1 lecture 05 making connections efficient: multiplexing and compression

1

Lecture 05

Making Connections Efficient: Multiplexing and Compression

2

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

• Different multiplexing techniques (to p3)

3


• Most common multiplexing techniques:

1. Frequency division multiplexing2. Time division multiplexing3. Wavelength Division Multiplexing4. Discrete Multitone5. Code division multiplexing

Comparison(to p4)

(to p28)

(to p11)

(to p5)

(to p37)

(to p32)

(to p30)

4


• Data Compression concept

• Application examples (to p57)

(to p39)

5

Frequency Division Multiplexing (FDM)

– it is a technique to pack several analog signals onto a telephone wire

– 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.– how multiplexing is done?

(to p6)

(to p7)

6

FIGURE 5-22 Frequency multiplexed voice signals.

(to p5)

7

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), phase modulation (PM).

– at the other end, we need to demodulation so that signals are can unscrambled back to the original form

(to p8)

(to p9)

8

FIGURE 5-23 Amplitude and frequency modulation.

(to p7)

9

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

• 12 voice channels grouped as a base group• 5 base groups into a super group• 10 super groups into a master group

(to p10)

(to p3)

10

FIGURE 5-24 The hierarchy of voice channels as they are multiplexed together.

(to p9)

11

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:• Synchronous time division multiplexing• Statistical time division multiplexing

(to p12)

(to p22)

(to p3)

12

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)

13

(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 p14)

14

(TDM)– it takes one bit from each terminal instead

of one character and transmit a frame in bit

– Different between FDM and TDM

– 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

(to p11)

(to p20)(to p19)

(to p18)

(to p15)

15

Synchronous Time Division Multiplexing (continued)

Mechanical data-transmission procedure(to p14)

(to p16)

16


• 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)

17


(to p15)

18

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)

19

T-1 Multiplexing

• The T-1 multiplexor stream is a continuous series of frames

(to p14)

20

ISDN Multiplexing

– The ISDN multiplexor stream is also a continuous series of frames

– Each frame contains various control and sync info

(to p14)

21

SONET/SDH Multiplexing

– Likewise, SONET incorporates a continuous series of frames

(to p14)

22

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 p25)

23

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 p22)

Alternative layout

(to p24)

24

(to p23)

25

STDM

– 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 p11)

(to p26)

26

How it works

• To identify each piece of data, an address is included, see Figure 5-10

• If the data is of variable size, a length is also included, see Figure 5-11

• More precisely, the transmitted frame contains a collection of data groups, see Figure 5-12

(to p25)

(to p27)

(to p27)

(to p27)

27

(to p26)

(to p26)

(to p26)

28

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 or more) onto one fiber

• Coarse wavelength division multiplexing combines only a few lambdas

(to p3)

(to p29)

29

Wavelength Division Multiplexing (continued)

(to p28)

30

Discrete Multitone

• 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(to p3)

(to p31)

31

Discrete Multitone (continued)

(to p30)

32

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 p33)

33

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 p34)

34


• 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 p35)

35


• 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 p36)

36


• 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 p3)

37

Comparison of Multiplexing Techniques

(to p38)

38

Comparison of Multiplexing Techniques (continued)

(to p3)

39

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 data

returns

2. Lossy – when data is uncompressed, you do not have the original data

1 vs 2

(to p4)

(to p41)

(to p44)

(to p40)

40

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 p39)

41

Lossless Compression

• Run-length encoding– Replaces runs of 0s with a count of how many

0s.00000000000000100000000011000000000000000000001…

1100000000000

^

(30 0s)

14 9 0 20 30 0 11

(to p42)

42

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 p43)

43

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 p39)

44

Lossy Compression

• Relative or differential encoding – 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.

(to p45)

45

5 7 6 2 8 6 6 3 5 66 5 7 5 5 6 3 2 4 78 4 6 8 5 6 4 8 8 55 1 2 9 8 6 5 5 6 6First Frame

5 7 6 2 8 6 6 3 5 66 5 7 6 5 6 3 2 3 78 4 6 8 5 6 4 8 8 55 1 3 9 8 6 5 5 7 6Second Frame

0 0 0 0 0 0 0 0 0 00 0 0 1 0 0 0 0 -1 00 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0Difference

Lossy Compression (continued)

(to p46)

46


• 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 p47)

47


• 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 p48)

48


• 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 p49)

49

80 blocks

60 blocks

640 x 480 VGA Screen ImageDivided into 8 x 8 Pixel Blocks


(to p50)

50


• 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 p51)

51


• 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 p52)

52


• 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 p53)

53

1 3 5 7 9 11 13 153 5 7 9 11 13 15 175 7 9 11 13 15 17 197 9 11 13 15 17 19 219 11 13 15 17 19 21 2311 13 15 17 19 21 23 2513 15 17 19 21 23 25 2715 17 19 21 23 25 27 29

U matrix

Q[i][j] = Round(T[i][j] / U[i][j]), for i = 0, 1, 2, …7 andj = 0, 1, 2, …7


(to p54)

54


• 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 p55)

55


(to p56)

56


• 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 p39)

57

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.

• Possible solution(to p59)

(to p58)

58

Business Multiplexing In Action (continued)

(to p57)

59

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

1 lecture 05 making connections efficient: multiplexing and compression

Documents