1. Communication Theory as Applied to Wireless Sensor Networks muse

2. Objectives Understand the constraints of WSN and how communication theory choices are influenced by them Understand the choice of digital over analog schemes Understand the choice of digital phase modulation methods over frequency or amplitude schemes muse

3. Objectives (cont.) Understand the cost/benefits of implementing source and channel coding for sensor networks Understand fundamental MAC concepts Grasp the importance of node synchronization Synthesize through examples these concepts to understand impact on energy and bandwidth requirements muse

4. Outline Sensor network constraints Digital modulation Source coding and Channel coding MAC Synchronization Synthesis: Energy and bandwidth requirements

5. WSN Communication Constraints Energy! Communication constraints

6. Data Collection Costs Sensors Activation Conditioning A/D Communication constraints

7. Computation Costs Node life support Simple data processing Censoring and Aggregation Source/Channel coding Communication constraints

8. Communication Costs Communication constraints

9. Putting it all together Communication constraints

10. Outline Sensor network constraints Digital modulation Source coding and Channel coding MAC Synchronization Synthesis: Energy and bandwidth requirements

11. Modulation Review Motivation for Digital Modulation

12. The Carrier Modulation

13. Amplitude Modulation (AM) DSB-SC (double sideband – suppressed carrier) Modulation

14. Frequency representation for DSB-SC (the math) Modulation

15. Frequency representation for DSB-SC (the cartoon) Modulation

16. Demodulation – coherent receiver Modulation

17. DSB-LC (or AM as we know it) Modulation

18. Frequency representation of DSB-LC Modulation

19. Amplitude Modulation Modulation

20. Frequency Modulation (FM) Modulation

21. Frequency Modulation Modulation

22. Phase Modulation Modulation

23. SNR Performance Modulation Fig. Lathi

24. Digital Methods Digital Modulation

25. Quadrature Modulation Digital Modulation

26. BPSK Digital Modulation

27. QPSK Digital Modulation

28. Constellation Plots Digital Modulation

29. BER Performance vs. Modulation Method Digital Modulation Fig. Lathi

30. BER Performance vs. Number of Symbols Digital Modulation Fig. Lathi

31. Outline Sensor network constraints Digital modulation Source coding and Channel coding MAC Synchronization Synthesis: Energy and bandwidth requirements

32. Source Coding Motivation Lossless Lossy Source Coding

33. Lossless Compression Zip files Entropy coding (e.g., Huffman code) Source Coding

34. Lossless Compression Approaches for Sensor Networks Constraints Run length coding Sending only changes in data Source Coding

35. Lossy Compression Rate distortion theory (general principles) JPEG Source Coding

36. Example of Lossy Compression - JPEG

37. Another comparison

38. Lossy Compression Approaches for Sensor Networks Constraints Transformations / Mathematical Operations Predictive coding / Modeling Source Coding

39. Example Actions by Nodes Adaptive Sampling Censoring Source Coding

40. In-Network Processing Data Aggregation Source Coding

41. Outline Sensor network contraints Digital modulation Source coding and Channel coding MAC Synchronization Synthesis: Energy and bandwidth requirements

42. Channel Coding (FEC) Motivation Block codes Convolution codes Channel Coding

43. Channel Coding Approaches for Sensor Networks Coding constraints Block coding Channel Coding

44. Example: Systematic Block Code Channel Coding

45. Alternative: Error Detection Motivation CRC Channel Coding

46. Performance Benefits Costs Channel Coding Fig. Lathi

47. Outline Sensor network contraints Digital modulation Source coding and Channel coding MAC Synchronization Synthesis: Energy and bandwidth requirements

48. Sharing Spectrum MAC Fig. Frolik (2007)

49. MAC Motivation Contention-based Contention-free MAC

50. ALOHA (ultimate in contention) Method Advantages Disadvantages MAC

51. CSMA (contentious but polite) Method Advantages Disadvantages MAC

52. Throughput comparison MAC

53. Contention Free Approaches RTS/CTS Reservations MAC

54. MAC for Sensor Networks: 802.15.4 Beacon enabled mode for star networks MAC

55. Bandwidth details: 802.15.4 2.4 GHz band (2.40-2.48 GHz) Sixteen channels spaced at 5 MHz (CH 11 – 26) Data rate – 250 kbps Direct sequence spread spectrum (DSSS) 4 bits → symbol → 32 chip sequence Chip rate of 2 Mcps Modulation – O-QPSK Total bandwidth requirement: ~3 MHz MAC

56. DSSS Motivation Operation MAC

57. Outline Sensor network contraints Digital modulation Source coding and Channel coding MAC Synchronization Synthesis: Energy and bandwidth requirements

58. Synchronization Motivation Categories Synchronization

59. Node Scheduling Sleep Listening Transmitting Synchronization

60. Sleep Scheduling for Sensor Networks: S-MAC Synchronization

61. Synchronizing for Effective Communications Carrier Bit/Symbol Frame Synchronization

62. Outline Sensor network contraints Digital modulation Source coding and Channel coding MAC Synchronization Synthesis: Energy and bandwidth requirements

63. Putting the Pieces Together

64. Synthesis: Energy and Bandwidth M-ary Signaling Channel Coding Energy & Bandwidth

65. Sensor Network Example 1: Single vs. Multihop Multihop Single hop Energy & Bandwidth

66. Sensor Network Example 2: Polling vs. Pushing Polling Pushing Energy & Bandwidth

67. Conclusions A digital communications approach to WSN has advantages in robustness, energy, and bandwidth performance Source coding reduces overall system level energy requirements Simple channel coding schemes improve data reliability minimizing the need for retransmissions muse

68. Conclusions - 2 MAC and routing strategies should be chosen with an eye towards network architecture – cross-layer design Node synchronization must occur regularly due to clock drift between nodes Simple digital communication techniques enable low-energy, low-bandwidth WSN system requirements muse

69. What to know more? B. Lathi, Modern Analog and Digital Communication Systems, 3 rd ed., Oxford, 1998. B. Krishnamachari, Networking Wireless Sensors, Cambridge Press, 2005. J. Frolik, “Implementation Handheld, RF Test Equipment in the Classroom and the Field,” IEEE Trans. Education, Vol. 50, No. 3, August 2007.