Transcript Lecture 05 - Hong Kong Baptist University

Lecture 05
Making Connections Efficient:
Multiplexing and Compression
1
Making Connections Efficient
• Under simplest conditions, medium can
carry only one signal at any moment in
time
• But, this approach is not efficient. In
practice, multiple signals share a medium.
• The technique used to place multi-signals
onto a medium is called multiplexing
(to p3)
• Different multiplexing techniques
2
Making Connections Efficient
•
Most common multiplexing techniques:
1.
2.
3.
4.
5.
Frequency division multiplexing
Time division multiplexing
Wavelength Division Multiplexing
Discrete Multitone
Code division multiplexing
(to p5)
(to p11)
(to p28)
(to p30)
(to p32)
Comparison
(to p37)
(to p4)
3
Making Connections Efficient
• Data Compression concept
(to p39)
• Application examples
(to p57)
4
Frequency Division Multiplexing
(FDM)
– it is a technique to pack several analog
signals onto a telephone wire
(to p6)
– General concept
– It works this way because a telephone signal
is carried signal range of 0 to 4000 hz
– A twisted pair of wire can carry 1 million hz.
(to p7)
– how multiplexing is done?
5
FIGURE 5-22
Frequency multiplexed voice signals.
(to p5)
6
Frequency Division Multiplexing
(FDM) (cont.)
– we need to transmit a sine wave in the new
freq range, the change of the carrier wave is
called Modulation
– similar token, we would have frequency
modulation ((FM), amplitude modulation (AM),
(to p8)
phase modulation (PM).
– at the other end, we need to demodulation so
that signals are can unscrambled back to the
original form
(to p9)
7
FIGURE 5-23
Amplitude and frequency modulation.
(to p7)
8
Frequency Division Multiplexing
(FDM) (cont.)
– In tel system, the modulation occurs at the
central office, and demodulation takes place
at the serving central office near the user
home/office. (same as MODEM at home?)
– multiplexing equipment (multiplexers) at
central office grouped as shown in
» Figure 5-24
(to p10)
• 12 voice channels grouped as a base group
• 5 base groups into a super group
• 10 super groups into a master group
(to p3)
9
FIGURE 5-24
The hierarchy of voice channels as they are multiplexed together.
(to p9)
10
Time division Multiplexing
(TDM)
– is a technique uses to divide a circuit’s
capacity into time slots so that data could be
transmitted in a long distance on a single
circuit without the need of the regeneration
(why important?)
– Digital signaling is used exclusively
– Time division multiplexing comes in two basic
forms:
to p12)
• Synchronous time division multiplexing
• Statistical time division multiplexing
(
(to
p22)
(to
11
p3)
Synchronous Time Division
Multiplexing
• Sharing of the signal is accomplished by
dividing available transmission time on a
medium among users
– A TDM takes one character from each
terminal and group them into a frame before
transmit them on the circuit
– At the end, another TDM breaks down the
frame and direct individual message to
respective receivers
(to
p13)
12
(TDM)
– TDM effect is totally a transparent to users,
terminal and computer
– total # of terminals could be packed into a
TDM is depended on capability of a circuit
• Eg:
If a circuit has a speed of 9600 bps, then
it may carry 4 x 2400 pbs or 8 x 1200 pbs etc
(to
13
p14)
(TDM)
– it takes one bit from each terminal instead
of one character and transmit a frame in bit
(to
(to
p15)
(to
p11)
p18)
– Different between FDM and TDM
(to
p19)
(to
p20)
– T-1 and ISDN telephone lines are common
examples of synchronous time division
multiplexing. (what is T-1 and ISDN?)
– Similar applied to Sonet system
14
Synchronous Time Division
Multiplexing (continued)
(to
p16)
Mechanical data-transmission procedure
(to
15
p14)
Synchronous Time Division
Multiplexing (continued)
• If one device generates data at 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 something (by
reserving a blank!) into the multiplexed stream,
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
(to p17)
16
Synchronous Time Division
Multiplexing (continued)
(to
p15)
17
FIGURE 9-14 FDM channels have full time use of a limited range of frequencies. TDM channels can use the full range of frequencies but only during
predetermined time slots.
(to
p14)
18
T-1 Multiplexing
• The T-1 multiplexor stream is a continuous
series of frames
(to
19
p14)
ISDN Multiplexing
– The ISDN multiplexor stream is also a
continuous series of frames
– Each frame contains various control and sync
info
(to
20
p14)
SONET/SDH Multiplexing
– Likewise, SONET incorporates a continuous
series of frames
(to p14)
21
2) Statistical TDM (STDM)
– does not assign a specific time slot for each
terminal, but transmit terminals address along
with each character or message of data
i.e. A statistical multiplexor transmits the data from active workstations only
– If a workstation is not active, no space is wasted in the multiplexed stream
– it avoids of having empty slot in a frame, and
attempt to allocate next terminal has data to
send so that efficiency rate is improved
– See Figure 9-16
(to
p23)
(to
22
p25)
(to p22)
FIGURE 9-16 The STDM tries to avoid having empty slots in a frame, thereby improving the line use. If a terminal has no data to send in a particular
time period, the STDM will see if the next terminal has data that can be included in the time slot. When the STDM at the receiving end breaks the frame
apart, it uses the terminal address to route the data to the proper device.
(to
p24)
Alternative layout
23
(to
24
p23)
STDM
to p26)
– Its mechanical steps
– STDM requires a storage area (ie buffer) so
that data can be saved until line can accept
for transmission
– Typically, it has buffer size up to 32,000 char,
but may encounter a slighter delay for
transmission when buffering is occurred
– In STDM, 12 terminals running at 1200 pbs
could be handled by a 9600 pbs line in most
cases
(
(to
25
p11)
How it works
• To identify each piece of data, an address
is included, see Figure 5-10 to p27)
• If the data is of variable size, a length is
also included, see Figure 5-11 to p27)
• More precisely, the transmitted frame
contains a collection of data groups, see
(
(
Figure 5-12
(to
p27)
(to
p25)
26
(to
(to
p26)
(to
p26)
p26)
27
Wavelength Division
Multiplexing
• Wavelength division multiplexing multiplexes multiple
(to p29)
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 or more) onto one fiber
• Coarse wavelength division multiplexing combines only a
few lambdas
(to
28
p3)
Wavelength Division
Multiplexing (continued)
(to
29
p28)
Discrete Multitone
• Discrete Multitone (DMT) – a multiplexing
technique commonly found in digital subscriber
to p31)
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
(
(to
30
p3)
Discrete Multitone (continued)
(to
p30)
31
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
• To send a binary 1, a mobile device transmits the unique
code
• To send a binary 0, a mobile devices transmits the
inverse of the code
• 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
(to
32
p33)
Code Division Multiplexing
(continued)
• For simplicity, assume 8-bit code
• Example
– Three different mobile devices 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
– Signal code: 1-chip = +N volt; 0-chip = -N volt
(to
33
p34)
Code Division Multiplexing
(continued)
• Example (continued)
– 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
(to
34
p35)
Code Division Multiplexing
(continued)
• Example (continued)
– Base station decode for Mobile A:
• Signal received: +3, -1, -1, +1, +1, -1, -3, +3
• Mobile A’s code: +1, -1, +1, +1, +1, -1, -1, +1
• Product result: +3, +1, -1, +1, +1, +1, +3, +3
– Sum of Products: +12
– Decode rule: For result near +8, data is binary
1
(to
35
p36)
Code Division Multiplexing
(continued)
• Example (continued)
– Base station decode for Mobile B:
• Signal received: +3, -1, -1, +1, +1, -1, -3, +3
• Mobile A’s code: -1, +1, +1, -1, +1, +1, +1, -1
• Product result: -3, -1, -1, -1, +1, -1, -3, -3
– Sum of Products: -12
– Decode rule: For result near -8, data is binary
0
(to
36
p3)
Comparison of Multiplexing
Techniques
(to
37
p38)
Comparison of Multiplexing
Techniques (continued)
(to
38
p3)
Compression–Lossless versus Lossy
•
Compression is another technique used to
squeeze more data over a communications
line
–
•
If you can compress a data file down to one half of
its original size, file will obviously transfer in less
time
Two basic groups of compression:
1. Lossless – when data is uncompressed, original
(to p41)
data returns
2. Lossy – when data is uncompressed, you do not
(to p44)
have the original data
(to p40)
1 vs 2
(to
39
p4)
Compression–Lossless versus
Lossy (continued)
• 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
(to
40
p39)
Lossless Compression
• Run-length encoding
– Replaces runs of 0s with a count of how many
0s.
00000000000000100000000011000000000000000000001…11000000
00000
^
(30 0s)
14
9
0
20
30
0
11
(to
41
p42)
Lossless Compression
(continued)
• Run-length encoding (continued)
– 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 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
(to
42
p43)
Lossless Compression
(continued)
• Run-length encoding (continued)
– 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
(to
43
p39)
Lossy Compression
• Relative or differential encoding
– Video does not compress well using runlength 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.
(to
44
p45)
Lossy Compression (continued)
5762866356
6575563247
8468564885
5129865566
First Frame
5762866356
6576563237
8468564885
5139865576
Second Frame
0000000000
0 0 0 1 0 0 0 0 -1 0
0000000000
0010000010
Difference
(to
45
p46)
Lossy Compression (continued)
• Image Compression
– One image (JPEG) or continuous images
(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!)
(to
46
p47)
Lossy Compression (continued)
• Image Compression (continued)
– 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!
• JPEG (Joint Photographic Experts Group)
– Compresses still images
– Lossy
– JPEG compression consists of 3 phases:
• Discrete cosine transformations (DCT)
• Quantization
• Run-length encoding
(to
47
p48)
Lossy Compression (continued)
• 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 B&W, 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)
(to
48
p49)
Lossy Compression (continued)
80 blocks
60 blocks
640 x 480 VGA Screen Image
Divided into 8 x 8 Pixel Blocks
(to
49
p50)
Lossy Compression (continued)
• JPEG Step 1 – DCT (continued)
– 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
(to
50
p51)
Lossy Compression (continued)
• JPEG Step 1 – DCT (continued)
– 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
– 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
(to
51
p52)
Lossy Compression (continued)
• JPEG Step 2 -Quantization
– The human eye can’t see small differences in
color
• So take T matrix and divide all values by 10
– Will give us more zero entries
» More 0s means more compression!
– But this is too lossy
– And dividing all values by 10 doesn’t take into account
that upper left of matrix has more action (the less subtle
features of the image, or low spatial frequencies)
(to
52
p53)
Lossy Compression (continued)
1
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13
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U matrix
Q[i][j] = Round(T[i][j] / U[i][j]), for i = 0, 1, 2, …7 and
j = 0, 1, 2, …7
(to
53
p54)
Lossy Compression (continued)
• JPEG Step 3 – Run-length encoding
– Now take the quantized matrix Q and perform
run-length encoding on it
• But don’t just go across the rows
– Longer runs of zeros if you perform the run-length
encoding in a diagonal fashion
(to
54
p55)
Lossy Compression (continued)
(to
55
p56)
Lossy Compression (continued)
• 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
(to
56
p39)
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
to p58)
• List some efficient techniques to link the
two buildings.
to p59)
•
Possible solution
(
(
57
Business Multiplexing In Action
(continued)
(to
58
p57)
Business Multiplexing In Action
(continued)
• 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
59