Telecommunications Concepts

1. Chapter 1.4 Communications Theory TelecommunicationsConcepts

2. Data transmission fundamentals Parallel vs. serial transmission Synchronous vs. asynchronous communications Analog vs. digital communications Shannon’s theorem Eye diagrams Transmission error correction Redundant encoding Sliding window error correction Encoding and modulation Contents

3. Data transmission fundamentals Parallel vs. serial transmission Synchronous vs. asynchronous communications Analog vs. digital communications Shannon’s theorem Eye diagrams Transmission error correction Redundant encoding Sliding window error correction Encoding and modulation Contents

4. Clock Parallel Transmission Disadvantages : Differences in propagation delay Cost of multiple communication channels

5. Serial Data Clock Serial Transmission

6. Serial Data + Clock Serial Transmissionwith clock/data multiplexing

7. Data transmission fundamentals Parallel vs. serial transmission Synchronous vs. asynchronous communications Analog vs. digital communications Shannon’s theorem Eye diagrams Transmission error correction Redundant encoding Sliding window error correction Encoding and modulation Contents

8. Clock + Serial Data Synchronous Transmission DTE DTE • Data is carried by the clock signal Rx clock extracted by DCE DCE DCE • Tx clock in DTE or DCE Modem Modem

9. 1 1 0 0 1 Clock Synchronous Transmission

10. Serial Data + Clock synchronization Asynchronous Transmission The DCE’s just transmit data bits. Provisions for Clock synchronization need to be included in data DTE DTE DCE DCE Modem Modem

11. Start-stop synchronization clock Designed for electro-mechanical terminals Still used in modern electronic terminals !

12. DTE DTE μP μP DCE DCE Modem Modem External PC modems Most external PC modems use an asynchronous link between the PC and the modem and a synchronous link between the modems. The modem contains a microcomputer that buffers the data Asynchronous links(serial port or USB) Synchronous link

13. Data transmission fundamentals Parallel vs. serial transmission Synchronous vs. asynchronous communications Analog vs. digital communications Shannon’s theorem Eye diagrams Transmission error correction Redundant encoding Sliding window error correction Encoding and modulation Contents

14. Digital Data Communications 011001 TX Analog communication channel 011001 RX

15. Transmitter (Tx) Input : stream of binary numbers Output : stream of analog signals suitable for transmission over long distances Receiver (Rx) Input : stream of analog signals generated by transmitter distorted by transmission channel Compares each input signal with all signals which could have been transmitted and decides from which one the input is a distorted image. Output : stream of binary numbers, preferably identical to the input of the transmitter Encoding and Decodingdigital signals

16. Data transmission fundamentals Parallel vs. serial transmission Synchronous vs. asynchronous communications Analog vs. digital communications Shannon’s theorem Eye diagrams Transmission error correction Redundant encoding Sliding window error correction Encoding and modulation Contents

17. Bandwidth Difference between highest and lowest frequency of sine waves which can be transmitted Number of possible state changes per second Signal to Noise ratio S/N = (signal power) / (noise power) S/N determines number of distinct states which can be distinguished within a given observation interval Analog Transmission Channel Characterized by : Received power Frequency

18. t t +8V 11 +6V 1 +4V 10 +8V +2V 0V -2V 01 0 -4V 0V -6V 00 -8V -8V Binary vs. Multi-bit encoding Noise margin = +/- 4 V Noise margin = +/- 2 V Modulation rate = 1/t (in Baud) Data rate = (1/t) Log 2 n (in b/s)

19. Examples: Telephone channel, B = 3000 Hz, S/N = 1000 DataRate <= 30 000 b/s Optical fiber B = 25 THz, S/N >= 1 DataRate <= 25 Tb/s Shannon’s Theorem DataRate <= B.Log2(1+S/N) B : Channel Bandwidth (in Hertz) S/N : Signal to Noise ratio

20. Data transmission fundamentals Parallel vs. serial transmission Synchronous vs. asynchronous communications Analog vs. digital communications Shannon’s theorem Eye diagrams Transmission error correction Redundant encoding Sliding window error correction Encoding and modulation Contents

21. Eye Diagrams 1 0 1 t Clock The incoming waveforms are displayed on an oscilloscope, synchronized by the recovered clock

22. Multi-bit eye diagrams Modern communication channels use phase and amplitude shifts, best displayed in polar eye diagrams Good signal/noise ratio Poor signal/noise ratio

23. Communications in degraded mode Same baud rate Half bit/s rate

24. Data transmission fundamentals Parallel vs. serial transmission Synchronous vs. asynchronous communications Analog vs. digital communications Shannon’s theorem Eye diagrams Transmission error correction Redundant encoding Sliding window error correction Encoding and modulation Contents

25. Error detection and correction k + r <= LMax k bits r bits, f(inf.mess.) 2 k 2 k+r Length of messages : Informative message: Redundancy: # Messages send: # Messages received: Hamming Distance (X-Y): i=1 |Xi-Yi| k+r

26. Bank account number structure Bank identification : 3 digits Account number : 7 digits Error detection : 2 digits The ten first digits modulo 97 are appended for error detection purposes. This algorithm allows detection of all single digit errors Example : 140-0571659-08. 1400571659 MOD 97 = 08 140-0671659-08. 1400671659 MOD 97 = 01 Error Detection ExampleBelgian Bank Account Numbers

27. 01 11 Hd = 2 00 11 00 10 Error detecting codes k = 1; r = 1; red.bit = inf.bit. Single bit errors are detected if hamming distance between legitimate messages > 1. No guessing is possible as erroneous messages are at equal distances from several correct ones.

28. 011 111 Hd = 3 000 111 010 110 001 101 000 100 Error correcting codes k = 1; r = 2; red.bits = inf.bit. Hamming distance between legitimate messages > 2. This implies that each erroneous message is closer to one correct message than to any other.

29. redundancy Overhead information 1 <= 4 <= 11 <= 26 <= 57 <= 120 <= 247 2 3 4 5 6 7 8 200 % 75 % 36 % 19 % 11 % 6 % 3 % Error correcting codes Required Overhead for single bit error correction k+r < 2r

30. Error correction with a 4+3 bit code 2 0000000 1111100 1 1111111 0001011 3 4 1110100 0010110 4 3 3 1101001 0011101 4 6 1100010 0100111 1011000 0101100 4 1010011 0110001 7 1001110 0111010 1000101 The three redundant bits are a function of the four data bits

31. Error detecting codes Correction by retransmission of erroneous blocks If few errors, very low overhead Most common approach to error correction in data communications Error correcting codes Very high overhead with short data blocks Longer data blocks can have multiple errors Used when retransmission impossible or impractical Also used when error rate rather high. Error correcting codes for long blocks, with multiple errors exist and are used (trellis encoding) Error Correction

32. Data transmission fundamentals Parallel vs. serial transmission Synchronous vs. asynchronous communications Analog vs. digital communications Shannon’s theorem Eye diagrams Transmission error correction Redundant encoding Sliding window error correction Encoding and modulation Contents

33. Error Correction byRetransmission Time-out 1 2 3 4 4 A Data Ack B time

34. Error Correction byRetransmission Inefficient unless round-trip delay << transmission time of a datablock 2 3 4 1 A Data B Ack time

35. Error Correctionwith sliding window Data blocks in sliding window can be transmitted without waiting for an acknowledgment. Receiving acknowledgments pushes window forward. 1 2 3 4 5 6 7 8 A Data B Ack 1 2 3 4 5 6 7 8 time

36. Error Correctionwith sliding window Data blocks in sliding window can be transmitted without waiting for an acknowledgment. Receiving acknowledgments pushes window forward. 1 2 3 4 5 6 7 8 A Data B Ack time

37. Error Correctionwith sliding window Data blocks in sliding window can be transmitted without waiting for an acknowledgment. Receiving acknowledgments pushes window forward. 1 2 3 4 5 6 7 8 A Data B Ack 1 time

38. Error Correctionwith sliding window Data blocks in sliding window can be transmitted without waiting for an acknowledgment. Receiving acknowledgments pushes window forward. 1 2 3 4 5 6 7 8 A Data B Ack 1 2 time

39. Error Correctionwith sliding window Data blocks in sliding window can be transmitted without waiting for an acknowledgment. Receiving acknowledgments pushes window forward. 1 2 3 4 5 6 7 8 A Data B Ack 1 2 time

40. Error Correctionwith sliding window Data blocks in sliding window can be transmitted without waiting for an acknowledgment. Receiving acknowledgments pushes window forward. Time-out 6 7 8 1 2 3 4 5 A Data B Ack 1 2 4 time

41. Error Correctionwith sliding window Data blocks in sliding window can be transmitted without waiting for an acknowledgment. Receiving acknowledgments pushes window forward. Time-out 6 7 8 1 2 3 4 5 A Data B Ack 1 2 4 5 time

42. Error Correctionwith sliding window Data blocks in sliding window can be transmitted without waiting for an acknowledgment. Receiving acknowledgments pushes window forward. 1 2 3 4 5 6 3 4 5 A Data Go Back n window management B Ack 1 2 4 5 time

43. Error Correctionwith sliding window Data blocks in sliding window can be transmitted without waiting for an acknowledgment. Receiving acknowledgments pushes window forward. 1 2 3 4 5 6 3 4 5 A Data B Ack 3 4 1 2 4 5 time

44. Error Correctionwith sliding window Data blocks in sliding window can be transmitted without waiting for an acknowledgment. Receiving acknowledgments pushes window forward. 1 2 3 4 5 8 3 6 7 A Data Buffering required in receiver B Ack 1 2 4 5 time

45. Data transmission fundamentals Parallel vs. serial transmission Synchronous vs. asynchronous communications Analog vs. digital communications Shannon’s theorem Eye diagrams Transmission error correction Redundant encoding Sliding window error correction Encoding and modulation Contents

46.   1  R (  )  lim v ( t ). v ( t   ). dt        S (  )  R (  ). cos(  ). d    Characterization of random signals* Autocorrelation function Fourier Spectrum * Students with inadequate mathematical background may skip this slide

47. v 0 1 0 1 0 0 1 1 1 a Power 1 t 0 0.5 Freq 0 0 1 2 3 Straight Binary Code • Frequency spectrum : • Maximum at f = 0 • important DC component due to voltage asymetry • No energy at clock frequency • Amplitude of maxima decreases as 1/f

48. Power 1 0.5 Freq 0 0 1 2 3 4 Manchester Code v 0 1 0 1 0 0 1 1 1 t • Frequency spectrum : • Nothing at f = 0 • High energy at clock frequency • Amplitude of maxima decreases as 1/f

49. Asymptotic Behavior of Spectra Both studied codes have energy spectra decreasing as 1/f2 , meaning that the voltage or current spectra decrease as 1/f. This is a consequence of the instantaneous state transitions 1 å w sin n t n 1 , 3 , 5 ,

50. 1 å w cos n t 2 n 1 , 3 , 5 , Asymptotic Behavior of Spectra The smoother the waveforms are, the lesser energy will be found in the spectrum at higher frequencies In actual transmission systems, rounded waveforms, such as parts of sine waves will be used.