Joint User Detection and Localization in Near-Field Using Reconfigurable Intelligent Surfaces

Abstract

This letter studies the problem of jointly detecting active user equipments (UEs) and estimating their location in the near field, wherein the base station (BS) is unaware of the number of active (or inactive) UEs and their positions. The system is equipped with multiple reconfigurable intelligent surfaces (RISs) that aid the process of inspecting the coverage area of the BS with adequate localization resolution providing a low-complexity solution for detection and location estimation. To address this problem, we propose to utilize the additional degrees of freedom due to the additional inspection points provided by the RISs. Specifically, we propose an iterative detection procedure, where multiple inspections are jointly considered, allowing the BS to assign known pilots to previously detected UEs and thereby to provide a structured channel access. Also, the problem of multiple access interference is explored and identified as a limiting performance factor for the activity detection. The results show that, with a proper implementation of the RISs, our proposed scheme can detect/localize the UEs with high accuracy, augmenting benchmark UE detection schemes to a spatially aware detection.