Device-Free 3D Drone Localization in RIS-Assisted mmWave MIMO Networks
Paper in proceeding, 2024

In this paper, we investigate the potential of reconfigurable intelligent surfaces (RISs) in facilitating passive/device-free three-dimensional (3D) drone localization within existing cellular infrastructure operating at millimeter-wave (mmWave) frequencies and employing multiple antennas at the transceivers. The developed localization system operates in the bi-static mode without requiring direct communication between the drone and the base station. We analyze the theoretical performance limits via Fisher information analysis and Cramér Rao lower bounds (CRLBs). Furthermore, we develop a low-complexity yet effective drone localization algorithm based on coordinate gradient descent and examine the impact of factors such as radar cross section (RCS) of the drone and training overhead on system performance. It is demonstrated that integrating RIS yields significant benefits over its RIS-free counterpart, as evidenced by both theoretical analyses and numerical simulations.

millimeter wave (mmWave)

passive 3D drone localization

Cramér Rao lower bound (CRLB)

reconfigurable intelligent surface (RIS)

Author

Jiguang He

Technology Innovation Institute

Great Bay University

Charles Vanwynsberghe

Technology Innovation Institute

Hui Chen

Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks

Chongwen Huang

Zhejiang University

Aymen Fakhreddine

University of Klagenfurt

2020 IEEE Global Communications Conference, GLOBECOM 2020 - Proceedings

23340983 (ISSN) 25766813 (eISSN)

4436-4441
9798350351255 (ISBN)

2024 IEEE Global Communications Conference, GLOBECOM 2024
Cape Town, South Africa,

Subject Categories (SSIF 2025)

Communication Systems

Telecommunications

Signal Processing

DOI

10.1109/GLOBECOM52923.2024.10900989

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4/4/2025 8