5G SLAM with Low-complexity Channel Estimation
Paper in 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.

channel estimator

5G

multidimensional ES-PRIT

SLAM

MPC

mmWave

Author

Yu Ge

Chalmers, Electrical Engineering, Communication and Antenna Systems, Communication Systems

Fan Jiang

Chalmers, Electrical Engineering, Communication and Antenna Systems, Communication Systems

Meifang Zhu

Lund University

Fuxi Wen

Chalmers, Electrical Engineering, Communication and Antenna Systems, Communication Systems

Lennart Svensson

Chalmers, Electrical Engineering, Signal Processing and Biomedical Engineering, Signal Processing

Henk Wymeersch

Chalmers, Electrical Engineering, Communication and Antenna Systems, Communication Systems

15th European Conference on Antennas and Propagation, EuCAP 2021

9411339

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

Subject Categories

Telecommunications

Probability Theory and Statistics

Signal Processing

DOI

10.23919/EuCAP51087.2021.9411339

More information

Latest update

8/24/2021