TR2023-142

RIS-Assisted Joint Preamble Detection and Localization


    •  Nuti, P., Kim, K.J., Wang, P., Koike-Akino, T., Parsons, K., "RIS-Assisted Joint Preamble Detection and Localization", IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), December 2023.
      BibTeX TR2023-142 PDF
      • @inproceedings{Nuti2023dec,
      • author = {Nuti, Pooja and Kim, Kyeong Jin and Wang, Pu and Koike-Akino, Toshiaki and Parsons, Kieran},
      • title = {RIS-Assisted Joint Preamble Detection and Localization},
      • booktitle = {IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)},
      • year = 2023,
      • month = dec,
      • url = {https://www.merl.com/publications/TR2023-142}
      • }
  • MERL Contacts:
  • Research Areas:

    Communications, Computational Sensing, Signal Processing

Abstract:

Reconfigurable intelligent surface (RIS) is envisioned to be a key enabling technology for future wireless systems and is currently being developed and studied for various applications. In this work, we investigate how a single, passive RIS can assist both preamble detection and localization. We propose a joint preamble detection and localization scheme and a rule-based multi-antenna peak correction method to improve the reliability of range estimates and preamble detection. The proposed approach builds prior information on a low-speed factory vehicle’s position based on a previously estimated position to more efficiently estimate the vehicle’s current location along a trajectory. Simulation results present how RIS can enable these two tasks and how performance varies across various vehicle positions.