a high-speed
communications line. A corresponding multiplexor,
or demultiplexor, is on the end of the high-speed
line and separates the multiplexed signals.
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Frequency Division Multiplexing Analog signaling
is used to transmits the signals. Broadcast radio
and television, cable television, and the AMPS
cellular phone systems use frequency division
multiplexing. This technique is the oldest
multiplexing technique. Since it involves analog
signaling, it is more susceptible to noise.
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Time Division Multiplexing Sharing of the signal
is accomplished by dividing available
transmission time on a medium among
users. Digital signaling is used
exclusively. Time division multiplexing comes in
two basic forms 1. Synchronous time division
multiplexing, and 2. Statistical, or asynchronous
time division multiplexing.
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Synchronous Time Division Multiplexing The
original time division multiplexing. The
multiplexor accepts input from attached devices
in a round-robin fashion and transmit the data in
a never ending pattern. T-1 and ISDN telephone
lines are common examples of synchronous time
division multiplexing.
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Synchronous Time Division Multiplexing If one
device generates data at a faster rate than other
devices, then the multiplexor must either sample
the incoming data stream from that device more
often than it samples the other devices, or
buffer the faster incoming stream. If a device
has nothing to transmit, the multiplexor must
still insert a piece of data from that device
into the multiplexed stream.
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So that the receiver may stay synchronized with
the incoming data stream, the transmitting
multiplexor can insert alternating 1s and 0s into
the data stream.
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The T-1 multiplexor stream is a continuous series
of frames.

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The ISDN multiplexor stream is also a continuous
stream of frames. Each frame contains various
control and sync info.

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Statistical Time Division Multiplexing A
statistical multiplexor transmits only the data
from active workstations. If a workstation is not
active, no space is wasted on the multiplexed
stream. A statistical multiplexor accepts the
incoming data streams and creates a frame
containing only the data to be transmitted.
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To identify each piece of data, an address is
included.
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If the data is of variable size, a length is also
included.
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More precisely, the transmitted frame contains a
collection of data groups.

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Wavelength Division Multiplexing Wavelength
division multiplexing multiplexes multiple data
streams onto a single fiber optic line. Different
wavelength lasers (called lambdas) transmit the
multiple signals. Each signal carried on the
fiber can be transmitted at a different rate from
the other signals. Dense wavelength division
multiplexing combines many (30, 40, 50, 60,
more?) onto one fiber. Coarse wavelength division
multiplexing combines only a few lambdas.

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Discrete Multitone (DMT) A multiplexing technique
commonly found in digital subscriber line (DSL)
systems DMT combines hundreds of different
signals, or subchannels, into one stream Each
subchannel is quadrature amplitude modulated
(recall - eight phase angles, four with double
amplitudes) Theoretically, 256 subchannels, each
transmitting 60 kbps, yields 15.36 Mbps.
Unfortunately, there is noise.
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Code Division Multiplexing Also known as code
division multiple access An advanced technique
that allows multiple devices to transmit on the
same frequencies at the same time. Each mobile
device is assigned a unique 64-bit code (chip
spreading code) To send a binary 1, mobile device
transmits the unique code To send a binary 0,
mobile device transmits the inverse of code
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Code Division Multiplexing Receiver gets summed
signal, multiplies it by receiver code, adds up
the resulting values Interprets as a binary 1 if
sum is near 64 Interprets as a binary 0 if sum
is near 64
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• Code Division Multiplexing Example
• For simplicity, assume 8-chip spreading codes
• 3 different mobiles use the following codes
• Mobile A 10111001
• Mobile B 01101110
• Mobile C 11001101
• Assume Mobile A sends a 1, B sends a 0, and C
  sends a 1

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Code Division Multiplexing Example Signal code
1-chip N volt 0-chip -N volt Three signals
transmitted -Mobile A sends a 1, or 10111001, or
--- -Mobile B sends a 0, or 10010001, or
----- -Mobile C sends a 1, or 11001101, or
--- Summed signal received by base station
3, -1, -1, 1, 1, -1, -3, 3
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Code Division Multiplexing Example Base station
decode for Mobile A Signal received 3, -1, -1,
1, 1, -1, -3, 3 Mobile As code 1, -1, 1,
1, 1, -1, -1, 1 Product result 3, 1, -1,
1, 1, 1, 3, 3 Sum of Product results
12 Decode rule For result near 8, data is
binary 1
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Code Division Multiplexing Example Base station
decode for Mobile B Signal received 3, -1, -1,
1, 1, -1, -3, 3 Mobile Bs code -1, 1, 1,
-1, 1, 1, 1, -1 Product result -3, -1, -1,
-1, 1, -1, -3, -3 Sum of Product results
-12 Decode rule For result near -8, data is
binary 0
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Business Multiplexing In Action XYZ Corporation
has two buildings separated by a distance of 300
meters. A 3-inch diameter tunnel extends
underground between the two buildings. Building A
has a mainframe computer and Building B has 66
terminals. List some efficient techniques to link
the two buildings.
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Possible Solutions Connect each terminal to the
mainframe computer using separate point-to-point
lines. Connect all the terminals to the mainframe
computer using one multipoint line. Connect all
the terminal outputs and use microwave
transmissions to send the data to the
mainframe. Collect all the terminal outputs using
multiplexing and send the data to the mainframe
computer using a conducted line.
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Compression This is another technique used to
squeeze more data over a communications line If
you can compress a data file down to ½ of its
original size, the file will obviously transfer
in less time Two basic groups of
compression Lossless when data is
uncompressed, original data returns Lossy
when data is uncompressed, you do not have the
original data
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Compression Compress a financial file? You want
lossless. Compress a video image, movie, or audio
file? Lossy is OK Examples of lossless
compression include Huffman codes, run-length
compression, and Lempel-Ziv compression Examples
of lossy compression include MPEG, JPEG, MP3
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Run-Length Compression Replace runs of 0s with a
count of how many 0s. 000000000000001000000000110
00000000000000000001000001100000000000
(30 0s) 14 9 0
20 30 0 11
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Run-Length Compression Now replace each decimal
value with a 4-bit binary value (nibble). Note
If you need to code a value larger than 15, you
need to use two code two consecutive 4-bit
nibbles. The first is decimal 15, or binary
1111, and the second nibble is the remainder.
For example, if the decimal value is 20, you
would code 1111 0101 which is equivalent to 15
5. If you want to code the value 15, you still
need two nibbles 1111 0000. The rule is that if
you ever have a nibble of 1111, you must follow
it with another nibble.
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Relative or Differential Encoding (Lossy) Video
does not compress well using run-length
encoding In one color video frame, not much is
alike But what about from frame to frame? Send
a frame, store it in a buffer Next frame is just
difference from previous frame Then store that
frame in buffer, etc.

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5 7 6 2 8 6 6 3 5 6 6 5 7 5 5 6 3 2 4 7 8 4 6 8 5
6 4 8 8 5 5 1 2 9 8 6 5 5 6 6 First Frame
5 7 6 2 8 6 6 3 5 6 6 5 7 6 5 6 3 2 3 7 8 4 6 8 5
6 4 8 8 5 5 1 3 9 8 6 5 5 7 6 Second Frame
0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 -1 0 0 0 0 0
0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 Difference
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Image Compression One image - JPEG, or
continuous images such as video - MPEG A color
picture can be defined by red/green/blue, or
luminance / chrominance / chrominance which are
based on RGB values Either way, you have 3
values, each 8 bits, or 24 bits total (224
colors!)
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Image Compression A VGA screen is 640 x 480
pixels 24 bits x 640 x 480 7,372,800 bits.
Ouch! And video comes at you 30 images per
second. Double Ouch! We need compression!
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JPEG Joint Photographic Experts
Group Compresses still images Lossy JPEG
compression consists of 3 phases Discrete
cosine transformations (DCT) Quantization Encodi
ng
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JPEG Step 1 -DCT Divide image into a series of
8x8 pixel blocks If the original image was
640x480 pixels, the new picture would be 80
blocks x 60 blocks (next slide) If BW, each
pixel in 8x8 block is an 8-bit value (0-255) If
color, each pixel is a 24-bit value (8 bits for
red, 8 bits for blue, and 8 bits for green)
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80 blocks
60 blocks
640 x 480 VGA Screen Image Divided into 8 x 8
Pixel Blocks
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JPEG Step 1 -DCT So what does DCT do? Takes an
8x8 array (P) and produces a new 8x8 array (T)
using cosines T matrix contains a collection of
values called spatial frequencies. These
spatial frequencies relate directly to how much
the pixel values change as a function of their
positions in the block
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JPEG Step 1 -DCT An image with uniform color
changes (little fine detail) has a P array with
closely similar values and a corresponding T
array with many zero values (next slide) An
image with large color changes over a small area
(lots of fine detail) has a P array with widely
changing values, and thus a T array with many
non-zero values
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JPEG Step 2 -Quantization The human eye cant
see small differences in color So take T matrix
and divide all values by 10. This will give us
more zero entries. More 0s means more
compression! But this is too lossy. And
dividing all values by 10 doesnt take into
account that upper left of matrix has more action
(the less subtle features of the image, or low
spatial frequencies)
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1 3 5 7 9 11 13 15 3 5
7 9 11 13 15 17 5 7 9
11 13 15 17 19 7 9 11 13 15
17 19 21 9 11 13 15 17 19 21
23 11 13 15 17 19 21 23 25 13 15
17 19 21 23 25 27 15 17 19 21 23
25 27 29
U matrix
Qij Round(Tij / Uij), for i 0, 1,
2, 7 and j 0, 1, 2, 7
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JPEG Step 3 -Encoding Now take the quantized
matrix Q and perform run-length encoding on
it But dont just go across the rows. Longer
runs of zeros if you perform the run-length
encoding in a diagonal fashion
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JPEG How do you get the image back? Undo
run-length encoding Multiply matrix Q by matrix
U yielding matrix T Apply similar cosine
calculations to get original P matrix back