Error-Based Interference Detection in WiFi Networks

Fabrizio Giuliano, Daniele Croce, Ilenia Tinnirello, Domenico Garlisi, Daniele Croce, Domenico Garlisi, Fabrizio Giuliano

Research output: Contribution to conferenceOtherpeer-review

1 Citation (Scopus)

Abstract

In this paper we show that inter-technology interference can be recognized by commodity WiFi devices by monitoring the statistics of receiver errors. Indeed, while for WiFi standard frames the error probability varies during the frame reception in different frame fields (PHY, MAC headers, payloads) protected with heterogeneous coding, errors may appear randomly at any point during the time the demodulator is trying to receive an exogenous interfering signal. We thus detect and identify cross-technology interference on off-the-shelf WiFi cards by monitoring the sequence of receiver errors (bad PLCP, bad PCS, invalid headers, etc.) and develop an Artificial Neural Network (ANN) to recognize the source of interference. The result is quite impressive, reaching an average accuracy of almost 99% in recognizing ZigBee, Microwave and LTE (in unlicensed spectrum) interference.
Original languageEnglish
Pages1-6
Number of pages6
Publication statusPublished - 2018

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Hardware and Architecture
  • Safety, Risk, Reliability and Quality

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