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Wireless Sensor System Design

Wireless Sensor System Design. A Joint Course of the University of South Florida and Tennessee Technological University Spring 2002 Lecture 3 - Signal Processing Techniques (as applicable to the project). Tennessee Tech UNIVERSITY. Weekly Lecture Topics. Course Introduction

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Wireless Sensor System Design

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  1. Wireless Sensor System Design A Joint Course of the University of South Florida and Tennessee Technological University Spring 2002 Lecture 3 - Signal Processing Techniques (as applicable to the project) Tennessee Tech UNIVERSITY

  2. Weekly Lecture Topics • Course Introduction • Analog and Digital Modulation Methods (1/11) • Fundamentals of Antennas and Propagation (1/18) • Signal Processing Techniques (1/25) • Microwave Systems: Communications Hardware, Noise, Linearity (2/1) • System Test, Evaluation and Documentation / Effective Presentation Styles (2/8) • Preliminary Design Review (student presentations*) (2/15) • Microwave Sensor Technology (2/22) @ TTU • TBD (3/1) • TBD (3/8) • Critical Design Review (student presentations*) (3/22) • Microelectromechanical Systems (MEMS) Sensors (4/5) • Modern Wireless Communication Systems (4/12) @ USF • Review / Course Wrap-up(4/19) * On-site internal reviews/preparation will precede inter-university presentations.

  3. The BIG Picture Sensor n http://www.ece.tntech.edu/472s02/dsp/ Data for 01APR01 Time Sensor °C Intensity Humidity 1532 26 24 70% 50% 1533 14 25 65% 55% 1544 29 30 0% 60% … … … … … … … … … … … … … … … Historical Data: By time By sensor Bylocation Sensor 14: °C Sensor: Temperature, Light Intensity, Humidity & Location Date/time

  4. How are we going to get there? ENVIRONMENT Signal Processing / WEB Baseband Antenna RF RX DC Power GPS Antenna Baseband RF TX Temp Intensity Humidity USER DC Power

  5. USF Team Project Areas : TX SENSOR / TRANSMITTER Red Team Green Team Blue Team • Baseband input • 500 MHz VCO • 500 MHz Filter • Lenny • Brad • TTU TX • 1.9 GHz VCO • 2.45 GHz mixer • 2.45 GHz filter • Anand • Hugo • 2.45 GHz dual amplifier • 2.45 GHz antenna • Glenn • Rob

  6. USF Team Project Areas : RX RECEIVER Red Team Green Team Blue Team • 500 MHz VCO • 500 MHz Filter • 500 MHz amplifiers • Baseband output • Lenny • Brad • TTU RX • 1.9 GHz VCO • 2.45 GHz mixer • 2.45 GHz filter • Anand • Hugo • 2.45 GHz receive network (with amplifiers) • 2.45 GHz antenna • Glenn • Rob TTU and USF need to talk ASAP!

  7. How are we going to get there? ENVIRONMENT Signal Processing / WEB Baseband Antenna RF RX DC Power GPS Antenna Baseband RF TX Temp Intensity Humidity USER DC Power

  8. Outline for Today’s Tutorial • Some digital signal processing scenarios. • What are we receiving? • How can this data be processed? • Wrap up / What’s next!

  9. Scenarios for Consideration How can the data be manipulated to: • Improve transmission characteristics? • Reduce the noise effects? • Determine sharp changes in data? • Extract frequency content vs. time (i.e., our application)?

  10. Scenario 1: Improving Transmission Characteristics • Scenario: Pulses are to be used to send data across a channel • Problem: Square waves produce harmonics which increase overall bandwidth • Solution: Filter output (simple pulse shaping)

  11. Square Wave Characteristics ~20 V Recall Fourier Series

  12. “Filtered” Square Wave Characteristics ~ 25 V

  13. Filtering Employed • Averaging over four values • Is this intuitive? • In the limit, averaging over all values results in the DC component • Averaging = Low Pass Filtering 3rd order filter

  14. What is Digital Signal Processing? • This simple example illustrates the manipulation of discrete-time, discrete-amplitude data • DSP: Algorithms designed to extract specific information from or improve the characteristics of such signals.

  15. Scenario 2: Reducing Noise Effects SNR ~ 10 dB Additive White Gaussian Noise

  16. LPF Using 3rd-Order Digital Filter SNR ~ 17 dB* * as compared to filtered noise-free data

  17. Scenario 3: Determining Sharp Changes in Data • DSP manipulation: • Is this intuitive? • Large changes imply large slopes • Recall the difference equation from Calculus • Results in edge-detection • Taking difference = High Pass Filtering

  18. Recall: Square Wave Characteristics ~20 V

  19. “Edge-detected” Square Wave Characteristics Impulse train again Fourier series

  20. Digital Image Processing • Apply similar ideas but into two-dimensions • LPF V-edge detect H-edge detect Average over 9 pixels Note: diagonal edges can also be detected with appropriate weightings

  21. LPF Image Original Image

  22. Noisy Image Filtered Noisy Image

  23. Vertical Edge Detection Horizontal Edge Detection

  24. Scenarios 4 & 5: AW3 Baseband options • “Analog” • Decimal data (i.e., 0-9) is encoded with baseband tones (DTMF) • Baseband signal drives VCO • FM modulation • PLL receiver • Digital • PCM encode information (i.e., analog to 0’s and 1’s) • Use binary signal and VCO to FSK modulate IF • PLL and/or bit detector at receiver

  25. FM/FSK

  26. What are we receiving at 2.4 GHz? Analog Spectrum Digital Spectrum “0” “0” “1” “9”

  27. Analog FM Receiver/PLL 2.4 GHz 550 MHz filter X filter X filter < 20 kHz VCO synthesizer PLL: phase locked loop

  28. Scenario 4: Extracting Frequency Content vs. Time • In the DTMF system, information is sent by using two tones • What tones are present at any point in time? • Note 7 distinct frequencies • 697, 770, 852, 941, 1209, 1336, 1447

  29. Signal Construction • In general: • Dual tone: • “7_a” • “7_b” • Analog System: n>2: harmonics, since tones will not be pure

  30. Time and Frequency Representation tone 1 vs sec tone 1 vs Hz tone 2 vs sec tone 2 vs Hz

  31. Time and Frequency Representation two tones vs sec two tones vs Hz Problem: Only time or frequency known. Not both! 4 tones, what occurred when?

  32. Short-Time Fourier Transform FFT FFT FFT FFT • Break time window into small chunks (of Nsamples each) • FFT each chunk • Stack FFTs • Represent as a time-frequency image • sample rate: FFT FFT FFT FFT Time resolution: freq Frequency resolution: time

  33. Time-Frequency Map Brief bursts Always present frequency time

  34. Result on FM Data (NestWatch 2001)

  35. Digital FSK Receiver 529 MHz or 571 MHz 41 MHz (?) 2.4 GHz “1” filter detector filter X filter X compare “0” filter detector 1 MHz (?) VCO synthesizer 530 MHz (?) 0 or 1

  36. Scenario 5: FSK Data Detection* 1 0 1 Note: this is NOT exactly how our implementation will be done

  37. Method 1: STFT on OOK and FSK data Bit sequence: 1 0 1 1 0 1 0 1 1 0 frequency time

  38. Method 2: Correlation Receiver: Time-Domain Processing • Correlate incoming signal with what you are looking for: • “1” – higher frequency signal • “0” – lower frequency signal • Take inner product of input with desired signal.

  39. Output of Correlation Receiver threshold 1 0 1 1 0 1 Looking for “1s” Looking for “0s”

  40. Conclusion • Signal processing is already widely used in telecommunication systems • Algorithms improve system performance • e.g., error correction code, compression • As processing power increases, DSP becomes even more cost effective to implement • What’s next? Software Radios • Chips running code perform typical radio functions • Reconfigurable

  41. Wrap Up Need quick answer to the following: USF/TTU: • What are the RF and DC power requirements? TTU: • What signal voltages are expected at the baseband?

  42. Two Month Course Schedule February • Week 4 (28-1) • First progress report • Parts list due • Week 5 (4-8) • Review peer reports • Week 6 (11-15) • Preliminary Design Review • Week 7 (18-22) • Weller at TTU January • Week 1 (7-11) • Week 2 (14-18) • Choose project • Literature search • Week 3 (21-25) • Literature search • Submit project description (1 page; references from literature search) and tentative schedule (design; fabrication; test; report) 1. All inputs are due on Friday of the specified week - no exceptions 2. Reviews of peer reports must be completed before the lecture on Friday

  43. Coming Soon! • Tutorial from USF: Microwave Systems: Communications Hardware, Noise, Linearity (2/1) • Tutorial from TTU: System Test, Evaluation and Documentation / Effective Presentation Styles (2/8) • Initial parts order next week! (Wednesday at TTU) • Individual progress report next Friday (2/1) • Hand in hardcopy to instructor

  44. Format for Progress Reports • Brief project description and purpose (1-3 sentences) • Objectives for the current reporting period (2-3 sentences) • Progress for the current reporting period (2-3 paragraphs; use figures and graphs where needed) • Plans for the upcoming project period (2-3 sentences) • Revised Project Schedule Keep in mind that the peer(s) who review your report may not be intimately familiar with your project, so you need to clearly explain the objectives and outcomes.

  45. Peer Review Process You are required to turn in reviews for two peer reports that will be assigned to you. You should include brief comments/suggestions and an overall grade of G (good), P (passing), and U (unsatisfactory). Hand-in the reports with your name attached, but NOT written on the report (the reviews are anonymous). Two “U” grades from peers will result in a loss of credit for the student, unless overridden by the instructor(s). Grading criteria: • Clarity of report • Level of progress made during reporting period • Clear goals for upcoming project period

  46. Final Comments • Need to think about subsystem interfaces • Electrical (DC) • Signal (frequency, voltages, etc.) • Dimensions • Packaging • Need TTU/USF contact to be made. • Keep up the good work!

  47. Anything else?

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