Reconfigurable Intelligent Surface Assisted Millimeter Wave Indoor Localization Systems

Reconfigurable intelligent surfaces (RISs) are regarded as one of the most promising techniques in the sixth-generation (6G) mobile communication networks. With the feature of smartly tuning the electromagnetic environment, RISs provide a possibility for ubiquitous and high-precision localization in 6G. However, proper system models for large indoor RIS-assisted networks and high-precision localization algorithms are still missing. In this paper, we propose a RIS-assisted downlink millimeter-wave (mmWave) indoor localization framework based on segment-by-segment far-field assumption. In addition, a brand new coarse-to-fine localization algorithm with low-complexity grid design is provided. Numerical results show that millimeter-level localization precision is achieved under the RIS-assisted indoor scenarios, which reveals that RIS can provide a solid support for accurate localization in the 6G era.

I. Introduction

Reconfigurable intelligent surfaces (RISs) have been recently proposed as a promising technique to achieve high spectral efficiency and extend coverage areas of the fifth-generation (5G) communication systems [1], [2]. Conventional wireless environment is uncontrollable, while RISs can manipulate wireless channels by dynamically tuning the signal reflections via a large number of low-cost reflecting units [3]. As such, RISs realize controllable multiple wireless propagation paths and thus draw a lot of attention to localization problems. In 4G, localization exploits the time-difference-of-arrival measurements by multiple base stations (BSs) [4]. In 5G, massive multi-input multi-output (MIMO) antennas are equipped at the BS side, and more information including angle-of-arrival (AoA) and angle-of-departure (AoD) can be used to perform localization at each BS [5]. In 6G, RISs are regarded as an indispensable technique, and thus the scenarios become RIS-assisted MIMOs.