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Communication Theory as Applied to Wireless Sensor Networks

Communication Theory as Applied to Wireless Sensor Networks. muse. Objectives. Understand the constraints of WSN and how communication theory choices are influenced by them Understand the choice of digital over analog schemes

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Communication Theory as Applied to Wireless Sensor Networks

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  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 representationof 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 Approachesfor 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 Approachesfor 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

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