Recursive UE Localization for a Multi-RIS-Assisted Wireless System in an Obstacle-Dense Environment

Accurate user equipment (UE) localization in an obstacle-dense environment is quite challenging due to the insufficiency of line-of-sight (LoS) links. However, the reconfigurable intelligent surface (RIS) has the potential for offering alternative RIS-assisted LoS links to refine the localization results. In this paper, a recursive localization scheme is proposed based on an iterative RIS selection strategy, with the help of prior knowledge of the propagation environment. And numerical results based on a geometry-based channel simulator in a typical composite urban environment exhibit the improvement of localization accuracy.