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ENGS 4 Lecture 12 Technology of Cyberspace Winter 2004 Thayer School of Engineering Dartmouth Colleg

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Title: ENGS 4 Lecture 12 Technology of Cyberspace Winter 2004 Thayer School of Engineering Dartmouth Colleg


1
ENGS 4 - Lecture 12Technology of Cyberspace
Winter 2004Thayer School of EngineeringDartmouth
College
  • Instructor George Cybenko, x6-3843
  • gvc_at_dartmouth.edu
  • Assistant Sharon Cooper (Shay), x6-3546
  • Course webpage http//thayer.dartmouth.edu/engs
    004/

2
Todays Class
  • Sarah (social inequality/digital divide)
  • Ryan (internet dating)
  • Noah R. (nanotechnology)
  • Leo
  • Break
  • Lempel-Ziv Coding
  • Digitalization of analog signals
  • Wireless networking basics

3
Future mini-lectures
  • Feb 24 Dason (pornography), En Young
    (persistence), Rob (GPS), Simon (online games)

4
Break
5
Models of a source
We can easily measure the probability of each
symbol in English. How? How about the
probabilities of each pair of symbols? Triples?
Sentences? True model of English model of
language model of thought This is very hard.
6
Lempel-Ziv Coding (zip codes, etc)
Want to encode a string aaabcababcaaa into
0s and 1s. Step 1 Convert to 0s and 1s by
any prefix substitution. a00 b01 c11 00000001
110001000111000000
7
Lempel-Ziv Coding (zip codes, etc)
Step 2 Parse the string into never before
seen strings. 00000001110001000111000000 0,00,0
00,01,1,10,001,0001,11,0000,00
8
Lempel-Ziv Coding (zip codes, etc)
Step 3 Assign binary numbers to
each. 0,00,000,01,1,10,001,0001,11,0000,00 0001
,0010,0011,0100,0101,0110,0111,1000,1001,1010,1011
Step 4 To each string, assign number of
substring plus last bit. 00000,00010,00100,00011,
00001,01010,00101, 000000001000100000110000101010
00101...
9
Lempel-Ziv Coding (zip codes, etc)
Step 5 Store this string plus length of labels
in bits. 00000,00010,00100, 1111000000001000100
.... This may be inefficient for small examples
but for very long inputs, it achieves the entropy
for the best model. LZW Lempel-Ziv-Welsch,
GIF image interchange standard
10
Example
What is the Lempel Ziv encoding of 00000...0000
(N 0s)? What is the entropy of the source? How
many bits per symbol will be used in the
encoded data as N goes to infinity? Lets work
out the details. How about 0100100010000100000100
00001.... ?
11
Properties of Lempel-Ziv
For most sources (alphabetsprobabilities),
the Lempel-Ziv algorithm will result in average
number of bits per symbol entropy of the source
(any order model) if the string/data to be
compressed is long enough. How about compressing
the compressed string? That is, applying
Lempel-Ziv again and again? Answer The
compressed bit string will look completely
random 0 or 1 with probability 1/2. Entropy
1 means 1 bit per symbol on average. No
improvement is possible.
12
Analog vs Digital
  • Most real world phenomena is continuous
  • images
  • vision
  • sound
  • touch
  • To transmit it, we must convert continuous
    signals
  • into digital signals.
  • Important note
  • There is a fundamental shift from continuous to
  • digital representation of the real world.

13
The Fundamental Shift
The telephone system is designed to carry
analog voice signals using circuit switching.
The whole infrastructure is based on that. When
a modem connects your computer to the
network over a telephone line, the modem must
disguise the computer data as a speech/voice
signal. The infrastructure of the internet is
totally digital. Sending voice over the internet
requires disguising voice as digital
data!!! This is a fundamental turnaround....same
will hold for TV, cable TV, audio, etc.
14
Analog to Digital Conversion
are samples
111 110 101 100 011 010 001 000
d 2d 3d 4d 5d 6d 7d 8d 9d 10d
11d 12d time
15
Analog to Digital Conversion
are samples
111 110 101 100 011 010 001 000
d 2d 3d 4d 5d 6d 7d 8d 9d 10d
11d 12d time
d is the sampling interval, 1/d is the
sampling rate
16
Sampling and quantization
In this example, we are using 8 quantization
levels which requires 3 bits per sample. Using
8 bits per sample would lead to 256 quantization
levels, etc. If the sampling interval is
1/1000000 second (a microsecond), the sampling
rate is 1000000 samples per second or 1
megaHertz. Hertz means number per second so
20,000 Hertz means 20,000 per second. So
sampling at 20 kiloHertz means 20,000 samples
per second
17
Analog frequencies
All real world signals can be represented as a
sum or superposition of sine waves with
different frequencies - Fourier
representation theorem. The frequency of a sine
wave is the number of times it oscillates in a
second. Sine wave with frequency 20 will
complete a cycle or period once every 1/20th of
a second so 20 times a second, etc. We say that
a sine wave with frequency 20 is a 20 Hertz
signal.....oscillates 20 times a second.
18
Fourier Java Applet
http//www.falstad.com/fourier/
19
Nyquist Sampling Theorem
  • If an analog signal is bandlimited (ie consists
    of frequencies in a finite range 0, F), then
    sampling must be at or above the twice the
    highest frequency to reconstruct the signal
    perfectly.
  • Does not take quantization into account.
  • Sampling at lower than the Nyquist rate will lead
    to aliasing.

20
Sampling for Digital Voice
  • High quality human voice is 4000 Hz
  • Sampling rate is 8000 Hz
  • 8 bit quantization means 64,000 bits per second
  • Phone system built around such a specification
  • Computer communications over voice telephone
    lines is limited to about 56kbps

21
Implications for Digital Audio
  • Human ear can hear up to 20 kHz
  • Sampling at twice that rate means 40 kHz
  • Quantization at 8 bits (256 levels)
  • 40,000 samples/second x 8 bits/ sample translates
    to 320,000 bits per second or 40,000 bytes per
    second.
  • 60 seconds of music 2,400,000 Bytes
  • 80 minutes about 190 Mbytes
  • Audio CD??

22
Some Digital Audio Links
  • http//www.musiq.com/recording/mp3/index.html
  • http//www.musiq.com/recording/digaudio/bitrates.h
    tml
  • Aliasing in Images
  • http//www.telacommunications.com/nutshell/pixelat
    ion.htmenlargement
  • Other
  • http//www.physics.nyu.edu/faculty/sokal/papers

23
Introduction to Wireless Networks
Radio frequency constraints Current
standards Current limitations
24
Atmospheric Propagation of RF
400km 250km 220km 200km 150km 90km 50km
F2
F2 F1 E D
F1
E
D
Height above ground
EARTH
Electron Density
Layers in the ionosphere
25
Refraction of Radiowaves
30 MHz
F2
20 MHz
F1
30 MHz
E
20 MHz
D
10 MHz
EARTH
26
Resulting Classes of RF Waves
27
Interior Path Loss Function
(Frequency dependent)
d
Powertransmitted - Powerreceived Lp L 10n
log10 (d) lognorm(v)
Experimentally and statistically determined - n
is signal decay exponent, L is path loss at d1m,
lognorm is log-normal distribution with variance
v.
28
Ambient Noise and Absorption
Power required for constant signal/(ambient noise)
Power for constant received signal power
Power required
Sweet Spot
Frequency
1GHz 2GHz
29
Digital bps vs Analog Hz
Digital bandwidth of B bits per second can be
encoded into an analog signal of roughly B Hertz.
The B Hz signal is attached to a C Hz carrier
resulting in a signal that lives in the interval
C,CB Hz. Example 2.4 - 2.45 GHz can carry
50 Mbps.
30
Current Standards
Cellular Digital Packet Data (CDPD) 19.2 kbps
extension of cellular telephone network Wireless
LANs 1-2 Mbps using 2.4 GHz ISM (Industrial,
Scientific Medical) band. Range 30-250 meters.
IEEE 802.11 standard in place. Products by
Lucent, Digital, etc. 500 PCMCIA radio
transceiver. gt 1000 for base. Wireless
WANs Metricom Richocet technology (US only).
28.8 kbps with a range of about 1 km.
31
Architecture
Access point (base station)
Multihop not implemented
Handoffs between access points in the same subnet
- else need mobile IP
Wired network
32
Satellite Communications Upswing
Name Speed Cost Receiver Start
Date Satellites Planet 1 9.6kbps 3/min
Notebook Now 5 GEOs ICO Globalcom 64kbps
1.50/min Dual-mode 2000 10
MEOs (Inmarsat) Iridium 2.4kpbs 3/min
Handset 1998 66 LEOs (Motorola) Globa
lstar 9.6kbps lt1/min Dual-mode 1998
48 GEOs Cyberstar 6mbps ??
Home dish 2000
3 GEOs (Loral) Odyssey 9.6kbps 0.95/min
Handset 2001 12 MEOs
(TRW) 64kbps 0.65/min Dish
Teledesic
2mbps 100s Dish 2002 288
LEOs (Gates/McCaw) /month
33
Glossary
LEOs - Low Earth Orbit about 1,000 kms above
earth MEOs - Medium Earth Orbit about 10,000
kms GEOs - Geostationary/Geosynchronous Earth
Orbit about 36,000 kms Dual-mode handset
supports both satellite and cellular communication
s.
34
Cellular Technology
  • Frequencies used in cell phones have limited
  • spatial propagation - this is good....we can
    reuse them.
  • But adjacent cells cannot use the same
    frequencies if the
  • phones are frequency multiplexed
  • So must multiplex based on space as well.

Cells of different colors use different frequencie
s.
35
Frequency Division Multiple Access (FDMA)
Freq 1 Freq 2 Freq 3
Time
User A User B User C
Within a cell users are allocated a single
frequency.
36
Time Division Multiple Access (TDMA)
Freq 1
Time
User A User B User C
Within a cell users are allocated time slots
within a single frequency.
37
Code Division Multiple Access (CDMA)
Freq 1 Freq 2 Freq 3
Time
User A User B User C
Within a cell users are allocated different
frequencies at different times.
38
Different Multiple Access Concepts
TDMA - examples?? FDMA - examples?? CDMA -
examples?? SDMA - examples??
39
Implications for Wireless Networking
  • Mobile users will experience varying delivered
    bandwidth.
  • Connections will be intermittent, unreliable.
  • Spatial multiplexing (cellular architecture) is
    required.
  • Bandwidth will be a precious resource.
  • Battery technology is very important.
  • Antenna size and type is a factor.
  • Security - eavesdropping, jamming.
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