5G SLAM with Low-complexity Channel Estimation
Paper i proceeding, 2021

5G millimeter-wave signals are beneficial for simultaneous localization and mapping (SLAM), due to their inherent geometric connection to the propagation environment. Channel estimators can exploit received signals to estimate multipath components in terms of delays and angles, which can be used in localization and mapping. Thus, a good channel estimator is essential for 5G SLAM. This paper presents a novel low-complexity multidimensional ESPRIT-based channel estimator and applies it to a 5G SLAM framework. Simulation results demonstrate that the proposed channel estimator can accurately estimate channel information with low computational cost, with limited impact on mapping performance, compared to a tensor-ESPRIT benchmark.

5G

multidimensional ES-PRIT

channel estimator

MPC

mmWave

SLAM

Författare

Yu Ge

Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk

Fan Jiang

Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk

Meifang Zhu

Lunds universitet

Fuxi Wen

Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk

Lennart Svensson

Chalmers, Elektroteknik, Signalbehandling och medicinsk teknik

Henk Wymeersch

Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk

15th European Conference on Antennas and Propagation, EuCAP 2021

9411339
9788831299022 (ISBN)

15th European Conference on Antennas and Propagation, EuCAP 2021
Dusseldorf, Germany,

5G mobil positionering för fordonssäkerhet

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

Ämneskategorier

Telekommunikation

Sannolikhetsteori och statistik

Signalbehandling

DOI

10.23919/EuCAP51087.2021.9411339

Mer information

Senast uppdaterat

2021-12-26