MmWave V2V Localization in MU-MIMO Hybrid Beamforming

Jaswinder Lota, Shihao Ju, Ojas Kanhere, Theodore S. Rappaport, Andreas Demosthenous

Research output: Contribution to journalArticlepeer-review


Recent trends for vehicular localization in millimetre-wave (mmWave) channels include employing a combination of parameters such as angle of arrival (AOA), angle of departure (AOD), and time of arrival (TOA) of the transmitted/received signals. These parameters are challenging to estimate, which along with the scattering and random nature of mmWave channels, and vehicle mobility lead to errors in localization. To circumvent these challenges, this paper proposes mmWave vehicular localization employing difference of arrival for time and frequency, with multiuser (MU) multiple-input-multiple-output (MIMO) hybrid beamforming; rather than relying on AOD/AOA/TOA estimates. The vehicular localization can exploit the number of vehicles present, as an increase in the number of vehicles reduces the Cramér-Rao bound (CRB) of error estimation. At 10 dB signal-to-noise ratio (SNR) both spatial multiplexing and beamforming result in comparable localization errors. At lower SNR values, spatial multiplexing leads to larger errors compared to beamforming due to formation of spurious peaks in the cross ambiguity function. Accuracy of the estimated parameters is improved by employing an extended Kalman filter leading to a root mean square (RMS) localization error of approximately 6.3 meters.

Original languageEnglish (US)
Pages (from-to)210-220
Number of pages11
JournalIEEE Open Journal of Vehicular Technology
StatePublished - 2022


  • Hybrid beamforming
  • V2V
  • localization
  • mmWave

ASJC Scopus subject areas

  • Automotive Engineering


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