On the Impact of hardware impairments on RIS-aided localization

Date
2022-05
Editor(s)
Advisor
Supervisor
Co-Advisor
Co-Supervisor
Instructor
Source Title
IEEE International Conference on Communications
Print ISSN
Electronic ISSN
Publisher
IEEE
Volume
Issue
Pages
2846 - 2851
Language
English
Journal Title
Journal ISSN
Volume Title
Series
Abstract

We investigate a reconfigurable intelligent surface (RIS)-aided near-field localization system with single-antenna user equipment (UE) and base station (BS) under hardware impairments by considering a practical phase-dependent RIS amplitude variations model. To analyze the localization performance under the mismatch between the practical model and the ideal model with unit-amplitude RIS elements, we employ the misspecified Cramér-Rao bound (MCRB). Based on the MCRB derivation, the lower bound (LB) on the mean-squared error for estimation of UE position is evaluated and shown to converge to the MCRB at low signal-to-noise ratios (SNRs). Simulation results indicate more severe performance degradation due to the model misspecification with increasing SNR. In addition, the mismatched maximum likelihood (MML) estimator is derived and found to be tight to the LB in the high SNR regime. Finally, we observe that the model mismatch can lead to an order-of-magnitude localization performance loss at high SNRs. © 2022 IEEE.

Course
Other identifiers
Book Title
Citation
Published Version (Please cite this version)