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CSCD 433 Network Programming Fall 2012

CSCD 433 Network Programming Fall 2012. Lecture 4a Physical Layer Line Coding. 1. Physical Layer Topics. Physical limits of networks for data Encoding data onto signals. 2. Physical Layer . Looked at physical media for networks Many types of wired and wireless connections

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CSCD 433 Network Programming Fall 2012

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  1. CSCD 433Network Programming Fall 2012 Lecture 4a Physical Layer Line Coding 1

  2. Physical Layer Topics • Physical limits of networks for data • Encoding data onto signals 2

  3. Physical Layer Looked at physical media for networks Many types of wired and wireless connections All have different capacities and purposes with regards to network creation Next, look at some theoretical limits of networks, encoding schemes for digital modulation and several multiplexing methods

  4. Data Rate Limits Important consideration in data communications is How fast we can send data, in bits per second, over a channel? Data rate depends on three factors: 1. The available bandwidth 2. The number of levels used to represent signals 3. The quality of the channel (the level of noise)

  5. Nyquist Maximum 1924, Henry Nyquist of AT&T developed an equation for a perfect channel with finite capacity His equation expresses Maximum data rate for a finite bandwidth noiseless channel

  6. Noiseless Channel: Nyquist Bit Rate Defines theoretical maximum bit rate for Noiseless Channel: Bit Rate=2 X Bandwidth X log2L L = number of signal levels

  7. Example Have a noiseless channel Bandwidth of 3000 Hz transmitting a signal with two signal levels The maximum bit rate can be calculated as Bit Rate = 2  3000  log2 2 = 6000 bps

  8. Example Consider the same noiseless channel Transmitting a signal with four signal levels • For each level, we send two bits The maximum bit rate can be calculated as: Bit Rate = 2 x 3000 x log2 4 = 12,000 bps

  9. Note Increasing the levels of a signal may reduce the reliability of the system

  10. Claude ShannonNoisy Channel Claude Shannon developed mathematical theory in the 1940's for noisy channels He used Entropy in his equation, which is the amount of randomness for a channel Then, defined the amount of information that a message could carry This allowed networks to plan for capacity of information

  11. Noisy Channel: Shannon Capacity Defines theoretical maximum bit rate for Noisy Channel: Capacity=Bandwidth X log2(1+SNR)

  12. Example Consider an extremely noisy channel in which the value of the signal-to-noise ratio is almost zero In other words, the noise is so strong that the signal is faint For this channel the capacity is calculated as C = B log2 (1 + SNR) = B log2 (1 + 0)= B log2 (1) = B  0 = 0

  13. Example We can calculate the theoretical highest bit rate of a regular telephone line A telephone line normally has a bandwidth of 4KHz The signal-to-noise ratio is usually 3162 For this channel the capacity is calculated as C = B log2 (1 + SNR) = 3000 log2 (1 + 3162) = 3000 log2 (3163) C = 3000  11.62 = 34,860 bps

  14. Example We have a channel with a 1 MHz bandwidth The SNR for this channel is 63, What is the appropriate bit rate and signal level? Solution First, we use the Shannon formula to find our upper limit C = B log2 (1 + SNR) = 106 log2 (1 + 63) = 106 log2 (64) = 6 Mbps Then we use the Nyquist formula to find the number of signal levels. 6 Mbps = 2  1 MHz  log2L  L = 8

  15. Digital Modulation

  16. Digital Modulation Process of converting between bits and signals is called digital modulation Convert voltages into bits Mostly for wired media Other schemes regulate the phase or frequency of a carrier signal Mostly for wireless media

  17. Line Coding Schemes

  18. Note In unipolar encoding, we use only one voltage level, positive

  19. Unipolar Encoding

  20. Note In polar encoding, we use two voltage levels: positive & negative

  21. Polar: NRZ-L and NRZ-I Encoding

  22. Note In NRZ-L, level of voltage determines value of the bit In NRZ-I, inversion or lack of inversion determines value of the bit

  23. Polar: RZ Encoding

  24. Polar: Manchester Encoding

  25. Note In Manchester and differential Manchester encoding, the transition at the middle of the bit is used for synchronization.

  26. Note In bipolar encoding, we use three levels: positive, zero, and negative.

  27. Bipolar: AMI (Alternative Mark Inversion) Encoding

  28. Summary

  29. Summary Many types of encoding for sending data over analog types of lines Multiplexing allows sharing More on this later …. There are actually limits to how much data can be sent within a network

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