Outlier Rejection for 5G-Based Indoor Positioning in Ray-Tracing-Enabled Industrial Scenario
Year: 2024
Type: preprint
Abstract: The precise and accurate indoor positioning using cellular communication technology remains to be a prerequisite for several industrial applications, including the emergence of a new topic of Integrated Sensing and Communication (ISAC). However, the frequently occurring Non-Line-of-Sight (NLoS) conditions in a heavy multipath dominant industrial scenario challenge the wireless signal propagation, leading to abnormal estimation errors (outliers) in the signal measurements taken at the receiver. In this paper, we investigate the iterative positioning scheme that is robust to the outliers in the Time of Arrival (ToA) measurements. The Iteratively Reweighted Least Squares (IRLS) positioning scheme formulated on the Least Squares (LS) is implemented to reject the outlier measurements and reweight the available ToA samples based on their confidence. Our positioning scheme is validated under 5G frequency bands, including the C-band (3.7 GHz) and the mmWave-band (26.8 GHz) in a Ray-Tracing enabled industrial scenario with different emulation setups.
Source: arXiv (Cornell University)
Institutions: Robert Bosch (Germany), Universitat Politècnica de Catalunya
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4403747465