VANET-Assisted Interference Mitigation for Millimeter-Wave Automotive Radar Sensors

Mengyuan Zhang, Shibo He, Chaoqun Yang, Jiming Chen, Junshan Zhang

Research output: Contribution to journalArticlepeer-review

14 Scopus citations


As key sensors of the ADAS, mmWave radars have been widely used for fulfilling tasks including adaptive cruise control, lane-changing assistance and collision avoidance. However, the interference generated by mmWave radars mounted on close-by vehicles, if not managed well, could seriously degrade the radars' performance, giving rise to a safety hazard. In this work, we study interference mitigation for the off-the-shelf 77 GHz FMCW mmWave radars. We review several state-of-the-art ideas for suppressing co-channel interference, based on which we introduce a VANET-assisted radar interference mitigation scheme, which is shown to be effective in an environment with dense traffic. Specifically, a TDMA based MAC protocol is devised that enables the coordination among vehicles on efficient multiple access of radar spectrum. Numerical results corroborate the performance gain of the proposed approach compared to the existing random frequency hopping approaches.

Original languageEnglish (US)
Article number9023460
Pages (from-to)238-245
Number of pages8
JournalIEEE Network
Issue number2
StatePublished - Mar 1 2020
Externally publishedYes

ASJC Scopus subject areas

  • Software
  • Information Systems
  • Hardware and Architecture
  • Computer Networks and Communications


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