6533b7cefe1ef96bd1257c25
RESEARCH PRODUCT
Learning from Errors: Detecting ZigBee Interference in WiFi Networks
Domenico GarlisiDaniele CroceIlenia TinnirelloFabrizio Giulianosubject
business.industryComputer scienceSettore ING-INF/03 - TelecomunicazioniComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKSReal-time computingwlan 802.11 802.15.4 frame error detection wireless coexistenceInterval (mathematics)Interference (wave propagation)SynchronizationLearning from errorsTransmission (telecommunications)HeaderbusinessHidden Markov modelComputer networkNeuRFondescription
In this work we show how to detect ZigBee interference on commodity WiFi cards by monitoring the reception errors, such as synchronization errors, invalid header formats, too long frames, etc., caused by ZigBee transmissions. Indeed, in presence of non-WiFi modulated signals, the occurrence of these types of errors follows statistics that can be easily recognized. Moreover, the duration of the error bursts depends on the transmission interval of the interference source, while the error spacing depends on the receiver implementation. On the basis of these considerations, we propose the adoption of hidden Markov chains for characterizing the behavior of WiFi receivers in presence of controlled interference sources (training phase) and then run-time recognizing the most likely cause of error patterns. Experimental results prove the effectiveness of our approach for detecting ZigBee interference.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2014-06-01 |