Towards Joint Optimization for UAV-Integrated RIS-Assisted Fluid Antenna Systems

Unmanned aerial vehicles (UAVs) integrated into cellular networks face significant challenges from air-to-ground interference. To address this, we propose a downlink UAV communication system that leverages a fluid antenna system (FAS)- assisted reconfigurable intelligent surface (RIS) to enhance signal quality. By jointly optimizing the FAS port positions and RIS phase shifts, we maximize the achievable rate. The resulting nonconvex optimization problem is solved using successive convex approximation (SCA) based on second-order cone programming (SOCP), which reformulates the constraints into a tractable form. Simulation results show that the proposed algorithm significantly improves both outage probability and achievable rate over conventional fixed-position antenna (FPA) schemes, with particularly large gains in large-scale RIS configurations. Moreover, the algorithm converges rapidly, making it suitable for real-time applications