RainGaugeNet：面向ISAC应用的基于CSI的Sub-6 GHz降雨衰减测量与分类
RainGaugeNet: CSI-Based Sub-6 GHz Rainfall Attenuation Measurement and Classification for ISAC Applications
AI总结：
本文首次在2.8 GHz频段基于CSI测量并分析降雨衰减，提出利用多径与时延特征的RainGaugeNet分类模型，仅用20秒CSI数据即在视距和非视距场景下分别取得超90%和85%的准确率，显著超越现有方法。
摘要：
降雨影响日常活动，并可能导致洪水等严重灾害。传统的降雨测量系统往往缺乏精细度或需要大量基础设施。虽然降雨引起的电磁波衰减在10 GHz以上频段已有充分文献记载，但sub-6 GHz频段通常被认为受到的影响可以忽略不计。然而，近期研究表明，即使在这些较低频率下也存在可测量的衰减。本研究首次提出了基于信道状态信息（CSI）的2.8 GHz降雨衰减测量与分析。结果证实了该频率下存在降雨引起的衰减，尽管分类仍然具有挑战性。衰减遵循幂律衰减模型，衰减速率随降雨强度增加而降低。此外，降雨开始显著增加了时延扩展。基于这些见解，我们提出了RainGaugeNet，这是第一个利用多径和时间特征的基于CSI的降雨分类模型。仅使用20秒的CSI数据，RainGaugeNet在视距场景下实现了超过90%的分类准确率，在非视距场景下实现了超过85%的分类准确率，显著优于现有最先进方法。
英文摘要：
Rainfall impacts daily activities and can lead to severe hazards such as flooding. Traditional rainfall measurement systems often lack granularity or require extensive infrastructure. While the attenuation of electromagnetic waves due to rainfall is well-documented for frequencies above 10 GHz, sub-6 GHz bands are typically assumed to experience negligible effects. However, recent studies suggest measurable attenuation even at these lower frequencies. This study presents the first channel state information (CSI)-based measurement and analysis of rainfall attenuation at 2.8 GHz. The results confirm the presence of rain-induced attenuation at this frequency, although classification remains challenging. The attenuation follows a power-law decay model, with the rate of attenuation decreasing as rainfall intensity increases. Additionally, rainfall onset significantly increases the delay spread. Building on these insights, we propose RainGaugeNet, the first CSI-based rainfall classification model that leverages multipath and temporal features. Using only 20 seconds of CSI data, RainGaugeNet achieved over 90% classification accuracy in line-of-sight scenarios and over 85% in non-lineof-sight scenarios, significantly outperforming state-of-the-art methods.
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