1. 01204325: Data Communication and Computer Networks
Digital Transmission
: Data Communication and Computer Networks
Asst. Prof. Chaiporn Jaikaeo, Ph.D.
Computer Engineering Department
Kasetsart University, Bangkok, Thailand
Adapted from lecture slides by Behrouz A. Forouzan
© The McGraw-Hill Companies, Inc. All rights reserved

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

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

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

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

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

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

12. Line Coding Methods Unipolar Polar Bipolar Multilevel
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. Unipolar Simplest form of digital encoding
Rarely used
Only one polarity of voltage is used
E.g., polarity assigned to 1 t 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. 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 t 1 t 1
N = Bit rate
Save = Average signal rate

16. 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 t 1 ?

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

18. 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 t 1

19. 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 - t 1

20. 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 t 1
Bipolar AMI
B8ZS V B
V – Bipolar violation
B – Valid bipolar signal

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

22. Block Coding Improves the performance of line coding Provides
Synchronization
Error detection t
Division
Substitution
Line Coding
… … : :

23. 4B/5B Encoding Table Data Code Data Code 0000 11110 1000 10010 0001
01001
1001
10011
0010
10100
1010
10110
0011
10101
1011
10111
0100
01010
1100
11010
0101
01011
1101
11011
0110
01110
1110
11100
0111
01111
1111
11101
Data
Code
Q (Quiet)
00000
I (Idle)
11111
H (Halt)
00100
J (start delimiter)
11000
K (start delimiter)
10001
T (end delimiter)
01101
S (Set)
11001
R (Reset)
00111

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

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

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

27. PCM: Quantization
Quantization

28. Quantization Error Assume sine-wave input and uniform quantization
Known as the 6 dB/bit approximation
See also:

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

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