LLM-RIMSA: Large Language Models driven Reconfgurable Intelligent Metasurface Antenna Systems
- Citation Author(s):
-
Yunsong Huang
- Submitted by:
- Yunsong Huang
- Last updated:
- DOI:
- 10.21227/r8v1-7334
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Abstract
The LLM-RIMSA dataset, designed to advance 6G networks through ultra-massive connectivity and intelligent radio environments. The dataset is built around a novel framework that integrates large language models (LLMs) with a reconfigurable intelligent metasurface antenna (RIMSA) architecture. This integration addresses limitations in hardware efficiency, dynamic control, and scalability seen in existing RIS technologies.
Instructions:
The RIMSA technology utilizes parallel coaxial feeding and 2D metasurface integration, allowing independent amplitude and phase adjustment for each metamaterial element. The dataset serves as a benchmark for researchers aiming to develop and test LLM-driven approaches for intelligent radio environment optimization.
