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Digital Transmission

Digital Transmission. Outline. Line coding Encoding considerations DC components in signals Synchronization Various line coding methods. Line Coding. Process of converting binary data to digital signal. Signal Levels vs. Data Levels. Number of signal levels

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Digital Transmission

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  1. Digital Transmission

  2. Outline • Line coding • Encoding considerations • DC components in signals • Synchronization • Various line coding methods

  3. Line Coding • Process of converting binary data to digital signal

  4. Signal Levels vs. Data Levels • Number of signal levels • Number of different voltage levels allowed in a signal • Number of data levels • Number of voltage levels that actually represent data values

  5. Signal vs. Data Elements

  6. 00 11 01 10 01 10 11 00 +3 +1 t -1 -3 One pulse(one signal element) Pulse Rate vs. Bit Rate b – number of bits per pulse L – number of different signal elements BitRate = PulseRate× b = PulseRate × log2L Bit rate  Bits per second Pulse rate  Baud (pulses or signals per second)

  7. Pulse Rate vs. Bit Rate • Example: In Manchester Encoding, if the bit rate is 10 Mbps, what is the pulse rate? 0 1 0 0 1 1 0 1 t One pulse(one signal element) One bit

  8. Encoding Considerations • Signal spectrum • Lack of DC components • Lack of high frequency components • Clocking/synchronization • Error detection • Noise immunity • Cost and complexity

  9. 0 1 0 0 1 1 0 1 t 0 1 0 0 1 1 0 1 t DC Components • DC components in signals are not desirable • Cannot pass thru certain devices • Leave extra (useless) energy on the line Signal with DC component Signal without DC component

  10. 0 1 0 0 1 1 0 1 Sender sends: 01001101 t 0 1 0 0 0 1 1 0 1 1 t Synchronization • To correctly decode a signal, receiver and sender must agree on bit interval Receiver sees: 0100011011

  11. data Sender Receiver clock 0 1 0 0 1 1 0 1 t Providing Synchronization • Separate clock wire • Self-synchronization

  12. Line Coding Methods • Unipolar • Uses only one voltage level (one side of time axis) • Polar • Uses two voltage levels (negative and positive) • E.g., NRZ, RZ, Manchester, Differential Manchester • Bipolar • Uses three voltage levels (+, 0, and –) for data bits • Multilevel

  13. 0 1 0 0 1 1 0 0 t Unipolar • Simplest form of digital encoding Rarely used • Only one polarity of voltage is used • E.g., polarity assigned to 1

  14. Polar Encoding • Two voltage levels (+,-) represent data bits • Most popular four • Nonreturn-to-Zero (NRZ) • Return-to-Zero (RZ) • Manchester • Differential Manchester

  15. 0 1 0 0 1 1 1 0 t 0 1 0 0 1 1 1 0 t NRZ Encoding • Nonreturn to Zero • NRZ-L (NRZ-Level):Signal level depends on bit value • NRZ-I (NRZ-Invert): Signal is inverted if 1 is encountered N = Bit rate Save = Average signal rate

  16. 0 1 0 0 1 1 0 0 t RZ Encoding • Return to Zero • Uses three voltage levels: +, - and 0, but only + and - represent data bits • Half way thru each bit, signal returns to zero ?

  17. = 0 0 1 0 0 1 1 0 1 t = 1 Manchester Encoding • Uses an inversion at the middle of each bit • For bit representation • For synchronization

  18. 0 1 0 0 1 1 0 1 t Differential Manchester Encoding • The inversion on the middle of each bit is only for synchronization • Transition at the beginning of each bit tells the value

  19. 0 1 0 0 1 1 0 1 t Bipolar Encoding • Bipolar encoding uses three voltage levels: +, - and 0 • Each of all three levels represents a bit • E.g., Bipolar AMI (Alternate Mark Inversion) • 0V always represents binary 0 • Binary 1s are represented by alternating + and -

  20. 1 1 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 1 0 Bipolar AMI t 0 0 0 V B 0 V B B8ZS BnZS Schemes • BnZS – Bipolar n-zero substitution • Based on Bipolar AMI • n consecutive zeros are substituted with some +/- levels • provides synchronization during long sequence of 0s • E.g., B8ZS V – Bipolar violation B – Valid bipolar signal

  21. 00 11 01 10 01 10 11 00 +3 +1 t -1 -3 Bit sequence Voltage level 00 -3 01 -1 10 +3 11 +1 Other Schemes • mBnL • m data elements are substituted with n signal elements • E.g., 2B1Q (two binary, 1 quaternary)

  22. t Block Coding • Improves the performance of line coding • Provides • Synchronization • Error detection Division Substitution LineCoding …01011010001… : 001011010001 : : 101100101101010 :

  23. 4B/5B Encoding Table

  24. PAM PAM signal(Sampled analog data) Analog signal Analog to Digital Conversion • Pulse Amplitude Modulation (PAM) • Converts an analog signal into a series of pulses by sampling

  25. Pulse Code Modulation (PCM) • Converts an analog signal into a digital signal • PAM • Quantization • Binary encoding • Line coding

  26. 6 4 Output 2 0 1 2 3 4 5 6 7 Input PCM: Quantization • Converts continuous values of data to a finite number of discrete values

  27. PCM: Quantization Quantization

  28. Quantization Error • Assume sine-wave input and uniform quantization • Known as the 6 dB/bit approximation See also: http://en.wikipedia.org/wiki/Quantization_error#Quantization_noise_model

  29. Example: Quantization Error • A telephone subscriber line must have an SNRdB above 40. What is the minimum number of bits per sample? Solution We can calculate the number of bits as Telephone companies usually assign 7 or 8 bits per sample.

  30. PCM: Binary Encoding • Maps discrete values to binary digits

  31. PCM: The Whole Process

  32. t sampling interval Minimum Sampling Rate • Nyquist Theorem: Sampling rate must be greater than twice the highest frequency Ex.Find the maximum samplinginterval for recording human voice(freq. range 300Hz – 3000Hz)

  33. Nyquist’s Sampling Theorem See also: Wagon-wheel effect Demo: sampling.py

  34. Sampling and Bit Rate • Ex.Calculate the minimum bit rate for recoding human voice, if each sample requires 60 levels of precision

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