Loading...

Near-field Localization with a Reconfigurable Intelligent Surface

Bakhshi, Mahdi | 2024

59 Viewed
  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 57780 (05)
  4. University: Sharif University of Technology
  5. Department: Electrical Engineering
  6. Advisor(s): Bayat, Siavash; Amiri, Rouhollah
  7. Abstract:
  8. The rapid advancements in 5G and the planned transition to 6G networks have highlighted the importance of precise localization in complex environments. This thesis explores near-field (NF) localization using reconfigurable intelligent surfaces (RIS) in single-input-single-output (SISO) systems. RIS, as an emerging technology, enables dynamic manipulation of signal propagation environments, significantly improving localization accuracy in scenarios where conventional far-field (FF) techniques fail due to spherical wavefront distortions or multipath effects. This study focuses on optimizing the placement of RIS to minimize localization errors, utilizing advanced metrics such as the Cramér-Rao Bound (CRB) and Position Error Bound (PEB). Through rigorous mathematical modeling, the system is analyzed under NF conditions where the radiative behavior and wave characteristics demand sophisticated approaches. A novel application of the Grey Wolf Optimization (GWO) algorithm is proposed to identify the optimal RIS placement, addressing the inherent non-convexity of the localization problem. Simulation results validate the proposed methodology, showing significant improvements in localization accuracy compared to benchmark techniques. This research provides a comprehensive framework for integrating RIS into next-generation wireless systems, paving the way for enhanced localization capabilities in smart cities, IoT ecosystems, and advanced communication networks. The findings offer valuable insights for academia and industry, emphasizing RIS's potential in solving the unique challenges of NF localization
  9. Keywords:
  10. Reconfigurable Intelligent Surface (RIS) ; Location ; Gray Wolf Algorithm ; Near Field ; Position Error

 Digital Object List

 Bookmark

No TOC