1. A Wireless Spectrum Analyzer in Your Pocket
Tan Zhang, Ashish Patro, Ning Leng, Suman Banerjee
University of Wisconsin-Madison
Tan Zhang / Snoopy / HotMobile 2015

2. What is Spectrum Sensing?
Tan Zhang / Snoopy / HotMobile 2015

3. Application of Spectrum Sensing
Whitespace spectrum
Spectrum Vacancy
Network Diagnosis
Device Management
Tan Zhang / Snoopy / HotMobile 2015

4. Problem of A Cathedral Approach
Spectrum Analyzer
Cumbersome
(up to 30kg)
Expensive
(10k – 50k)
Sophisticated
(RF/IF gain, filter bw)
Tan Zhang / Snoopy / HotMobile 2015

5. Opportunity of Mobile Phone Sensing
Can we use smartphones and tablets for spectrum sensing?
Compact
Cheap
Easy to use
Tan Zhang / Snoopy / HotMobile 2015

6. Opportunity of Mobile Phone Sensing
Enable spectrum analytics at massive scale
Spatial Distribution of Android and IPhone devices
New York
Los Angeles
Tan Zhang / Snoopy / HotMobile 2015

7. Opportunity of Mobile Phone Sensing
Approach 1 – leverage subcarrier energy sample from built-in WiFi chipsets, e.g., Atheros 92xx
WiFi
Chipset
Subcarrier
Power
Airshark
Frequency
Tan Zhang / Snoopy / HotMobile 2015

8. Opportunity of Mobile Phone Sensing
Approach 2 – attach customized analyzer dongle
WiSpy (WiFi band)
RTL-SDR (TV band)
Tan Zhang / Snoopy / HotMobile 2015

9. Limitation of Existing Mobile Phone Sensing
Narrow frequency range
WiFi or TV band
Low spectrum resolution
64 subcarriers over a 20MHz band
1000 times worse than spectrum analyzer
Tan Zhang / Snoopy / HotMobile 2015

10. Spectrum Knowledge out of Your Pocket
Goal
Develop hardware attachment and signal processing technique to enhance spectrum sensing on mobile devices
Spectrum Knowledge out of Your Pocket
Snoopy
Tan Zhang / Snoopy / HotMobile 2015

11. Outline Smartphone based sensing platform – Snoopy
Frequency translator
Spectrum sensing on WiFi cards
Statistical feature based signal detection
Implementation
Evaluation
Future work
Tan Zhang / Snoopy / HotMobile 2015

12. Snoopy Overview Antenna Frequency Translator WiFi band FFTs (2.4GHz)
Power
(2.4GHz)
Power
Power
FFTs
Signal Type, Power
Antenna
Frequency
Translator
Tan Zhang / Snoopy / HotMobile 2015

13. Frequency Translator Input Output Frequency Mixer Frequency
Tune to let
Input
Output
Frequency Mixer
Frequency
Synthesizer
Tan Zhang / Snoopy / HotMobile 2015

14. Spectrum Collection on WiFi Cards
Recent WiFi chipsets expose subcarrier energy samples
e.g., Intel 5300, Atheros 92xx and 93xx
Metric
Performance
Capture bandwidth
20/40MHz
Capture delay
120us
Spectrum resolution
312KHz
Challenging to determine vacant spectrum
Tan Zhang / Snoopy / HotMobile 2015

15. Challenge of Determining Whitespaces from WiFi Spectrum Scan
-90dBm power
Spectrum Analyzer TV
FFT
Need to detect TV and wireless microphone
Microphone
Noise (whitespace)
Tone
Pilot
Noise fluctuation reduce peak detection accuracy
WiFi Scan
FFT
Pilot
Tone
Tan Zhang / Snoopy / HotMobile 2015

16. Statistical Spectrum Feature
Apply Fourier Transform on spectrum to collect entire shape features
Coefficients can help signal detection
FFT Index
Co-efficient
FFT over FFT
Tan Zhang / Snoopy / HotMobile 2015

17. Statistical Spectrum Feature
-90dBm power
WiFi Scan TV
Microphone
Noise (whitespace)
Use SVM classifier to learn the importance of individual coefficients
FFT over FFT
Dominant peak
Constant offset
Square envelop
Tan Zhang / Snoopy / HotMobile 2015

18. Implementation Frequency translation hardware Wide band digital radio
RF chain 1
RF chain 1
RF chain 2
30MHz – 7.5GHz frequency range
1ms frequency switching delay
Tan Zhang / Snoopy / HotMobile 2015

19. Implementation Software
Patch Ath9k driver to enable spectrum scan in the 2.4GHz
WiSense – Android based application for WiFi band sensing
Tan Zhang / Snoopy / HotMobile 2015

20. Experiment Experiment setup Linux Router
Used a Linux based router with an Atheros 9280 card for spectrum sensing
Connect Snoopy and a ThinkRF WSA4000 analyzer to the same antenna
Linux
Router
Tan Zhang / Snoopy / HotMobile 2015

21. Accuracy in Detecting Primary Signals
Collect spectrum data in 8 UHF channels
Use a RF attenuator to capture TV and microphone signals from -50dBm to -90dBm
1-5% gain of
statistical feature
15%
<10% worse than ThinkRF 7% 3%
Tan Zhang / Snoopy / HotMobile 2015

22. Accuracy of Measuring Channel Power
Measure in-band power of 6MHz TV channels
Calculate absolute power difference between Snoopy and ThinkRF analyzer in each channel
<4dB median error in lower UHF band
Higher error due to translator distortion
Tan Zhang / Snoopy / HotMobile 2015

23. Challenges and Future Work
Connect off-the-shelf mobile devices
WiFi dongle with SMA connector
WiFi repeater to relay translated signal
Reduce size and cost of translator
Translator for receiving only
0.1 – 4GHz frequency range and $48
Improve measurement accuracy
Collaborative sensing with longitudinal measurements
Leverage phase information from I, Q samples
TL-WN722N
EST-1W
ZX05 – U432H
Tan Zhang / Snoopy / HotMobile 2015

24. Conclusion
Designed a smartphone based spectrum sensing platform to enable citizen-contributed spectrum analytics.
Designed statistical spectrum features to improve signal detection accuracy from low-resolution spectrum.
Built driver hooks and an Android application to enable spectrum sensing on smartphones and tablets.
WiSense:
Tan Zhang / Snoopy / HotMobile 2015

25. WiSense Demo
Tan Zhang / Snoopy / HotMobile 2015

26. Thanks for your attention! tzhang@cs.wisc.edu
Tan Zhang / Snoopy / HotMobile 2015