Misbehavior Detection in Wi-Fi/LTE Coexistence over Unlicensed Bands

Islam Samy, Xiao Han, Loukas Lazos, Ming Li, Yong Xiao, Marwan Krunz

Research output: Contribution to journalArticlepeer-review

Abstract

We address the problem of detecting misbehavior in the coexistence between LTE and Wi-Fi systems operating in the 5 GHz U-NII unlicensed bands. We define selfish misbehavior strategies for the LTE that can yield an unfair share of the spectrum resources. Such strategies are based on manipulating the operational parameters of the LTE-LAA standard. Prior methods for detecting misbehavior in homogeneous settings are not applicable in a spectrum sharing scenario because the devices of one system cannot decode the transmissions of another. We develop implicit sensing techniques that can accurately estimate the operational parameters of LTE transmissions under various topological scenarios and {\em without decoding.} These techniques apply correlation-based signal detection to infer the required information. Our techniques are validated through experiments on a USRP testbed. We further apply a statistical inference framework for determining deviations of the LTE behavior from the coexistence etiquette. By characterizing the detection and false alarm probabilities, we show that our framework yields high detection accuracy at a very low false alarm rate. Although our methods focus on detecting misbehavior of the LTE system, they can be generalized to detect Wi-Fi misbehavior and to other coexistence scenarios.

Original languageEnglish (US)
JournalIEEE Transactions on Mobile Computing
DOIs
StateAccepted/In press - 2022

Keywords

  • Decoding
  • Downlink
  • Interference
  • Long Term Evolution
  • Monitoring
  • Standards
  • Wireless fidelity

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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