2. ENGS4 2004 Lecture 13 ENGS 4 - Lecture 13 Technology of Cyberspace Winter 2004 Thayer School of Engineering Dartmouth College Instructor: George Cybenko, x6-3843 gvc@dartmouth.edu Assistant: Sharon Cooper (“Shay”), x6-3546 Course webpage: http://thayer.dartmouth.edu/~engs004/ http://thayer.dartmouth.edu/~engs004/

3. ENGS4 2004 Lecture 13 Today’s Class Final Projects Lempel-Ziv Example Ryan (internet dating) Dason (pornography) Digitalization of analog signals Break En Young (persistence) Rob (GPS) Simon (online games) Wireless networking basics

4. ENGS4 2004 Lecture 13 Schedule Final Project Presentations: March 2, 4, 9 Assignment 3: Due March 4 Take-home Final Exam: March 11, due March 16

5. ENGS4 2004 Lecture 13 Example What is the Lempel Ziv encoding of 00000...0000 (N 0’s)? What is the entropy of the source? How many bits per symbol will be used in the encoded data as N goes to infinity? Let’s work out the details. How about 010010001000010000010000001.... ?

6. ENGS4 2004 Lecture 13 Properties of Lempel-Ziv For most sources (alphabets+probabilities), 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.

7. ENGS4 2004 Lecture 13 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.

8. ENGS4 2004 Lecture 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.

9. ENGS4 2004 Lecture 13 Analog to Digital Conversion 111 110 101 100 011 010 001 000 d 2d 3d 4d 5d 6d 7d 8d 9d 10d 11d 12d time are samples

10. ENGS4 2004 Lecture 13 Analog to Digital Conversion 111 110 101 100 011 010 001 000 d 2d 3d 4d 5d 6d 7d 8d 9d 10d 11d 12d time are samples d is the “sampling interval”, 1/d is the sampling “rate”

11. ENGS4 2004 Lecture 13 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”

12. ENGS4 2004 Lecture 13 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.

13. ENGS4 2004 Lecture 13 Fourier Java Applet http://www.falstad.com/fourier/

14. ENGS4 2004 Lecture 13 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”.

15. ENGS4 2004 Lecture 13 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

16. ENGS4 2004 Lecture 13 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??

17. ENGS4 2004 Lecture 13 Some Digital Audio Links http://www.musiq.com/recording/mp3/index.html http://www.musiq.com/recording/digaudio/bitrates.html Aliasing in Images http://www.telacommunications.com/nutshell/pixelation.h tm#enlargementhttp://www.telacommunications.com/nutshell/pixelation.h tm#enlargement Other http://www.physics.nyu.edu/faculty/sokal/#papers

18. ENGS4 2004 Lecture 13 Introduction to Wireless Networks Radio frequency constraints Current standards Current limitations

19. ENGS4 2004 Lecture 13 Atmospheric Propagation of RF EARTH D F1F1 F2F2 E 400km 250km 220km 200km 150km 90km 50km Height above ground Electron Density F2F1EDF2F1ED Layers in the ionosphere

20. ENGS4 2004 Lecture 13 Refraction of Radiowaves EARTH F2F2 F1F1 E D 30 MHz 20 MHz 30 MHz 20 MHz 10 MHz

21. ENGS4 2004 Lecture 13 Resulting Classes of RF Waves Ground Wave 10-3000 kHz Sky Wave 3-30 MHz Space Wave 30-3000 MHz Communications satellite > 3GHz

22. ENGS4 2004 Lecture 13 Interior Path Loss Function d Power transmitted - Power received = L p = L + 10n log 10 (d) +lognorm(v) Experimentally and statistically determined - n is signal decay exponent, L is path loss at d=1m, lognorm is log-normal distribution with variance v. (Frequency dependent)

23. ENGS4 2004 Lecture 13 Ambient Noise and Absorption Frequency Power required Power required for constant signal/(ambient noise) Power for constant received signal power 1GHz 2GHz Sweet Spot

24. ENGS4 2004 Lecture 13 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,C+B] Hz. Example: 2.4 - 2.45 GHz can carry 50 Mbps.

25. ENGS4 2004 Lecture 13 Current Standards Cellular Digital Packet Data (CDPD) 19.2 kbps extension of cellular telephone network Wireless LAN’s 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. > $1000 for base. Wireless WAN’s Metricom Richocet technology (US only). 28.8 kbps with a range of about 1 km.

26. ENGS4 2004 Lecture 13 Architecture Access point (base station) Wired network Multihop not implemented Handoffs between access points in the same subnet - else need mobile IP

27. ENGS4 2004 Lecture 13 Satellite Communications Upswing NameSpeed Cost ReceiverStart DateSatellites Planet 19.6kbps $3/min NotebookNow5 GEO’s ICO Globalcom 64kbps $1.50/min Dual-mode200010 MEO’s (Inmarsat) Iridium2.4kpbs $3/min Handset 199866 LEO’s (Motorola) Globalstar9.6kbps <$1/min Dual-mode 1998 48 GEO’s Cyberstar6mbps ?? Home dish 2000 3 GEO’s (Loral) Odyssey9.6kbps $0.95/min Handset 2001 12 MEO’s (TRW) 64kbps $0.65/min Dish Teledesic 2mbps $100’s Dish2002288 LEO’s (Gates/McCaw) /month

28. ENGS4 2004 Lecture 13 Glossary LEO’s - Low Earth Orbit about 1,000 kms above earth MEO’s - Medium Earth Orbit about 10,000 kms GEO’s - Geostationary/Geosynchronous Earth Orbit about 36,000 kms Dual-mode handset supports both satellite and cellular communications.

29. ENGS4 2004 Lecture 13 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 frequencies. is a cell in which certain frequencies are allowed to be used.

30. ENGS4 2004 Lecture 13 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.

31. ENGS4 2004 Lecture 13 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.

32. ENGS4 2004 Lecture 13 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.

33. ENGS4 2004 Lecture 13 Different Multiple Access Concepts TDMA - examples?? FDMA - examples?? CDMA - examples?? SDMA - examples??

34. ENGS4 2004 Lecture 13 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.