Orientation aware control improves drone assisted wireless connections
Orientation-Aware Control and Trajectory Design for Aerial RIS-Assisted Wireless Communications
Networking and Internet ArchitectureRobotics
Summary
Wireless signals can get blocked or weakened by obstacles like buildings or trees. Some researchers studied how using flying drones with special surfaces called Reconfigurable Intelligent Surfaces (RIS) can boost these signals by reflecting them. They found that paying attention to the drone’s position and especially its angle (orientation) is really important because even small tilts can affect the signal quality. Their method plans drone paths and adjusts the signal beams together, which made the wireless connections more reliable and faster in their simulations.
What this means in practice
- •For wireless network operators: Improve drone-based wireless coverage in obstacle dense areas by coordinating drone movement and signal beam control considering drone orientation.
- •For drone control engineers: Develop flight controllers that integrate communication goals with drone orientation and movement dynamics for better signal reflection.
Authors
Abdoul Karim A. H. Saliah, Hajar El Hammouti, Daniel Bonilla Licea, Giuseppe Silano
Abstract
Aerial Reconfigurable Intelligent Surfaces (ARISs) can enhance wireless connectivity in obstructed environments by combining reconfigurable metasurfaces with aerial mobility. However, in practical deployments, the Reconfigurable Intelligent Surface (RIS) is rigidly mounted on a multi-rotor Unmanned Aerial Vehicle (UAV), which creates coupled position-orientation dynamics that directly affect communication quality. Since RIS performance is highly sensitive to orientation, point-mass or orientation-invariant models may lead to optimistic performance estimates. This paper proposes an orientation-aware ARIS framework that explicitly accounts for UAV dynamics, actuation limits, and orientation-dependent channels. The proposed approach combines a communications-guided reference trajectory planner with a Nonlinear Model Predictive Control for dynamically feasible trajectory tracking and favorable RIS orientation, while employing lightweight beamforming and RIS phase-shift updates. Simulations show that accounting for orientation improves user throughput by 13.77%, while the proposed joint communication updates improve network throughput by 28% over phase-shift-only optimization and by at least a factor of 2.5 over beamforming-only optimization. These results highlight the importance of orientation-aware modeling and joint communication-control design in ARIS-assisted wireless systems.