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Joint UAV Trajectory and Beamforming Designs for RIS-Assisted MIMO System

Si Li, Huiqin Du, Duoying Zhang, Kexin Li

2023IEEE Transactions on Vehicular Technology28 citationsDOI

Abstract

This paper considers a wireless downlink multiple-input multiple-output (MIMO) system, where communication between the base station and multiple users is facilitated by a reconfigurable intelligent surface (RIS) deployed on an unmanned aerial vehicle (UAV). Under the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\ell _{0}$</tex-math></inline-formula> -norm-based capacity-limited backhaul, the average weighted sum rate is maximized over the flying period by jointly designing the user scheduling, UAV's trajectory, active beamforming and passive beamforming. Given the highly coupled variables and non-convex combinatorial constraints, the underlying problem is decomposed into three subproblems. Relaxing the mixed-integer constraint as a weighted <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\ell _{1}$</tex-math></inline-formula> -norm, the transmit precoding and user scheduling can be jointly obtained by the conic relaxation. The RIS phase shift with unit-modulus constraint is obtained via the alternating direction method of multipliers. The UAV's trajectory is optimized by the successive convex approximation approach. Numerical results demonstrate the effectiveness of the proposed algorithm in improving the average achievable rate within the constraints of a finite-capacity backhaul.

Topics & Concepts

BeamformingJoint (building)TrajectoryMIMOComputer scienceEngineeringElectronic engineeringTelecommunicationsPhysicsArchitectural engineeringAstronomyAdvanced Wireless Communication TechnologiesUAV Applications and OptimizationAdvanced MIMO Systems Optimization