Towards Real-time Radio-SLAM via Optimal Importance Sampling
Paper in proceeding, 2022

In future cellular networks, it will be possible to estimate the channel parameters of non-line-of-sight propagation paths providing unique opportunities for simultaneous localization and mapping (SLAM) with commodity user equipments (UEs). Radio-SLAM generally relies on generating samples of the UE trajectory and constructing a trajectory-conditioned map. To reduce the number of samples and complexity, we propose an iterative method to approximate the optimal sampling density. The numerical results demonstrate that the added computational complexity of the proposed method can be easily justified by the more efficient use of particles. As an outcome, the presented filter nearly achieves the lower bound and still runs in real-time.

importance density

simultaneous localization and mapping

millimeter wave

probability hypothesis density

Author

Ossi Kaltiokallio

University of Tampere

Roland Hostettler

Uppsala University

Jukka Talvitie

University of Tampere

Yu Ge

Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks

Hyowon Kim

Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks

Henk Wymeersch

Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks

M. Valkama

University of Tampere

IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC

Vol. 2022-July
9781665494557 (ISBN)

23rd IEEE International Workshop on Signal Processing Advances in Wireless Communication, SPAWC 2022
Oulu, Finland,

5G cellular positioning for vehicular safety

VINNOVA (2019-03085), 2020-01-01 -- 2021-12-31.

Subject Categories

Computational Mathematics

Communication Systems

Signal Processing

DOI

10.1109/SPAWC51304.2022.9833982

More information

Latest update

1/18/2023