In the era of 5G communication, the knowledge of channel state information (CSI) is crucial for enhancing network performance. This paper explores the utilization of language models for spatial CSI prediction within MIMO-OFDM systems. We begin by outlining the significance of accurate CSI in enabling advanced functionalities such as adaptive modulation. We review existing methodologies for CSI estimation, emphasizing the shift from traditional to data-driven approaches. Then a novel framework for spatial CSI prediction using realistic environment information is proposed, and experimental results demonstrate the effectiveness. This research paves way for innovative strategies in managing wireless networks.

翻译：在5G通信时代，信道状态信息（CSI）的认知对于提升网络性能至关重要。本文探讨了在MIMO-OFDM系统中利用语言模型进行空间CSI预测的方法。我们首先概述了精确CSI对于实现自适应调制等高级功能的重要性。我们回顾了现有的CSI估计方法，强调了从传统方法向数据驱动方法的转变。随后，我们提出了一种利用真实环境信息进行空间CSI预测的新颖框架，实验结果验证了其有效性。本研究为无线网络管理的创新策略铺平了道路。