@inproceedings{b6e6f96362ab4630a25189c04b703fb4,
title = "Beam-based Device Positioning in mmWave 5G Systems under Orientation Uncertainties",
abstract = "High-accuracy positioning based on angles from multiple base-stations (BSs) requires precise knowledge of the BSs{\textquoteright} orientation. Installation errors are bound to occur in practice, and any mismatch between the actual and assumed orientation of the BSs on a given coordinate system leads to systematic errors in the position estimates. In this paper, we consider a system in which BSs transmit reference-signals (RSs) by means of static beams. The directions of such transmissions are known up to an error that is common to all beams for each BS. Different BSs have independent orientation errors. Users determine the reference-signal-received-power (RSRP) of such directional transmissions by employing receive beams. This is termed beam-RSRP (BRSRP) measurements, and they are reported to the network by the users. We propose an algorithm that jointly estimates the 3D positions of users and the orientation errors of the BSs from reported BRSRP measurements. The proposed algorithm is also applicable to the case of a single moving user. The performance of the proposed solution is assessed on a realistic mmW 5G outdoor deployment simulator at 39 GHz and based on ray-tracing propagation modeling. Results show that for a minimum of three BSs in line-of-sight (LoS) to the user, and an orientation uncertainty in azimuth angle of $phi leq 3 ^ circ$ sub-meter positioning accuracy is achieved in 90% of locations. Such orientation uncertainty is estimated with an accuracy of 0.5° in 98% of locations.",
keywords = "Uncertainty, US Department of Defense, Estimation, Atmospheric measurements, Particle measurements, Covariance matrices, Position measurement, 5G networks, beamforming, RSRP, positioning, localization, tracking, direction-of-departure, location-awareness, extended Kalman filter, line-of-sight",
author = "Elizaveta Rastorgueva-Foi and M{\'a}rio Costa and Mike Koivisto and Jukka Talvitie and Kari Lepp{\"a}nen and Mikko Valkama",
year = "2018",
month = oct,
doi = "10.1109/ACSSC.2018.8645340",
language = "English",
isbn = "978-1-5386-9219-6",
publisher = "IEEE",
pages = "3--7",
booktitle = "2018 52nd Asilomar Conference on Signals, Systems, and Computers",
note = "Asilomar Conference on Signals, Systems and Computers ; Conference date: 01-01-1900",
}