TY - JOUR
T1 - Joint User Localization and Location Calibration of a Hybrid Reconfigurable Intelligent Surface
AU - Ghazalian, Reza
AU - Chen, Hui
AU - Alexandropoulos, George C.
AU - Seco-Granados, Gonzalo
AU - Wymeersch, Henk
AU - Jantti, Riku
N1 - Publisher Copyright:
© 1967-2012 IEEE.
PY - 2024/1
Y1 - 2024/1
N2 - The recent research in the emerging technology of reconfigurable intelligent surfaces (RISs) has identified its high potential for localization and sensing. However, to accurately localize a user placed in the area of influence of an RIS, the RIS location needs to be known a priori and its phase profile is required to be optimized for localization. In this article, we study the problem of the joint localization of a hybrid RIS (HRIS) and a user, considering that the former is equipped with a single reception radio-frequency (RF) chain enabling simultaneous tunable reflections and sensing via power splitting. Focusing on the downlink of a multi-Antenna base station, we present a multi-stage approach for the estimation of the HRIS position and orientation as well as the user position. Our simulation results, including comparisons with the Cramér-Rao lower bounds, demonstrate the efficiency of the proposed localization approach, while showcasing that there exists an optimal HRIS power splitting ratio for the desired multi-parameter estimation problem.
AB - The recent research in the emerging technology of reconfigurable intelligent surfaces (RISs) has identified its high potential for localization and sensing. However, to accurately localize a user placed in the area of influence of an RIS, the RIS location needs to be known a priori and its phase profile is required to be optimized for localization. In this article, we study the problem of the joint localization of a hybrid RIS (HRIS) and a user, considering that the former is equipped with a single reception radio-frequency (RF) chain enabling simultaneous tunable reflections and sensing via power splitting. Focusing on the downlink of a multi-Antenna base station, we present a multi-stage approach for the estimation of the HRIS position and orientation as well as the user position. Our simulation results, including comparisons with the Cramér-Rao lower bounds, demonstrate the efficiency of the proposed localization approach, while showcasing that there exists an optimal HRIS power splitting ratio for the desired multi-parameter estimation problem.
KW - Channel estimation
KW - hybrid reconfigurable intelligent surface
KW - localization
KW - sensing
KW - synchronization
UR - https://www.scopus.com/pages/publications/85168727954
U2 - 10.1109/TVT.2023.3306936
DO - 10.1109/TVT.2023.3306936
M3 - Article
AN - SCOPUS:85168727954
SN - 0018-9545
VL - 73
SP - 1435
EP - 1440
JO - IEEE Transactions on Vehicular Technology
JF - IEEE Transactions on Vehicular Technology
IS - 1
ER -