UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

MmWave V2V Localization in MU-MIMO Hybrid Beamforming

Lota, J; Ju, S; Kanhere, O; Rappaport, TS; Demosthenous, A; (2022) MmWave V2V Localization in MU-MIMO Hybrid Beamforming. IEEE Open Journal of Vehicular Technology 10.1109/OJVT.2022.3170522. (In press). Green open access

[thumbnail of MmWave_V2V_Localization_in_MU-MIMO_Hybrid_Beamforming.pdf]
MmWave_V2V_Localization_in_MU-MIMO_Hybrid_Beamforming.pdf - Accepted Version

Download (1MB) | Preview


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 a number of vehicles reduces the Cramr-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.

Type: Article
Title: MmWave V2V Localization in MU-MIMO Hybrid Beamforming
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/OJVT.2022.3170522
Publisher version: https://doi.org/10.1109/OJVT.2022.3170522
Language: English
Additional information: © 2022 IEEE. This work is licensed under a Creative Commons Attribution 4.0 License. For more information (https://creativecommons.org/licenses/by/4.0/).
Keywords: Hybrid beamforming, localization, mmWave, MU-MIMO, V2V
UCL classification: UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng
UCL > Provost and Vice Provost Offices > UCL BEAMS
URI: https://discovery.ucl.ac.uk/id/eprint/10149233
Downloads since deposit
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item