Distributed Reconfigurable Intelligent Surfaces-Enabled Indoor Localization Based On Wireless Fingerprinting

Yongqing Xu, Yong Li, Tony Q.S. Quek

研究成果: Article同行評審

摘要

Wireless fingerprint-based localization methods are widely applied in indoor scenarios due to their low complexity. However, traditional localization methods rely on signals from multiple access points (APs), and their performance degrade significantly when signals from distant APs are weak. In this letter, we propose using distributed reconfigurable intelligent surfaces (RISs) to enhance indoor localization with only one single-antenna AP, achieved by adjusting the phase-shift matrices of multiple RISs to generate distinguishable wireless fingerprints for each sub-region within the localization area. We optimize the phase-shift matrices of multiple RISs by minimizing the weighting localization error probability. The formulated minimization problem is solved through an alternating optimization (AO) algorithm and a Riemannian steepest descent (RSD) algorithm. Extensive simulations validate the effectiveness of the proposed approach.

原文English
頁(從 - 到)1
頁數1
期刊IEEE Wireless Communications Letters
DOIs
出版狀態Accepted/In press - 2024

All Science Journal Classification (ASJC) codes

  • 控制與系統工程
  • 電氣與電子工程

指紋

深入研究「Distributed Reconfigurable Intelligent Surfaces-Enabled Indoor Localization Based On Wireless Fingerprinting」主題。共同形成了獨特的指紋。

引用此