Research proposes aerial reconfigurable surfaces with fluid antennas for 6G networks

A new technical paper proposes integrating autonomous aerial vehicles with multi-functional reconfigurable intelligent surfaces (MF-RISs) to address high data traffic demands in sixth-generation (6G) networks. This architecture, called AM-RIS, operates within fluid antenna-assisted full-duplex networks. The AM-RIS provides hybrid functionalities including signal reflection, amplification, and energy harvesting, potentially improving both signal coverage and sustainability. Fluid antennas facilitate fine-grained spatial adaptability at full-duplex-enabled base stations, complementing residual self-interference suppression. The research aims to maximize overall energy efficiency by jointly optimizing transmit downlink beamforming at the base station, uplink user power, configuration of AM-RIS, and positions of the fluid antenna and AM-RIS. Due to the hybrid continuous-discrete parameters and high dimensionality of this intractable problem, the authors have conceived a self-optimized hybrid deep reinforcement learning approach. The paper is available on arXiv with identifier 2604.14309v2. This work addresses the increasing demands for data traffic in next-generation wireless networks through innovative hardware and algorithmic solutions.