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.

MPC

multidimensional ES-PRIT

channel estimator

SLAM

5G

mmWave

Författare

Yu Ge

Chalmers, Elektroteknik, Kommunikations- och antennsystem, Kommunikationssystem

Fan Jiang

Chalmers, Elektroteknik, Kommunikations- och antennsystem, Kommunikationssystem

Meifang Zhu

Lunds universitet

Fuxi Wen

Chalmers, Elektroteknik, Kommunikations- och antennsystem, Kommunikationssystem

Lennart Svensson

Chalmers, Elektroteknik, Signalbehandling och medicinsk teknik, Signalbehandling

Henk Wymeersch

Chalmers, Elektroteknik, Kommunikations- och antennsystem, Kommunikationssystem

15th European Conference on Antennas and Propagation, EuCAP 2021

9411339

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

Ämneskategorier

Telekommunikation

Sannolikhetsteori och statistik

Signalbehandling

DOI

10.23919/EuCAP51087.2021.9411339

Mer information

Senast uppdaterat

2021-05-24