A cognitive transmission and deployment strategy for UAV-assisted hybrid RIS relay network

Unmanned aerial vehicle (UAV)-assisted relay networks are increasingly vital for emergency scenarios and coverage-limited areas in 5 G/6 G communications, due to their line-of-sight (LoS) transmission and flexible deployment capabilities. Integrating reconfigurable intelligent surfaces (RIS) into these networks enhances signal coverage and energy efficiency, but also introduces new challenges in real-time optimization for multi-reflection environments. This paper proposes a novel UAV-assisted hybrid RIS relay architecture for downlink multi-user multiple-input single-output (MISO) communication systems. The system combines a UAV-mounted RIS and a ground-based RIS, enabling dynamic control over reflection paths. To fully exploit this hybrid architecture, we develop a joint optimization strategy for the transmit covariance matrix, RIS phase shifts, and UAV trajectory, aiming to maximize the achievable rate under system constraints. The proposed framework introduces a cognitive transmission and deployment strategy, where each component adapts intelligently to channel and network conditions. Simulation results demonstrate that our method outperforms conventional UAV relay and static RIS schemes in terms of spectral efficiency, energy efficiency, and deployment flexibility. This work highlights a scalable, low-cost solution for future wireless systems operating in complex and dynamic environments.