Tan Zhang Ashish Patro Ning Leng Suman Banerjee University of WisconsinMadison 1 Tan Zhang Snoopy HotMobile 2015 What is Spectrum Sensing 2 Tan Zhang Snoopy HotMobile 2015 ID: 405960
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Slide1
A Wireless Spectrum Analyzer in Your Pocket
Tan Zhang, Ashish Patro, Ning Leng, Suman BanerjeeUniversity of Wisconsin-Madison
1
Tan Zhang / Snoopy / HotMobile 2015Slide2
What is Spectrum Sensing?
2Tan Zhang / Snoopy / HotMobile 2015Slide3
Application of Spectrum Sensing
3Tan Zhang / Snoopy / HotMobile 2015
Spectrum Vacancy
Network Diagnosis
Device Management
Whitespace spectrumSlide4
Problem of A Cathedral Approach
4Tan Zhang / Snoopy / HotMobile 2015Spectrum Analyzer
Cumbersome(up to 30kg)
Expensive
(10k – 50k)
Sophisticated
(RF/IF gain, filter
bw
)Slide5
Opportunity of Mobile Phone Sensing
5Tan Zhang / Snoopy / HotMobile 2015Can we use smartphones and tablets for spectrum sensing?Compact
Cheap
Easy to useSlide6
Opportunity of Mobile Phone Sensing
6Tan Zhang / Snoopy / HotMobile 2015New York
Spatial Distribution of Android and IPhone devices
Los Angeles
Enable spectrum
a
nalytics at massive scaleSlide7
Approach 1 – leverage subcarrier energy sample from built-in WiFi chipsets, e.g., Atheros 92xx
Opportunity of Mobile Phone Sensing
WiFi
Chipset
Power
Frequency
Tan Zhang / Snoopy / HotMobile 2015
7
Airshark
SubcarrierSlide8
Approach 2 – attach customized analyzer dongle
Opportunity of Mobile Phone Sensing
Tan Zhang / Snoopy / HotMobile 2015
8
WiSpy (WiFi band)
RTL-SDR (TV band) Slide9
Limitation of Existing Mobile Phone Sensing
9Tan Zhang / Snoopy / HotMobile 2015Narrow frequency rangeWiFi or TV bandLow spectrum resolution64 subcarriers over a 20MHz band1000 times worse than spectrum analyzerSlide10
Goal
10Tan Zhang / Snoopy / HotMobile 2015Develop hardware attachment and signal processing technique to enhance spectrum sensing on mobile devicesSpectrum K
nowledge out
of Your P
ocket
SnoopySlide11
Outline
11Tan Zhang / Snoopy / HotMobile 2015Smartphone based sensing platform – SnoopyFrequency translator Spectrum sensing on WiFi cardsStatistical feature based signal detectionImplementationEvaluationFuture work Slide12
(2.4GHz)
PowerSnoopy Overview12
Tan Zhang / Snoopy / HotMobile 2015
Signal Type, Pow
er
Antenna
Frequency
Translator
Frequency
Power
Power
FFTs
WiFi bandSlide13
Frequency Translator
InputOutput
FrequencySynthesizer
Frequency Mixer
Tune to let
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Tan Zhang / Snoopy / HotMobile 2015Slide14
Spectrum Collection on WiFi Cards
14Tan Zhang / Snoopy / HotMobile 2015Recent 802.11 WiFi chipsets expose subcarrier energy samples e.g., Intel 5300, Atheros 92xx and 93xxMetricPerformanceCapture
bandwidth20/40MHz
Capture delay
120us
Spectrum resolution
312KHz
Challenging to determine vacant spectrumSlide15
Challenge of Determining Whitespaces from WiFi Spectrum Scan
15Tan Zhang / Snoopy / HotMobile 2015Spectrum Analyzer
WiFi Scan
TV
Microphone
Noise (whitespace)
FFT
Noise fluctuation reduce peak detection accuracy
Tone
Pilot
Tone
Pilot
-90dBm power
FFT
Need to detect TV and wireless microphoneSlide16
Statistical Spectrum Feature
16Tan Zhang / Snoopy / HotMobile 2015
FFT Index
Co-efficient
Apply Fourier Transform on spectrum to collect entire shape features
FFT over FFT
C
oefficients can help signal detectionSlide17
Statistical Spectrum Feature
17Tan Zhang / Snoopy / HotMobile 2015
TV
Microphone
Noise (whitespace)
WiFi Scan
FFT over FFT
-90dBm power
Square envelop
Dominant peak
Constant offset
Use SVM classifier to learn the importance of individual coefficients Slide18
Implementation
18Tan Zhang / Snoopy / HotMobile 2015RF chain 1Frequency translation hardwareWide band digital radio
RF chain 1
RF chain 2
30MHz – 7.5GHz frequency range
1ms frequency switching delaySlide19
Implementation
19Tan Zhang / Snoopy / HotMobile 2015SoftwarePatch Ath9k driver to enable spectrum scan in the 2.4GHzWiSense – Android based application for WiFi band sensingSlide20
Experiment
Experiment setupUsed a Linux based router with an Atheros 9280 card for spectrum sensingConnect Snoopy and a ThinkRF WSA4000 analyzer to the same antenna20Tan Zhang / Snoopy / HotMobile 2015 LinuxRouterSlide21
Accuracy in Detecting Primary Signals
21Tan Zhang / Snoopy / HotMobile 2015Collect spectrum data in 8 UHF channels Use a RF attenuator to capture TV and microphone signals from -50dBm to -90dBm3%
15%
<10% worse than
ThinkRF
1-5% gain of
statistical feature
7
%Slide22
Accuracy of Measuring Channel Power
22Tan Zhang / Snoopy / HotMobile 2015Measure in-band power of 6MHz TV channelsCalculate absolute power difference between Snoopy and ThinkRF analyzer in each channel
<4dB median error in lower UHF band
Higher error due to translator distortionSlide23
Connect off-the-shelf mobile devicesWiFi dongle with SMA connector
WiFi repeater to relay translated signalReduce size and cost of translatorTranslator for receiving only0.1 – 4GHz frequency range and $48Improve measurement accuracyCollaborative sensing with longitudinal measurementsLeverage phase information from I, Q samplesChallenges and Future Work23
Tan Zhang / Snoopy / HotMobile 2015
TL-WN722N
EST-1W
ZX05 – U432HSlide24
Conclusion
24Tan Zhang / Snoopy / HotMobile 2015Designed 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:
http://research.cs.wisc.edu/wings/projects/wisense/Slide25
WiSense Demo
25Tan Zhang / Snoopy / HotMobile 2015Slide26
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Tan Zhang / Snoopy / HotMobile 2015 Thanks for your attention! tzhang@cs.wisc.edu