Autonomous Large Language Model-Assisted Pattern-Switching Technology Based on Amplitude–Phase-Controllable Intelligent Metasurface

Programmable metasurfaces provide transformative platforms for wavefront manipulation and beamforming. However, current works still highly rely on manual control (e.g., pre-specified look-up table rules), which limits their applications for intelligent wireless communications. Here, we propose a large language model (LLM)-assisted pattern-switching technology based on an amplitude–phase-controllable metasurface, which can reason the working states of the metasurface according to semantics and realize the expected beam-steering and beamforming functions. The proposed meta-atom integrates two types of diodes (PIN and varactor diodes), providing independent amplitude–phase control and 360° full-phase coverage. The LLM can conduct the dimensionality reduction in high-level semantics into structured electromagnetic targets and map them to the metasurfaces, controlling the sequences of the metasurface and thereby realizing the desired pattern-switching function. The autonomy refers to task-level autonomous execution after a high-level user requirement is specified, including automatic state searching, threshold-based performance evaluation, and iterative reconfiguration. To verify the feasibility of the proposed strategy, we fabricated an amplitude–phase-controllable metasurface and conducted LLM-assisted functional measurements. The measured results agree well with the expected ones. The proposed method holds great potential for future human–machine interfaces in wireless communications.