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Deploying an Aerial Reconfigurable Intelligent Surface for Vehicle-to-Vehicle Communications (PL: Wykorzystanie powietrznych przełączalnych inteligentnych powierzchni do komunikacji międzypojazdowej)

Salim Janji

TL;DR

The paper investigates deploying a drone relay station (DRS) equipped with a reconfigurable intelligent surface (RIS) to boost ground V2V communication. It formulates a two-part optimization: a trajectory plan for the DRS to quickly reach positions that maximize RIS-aided throughput, and an orientation control strategy to minimize interference from a nearby node by adjusting the RIS phase alignment. The trajectory is guided by a midpoint-based target location and height optimization solved via gradient methods, while interference is mitigated analytically by optimizing a rotation angle $\alpha$ to zero the interference-affected RIS term $\Psi_I^{(n)}(\alpha)$. Simulation results show the framework provides throughput gains, with orientation control yielding modest improvements, highlighting a practical and deployable approach for enhancing V2V connectivity using aerial RIS-enabled relays.

Abstract

This paper addresses the deployment of a drone equipped with a reconfigurable intelligent surface (RIS), creating a drone relay station (DRS) to enhance the connectivity of vehicle-to-vehicle (V2V) pairs on the ground. The trajectory of the DRS is optimized to quickly reach the best location for maximizing throughput. Additionally, the presence of an interfering node is considered, and an analytical solution is derived to determine the optimal orientation of the DRS at each time step, minimizing interference to the receiver. Simulation results confirm the effectiveness of the proposed framework.

Deploying an Aerial Reconfigurable Intelligent Surface for Vehicle-to-Vehicle Communications (PL: Wykorzystanie powietrznych przełączalnych inteligentnych powierzchni do komunikacji międzypojazdowej)

TL;DR

The paper investigates deploying a drone relay station (DRS) equipped with a reconfigurable intelligent surface (RIS) to boost ground V2V communication. It formulates a two-part optimization: a trajectory plan for the DRS to quickly reach positions that maximize RIS-aided throughput, and an orientation control strategy to minimize interference from a nearby node by adjusting the RIS phase alignment. The trajectory is guided by a midpoint-based target location and height optimization solved via gradient methods, while interference is mitigated analytically by optimizing a rotation angle to zero the interference-affected RIS term . Simulation results show the framework provides throughput gains, with orientation control yielding modest improvements, highlighting a practical and deployable approach for enhancing V2V connectivity using aerial RIS-enabled relays.

Abstract

This paper addresses the deployment of a drone equipped with a reconfigurable intelligent surface (RIS), creating a drone relay station (DRS) to enhance the connectivity of vehicle-to-vehicle (V2V) pairs on the ground. The trajectory of the DRS is optimized to quickly reach the best location for maximizing throughput. Additionally, the presence of an interfering node is considered, and an analytical solution is derived to determine the optimal orientation of the DRS at each time step, minimizing interference to the receiver. Simulation results confirm the effectiveness of the proposed framework.

Paper Structure

This paper contains 9 sections, 17 equations, 3 figures.

Table of Contents

  1. Introduction
  2. System model
  3. Problem formulation
  4. Proposed Solution
  5. Setting the trajectory of the DRS
  6. Reducing interference by controlling orientation
  7. Simulation results
  8. Simulation setup
  9. Conclusions

Figures (3)

  • Figure 1: Depiction of the examined scenario where a V2V pair is engaged in communication with potential obstacles impeding direct connections between vehicles. A DRS is deployed to enhance connectivity, yet interference reflected by the DRS from other nodes must also be accounted for.
  • Figure 2: Received throughput through the DRS at each cycle index averaged across all simulated V2V pairs. Optimizing orientation seems to slightly improve the performance since it cancels the interference.
  • Figure 3: Cancelling the interference seems to improve the rate by 0.5%.