RIS-Augmented Millimeter-Wave MIMO Systems for Passive Drone Detection

In the past decade, the number of amateur drones is increasing, and this trend is expected to continue in the future. The security issues brought by abuse and misconduct of drones become more and more severe and may incur a negative impact to the society. In this paper, we leverage existing cellular multiple-input multiple-output (MIMO) base station (BS) infrastructure, operating at millimeter wave (mmWave) frequency bands, for drone detection in a device-free manner with the aid of one reconfigurable intelligent surface (RIS), deployed in the proximity of the BS. We theoretically examine the feasibility of drone detection with the aid of the generalized likelihood ratio test (GLRT) and validate via simulations that, the optimized deployment of an RIS can bring added benefits compared to RIS-free systems. In addition, the effect of RIS training beams, training overhead, and radar cross section, is investigated in order to offer theoretical design guidance for the proposed cellular RIS-based passive drone detection system.

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Publication Details

Published
2024-09-02
DOI
https://doi.org/10.1109/pimrc59610.2024.10817446
Citations
4
Primary Topic
UAV Applications and Optimization
Type
article
Field-Weighted Citation Impact
5.20

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article

RIS-Augmented Millimeter-Wave MIMO Systems for Passive Drone Detection

Aymen Fakhreddine, Jiguang He, George C. Alexandropoulos
4 citations
UAV Applications and Optimization
5.20
article

RIS-Augmented Millimeter-Wave MIMO Systems for Passive Drone Detection

Aymen Fakhreddine, Jiguang He, George C. Alexandropoulos
article en
4 citations

Abstract

In the past decade, the number of amateur drones is increasing, and this trend is expected to continue in the future. The security issues brought by abuse and misconduct of drones become more and more severe and may incur a negative impact to the society. In this paper, we leverage existing cellular multiple-input multiple-output (MIMO) base station (BS) infrastructure, operating at millimeter wave (mmWave) frequency bands, for drone detection in a device-free manner with the aid of one reconfigurable intelligent surface (RIS), deployed in the proximity of the BS. We theoretically examine the feasibility of drone detection with the aid of the generalized likelihood ratio test (GLRT) and validate via simulations that, the optimized deployment of an RIS can bring added benefits compared to RIS-free systems. In addition, the effect of RIS training beams, training overhead, and radar cross section, is investigated in order to offer theoretical design guidance for the proposed cellular RIS-based passive drone detection system.

National and Kapodistrian University of Athens (GR), Technology Innovation Institute (AE)
Austrian Science Fund, HORIZON EUROPE Framework Programme
Affordable and clean energy
Openalex Percentile: Top 5%
UAV Applications and Optimization
5.20
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RIS-Augmented Millimeter-Wave MIMO Systems for Passive Drone Detection — Aymen Fakhreddine, Jiguang He, et al. · (2024) | TGRS Research Map | TGRS