RainGaugeNet: CSI-Based Sub-6 GHz Rainfall Attenuation Measurement and Classification for ISAC Applications

TL;DR

This paper introduces RainGaugeNet, a novel CSI-based model for rainfall measurement and classification at 2.8 GHz, demonstrating high accuracy and revealing measurable rain-induced attenuation at sub-6 GHz frequencies.

Contribution

It is the first to analyze rainfall attenuation at 2.8 GHz using CSI data and proposes a new classification model that outperforms existing methods.

Findings

Rainfall causes measurable attenuation at 2.8 GHz.

RainGaugeNet achieves over 90% accuracy in LOS scenarios.

RainGaugeNet achieves over 85% accuracy in NLOS scenarios.

Abstract

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.