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Omnidirectional Multi-Rotor Aerial Vehicle Pose Optimization: A Novel Approach to Physical Layer Security

Daniel Bonilla Licea, Giuseppe Silano, Mounir Ghogho, Martin Saska

TL;DR

This paper considers an omnidirectional MRAV serving as a Base Station for legitimate ground nodes, under attack by a malicious jammer, and optimize the MRAV pose to maximize the minimum Signal-to-Interference-plus-Noise Ratio (SINR) over all legitimate nodes.

Abstract

The integration of Multi-Rotor Aerial Vehicles (MRAVs) into 5G and 6G networks enhances coverage, connectivity, and congestion management. This fosters communication-aware robotics, exploring the interplay between robotics and communications, but also makes the MRAVs susceptible to malicious attacks, such as jamming. One traditional approach to counter these attacks is the use of beamforming on the MRAVs to apply physical layer security techniques. In this paper, we explore pose optimization as an alternative approach to countering jamming attacks on MRAVs. This technique is intended for omnidirectional MRAVs, which are drones capable of independently controlling both their position and orientation, as opposed to the more common underactuated MRAVs whose orientation cannot be controlled independently of their position. In this paper, we consider an omnidirectional MRAV serving as a Base Station (BS) for legitimate ground nodes, under attack by a malicious jammer. We optimize the MRAV pose (i.e., position and orientation) to maximize the minimum Signal-to-Interference-plus-Noise Ratio (SINR) over all legitimate nodes.

Omnidirectional Multi-Rotor Aerial Vehicle Pose Optimization: A Novel Approach to Physical Layer Security

TL;DR

This paper considers an omnidirectional MRAV serving as a Base Station for legitimate ground nodes, under attack by a malicious jammer, and optimize the MRAV pose to maximize the minimum Signal-to-Interference-plus-Noise Ratio (SINR) over all legitimate nodes.

Abstract

The integration of Multi-Rotor Aerial Vehicles (MRAVs) into 5G and 6G networks enhances coverage, connectivity, and congestion management. This fosters communication-aware robotics, exploring the interplay between robotics and communications, but also makes the MRAVs susceptible to malicious attacks, such as jamming. One traditional approach to counter these attacks is the use of beamforming on the MRAVs to apply physical layer security techniques. In this paper, we explore pose optimization as an alternative approach to countering jamming attacks on MRAVs. This technique is intended for omnidirectional MRAVs, which are drones capable of independently controlling both their position and orientation, as opposed to the more common underactuated MRAVs whose orientation cannot be controlled independently of their position. In this paper, we consider an omnidirectional MRAV serving as a Base Station (BS) for legitimate ground nodes, under attack by a malicious jammer. We optimize the MRAV pose (i.e., position and orientation) to maximize the minimum Signal-to-Interference-plus-Noise Ratio (SINR) over all legitimate nodes.
Paper Structure (7 sections, 14 equations, 2 figures)

This paper contains 7 sections, 14 equations, 2 figures.

Table of Contents

  1. Introduction
  2. System Model
  3. Pose Optimization
  4. Zero Interference
  5. Maximum Gain
  6. Simulation Results
  7. Conclusion

Figures (2)

  • Figure 1: Illustration of two MRAV configurations along with the global ($\mathcal{F}_W$) and untilted ($\mathcal{F}_U$) reference systems: under-actuated (left) and omnidirectional (right) Aboudorra2023ArXiv.
  • Figure 2: Minimum SINR (i.e., $\min(\Gamma_1,\Gamma_2)$) for different jamming powers for the optimum solution (blue), the maximum gain solution (red), the zero interference solution (black), and the vertical orientation solution (magenta).