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This research addresses a critical gap in aerial Reconfigurable Intelligent Surface (ARIS) deployments by integrating UAV orientation dynamics into trajectory planning, moving beyond simplified point-mass models. By jointly optimizing Nonlinear Model Predictive Control with RIS phase-shift updates, the study demonstrates that accounting for rigid mounting constraints significantly boosts network throughput compared to traditional optimization methods. The work establishes a necessary framework for future aerial wireless systems where physical orientation directly dictates communication efficacy.
Orientation-Aware Control and Trajectory Design for Aerial RIS-Assisted Wireless Communications
arXiv:2609.23157v1 Announce Type: cross 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.
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.
Accepted for publication in IEEE Transactions on Vehicular Technology. Copyright (c) 20xx IEEE. Personal use of this material is permitted. However, permission to use this material for any other purposes must be obtained from the IEEE by sending a request to pubs-permissions@ieee.org
Networking and Internet Architecture (cs.NI); Robotics (cs.RO)
arXiv:2609.23157 [cs.NI]
(or arXiv:2609.23157v1 [cs.NI] for this version)
https://doi.org/10.48550/arXiv.2609.23157 arXiv-issued DOI via DataCite (pending registration)
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