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AirTrack: Locating Non-WiFi Interferers using Commodity WiFi Hardware Ashish Patro, Shravan Rayanchu, Suman Banerjee Wisconsin Wireless and NetworkinG Systems (WiNGS) Laboratory, UW-Madison. RESULTS. AirTrack ARCHITECTURE. PROBLEM STATEMENT. Synchronization results. Non WiFi devices

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AirTrack: Locating Non-WiFi Interferers using Commodity WiFi Hardware

  • Ashish Patro, Shravan Rayanchu, Suman Banerjee
  • Wisconsin Wireless and NetworkinG Systems (WiNGS) Laboratory, UW-Madison

RESULTS

AirTrack ARCHITECTURE

PROBLEM STATEMENT

Synchronization results

Non WiFi devices

affect WiFi performance

Access Point (with Airshark sniffer)

  • For time interval <= 500 µs, Synchronization Error < 10 µs

AirTrack controller

Clustering results

How do we locate the multiple non-WiFi devices (even of the same type) ?

How to synchronize access points?

STAGE 1: Synchronization

  • QUESTIONS?
  • How do we locate these non-WiFi devices?
  • How do we this in real time on a WiFi card, without additional hardware?

Reference AP

  • Need to synchronize tagged pulses from multiple nodes
  • Find common packets received by multiple sniffers
  • BFS from the reference access point to get per-node skew

+6 µs

+5 µs

  • CHALLENGES?
  • Identify non-WiFi device transmissions
  • Identify unique non-WiFi device instances (e.g., 2 FHSS devices)
  • Localize devices with unknown transmit power

-8 µs

Microwave Oven

FHSS Phones

FHSS Phones

-5 µs

Time domain clustering

RSS domain clustering

How to merge common pulses from the same non-WiFi device?

  • Each cluster is a unique active device
  • AirTrack can differentiate between multiple devices

STAGE 2 : Merge pulses

SOLUTION FRAMEWORK

  • Waterfall Merging Approach: Merge common pulses seen by multiple access points
  • - Matching Start/End time
  • - Matching center frequency
  • - Matching bandwidth

FHSS

Pulses

Localization results

Time

Sniffers that detect presence of non-WiFi devices

Airshark

Pairwise AP: S0,S2

0 - 56

0 - 56

0 - 56

Frequency (FFT bins)

Synchronization

Capture FFT samples

Identify ``Pulses”

Extract ``Features’’

Binary Decision

Tree classifier

Airshark

Airshark

Airshark

Duration

S3

S2

S1

Power

STAGE 3 : Cluster pulses

Bandwidth

How many devices are active simultaneously?

Pairwise AP: S5,S7

Frequency

“Tagged

Pulses”

Timing

Properties

  • Cluster pulses to identify unique devices
  • - Temporal properties
  • - RSSI properties
  • Each cluster is a unique device

Localization error CDF for FHSS phone

Locate non-WiFi devices using multiple Airshark sniffers

AirTrack

Pairwise AP: S3,S5

STAGE 4 : Localization

How to find device’s physical location?

“Tagged

Pulses”

  • AP locations are known
  • Device transmit power is unknown
  • Create RF propagation model
  • For each cluster, find location
  • - RSS per sniffer

Synchronize access points

Merge + Cluster pulses

Localize each device

(Pulse Cluster)

S1: -40db

S2: -70db

S3: -75db

S1

S2

S1: -70db

S2: -60db

S3: -45db

Access Point (with Airshark sniffer)

  • Localization error < 6 metres for 80% of the locations

S3