RIS-Aided UE’s Localization Method Using QR Decomposition in Hybrid Field-THz System

Accuracy can be improved by localization techniques aided by reconfigurable intelligent surfaces (RIS). The majority of studies, however, primarily use base stations (BS) to pick up signals. The accuracy of the user’s positioning is impacted by the mutual interference between various pathways in the mixed field, which is ignored by BS information while designing positioning algorithms. The mixed field gain channel matrix is subjected to QR decomposition in this letter. The R matrix improves the directional information of the user (UE), greatly increasing the accuracy of the UE’s location. In particular, to extract the UE’s angle domain information from the R matrix, we first provide an angle domain dictionary set approach. Next, we present a user localization technique based on QR decomposition for dictionaries (QR-CDL and QR-PHD-MUSIC) that eliminates interference beams in various pathways, creates a lower sparsity angle domain dictionary set, and applies QR decomposition to the mixed field’s channel gain matrix. The UE’s angle domain information is then obtained utilizing iterative techniques. The experimental findings demonstrate that the algorithm provided in this research can achieve higher user location accuracy when compared to the dictionary-based localization (CDL) and polar-domain hierarchical dictionary-MUSIC (PHD-MUSIC) approach.