# Smartphone-Based Experimental Analysis of Rainfall Effects on LTE Signal Indicators
## 5 Data-Driven Analysis
### Rainfall Impact on Signal Measurements
#### 5.2.2 Frequency Difference for the Different Weather
Figure 14: Signal measurements during rain (4–6 April): (**a**) NPSD for signal measurements. (**b**) RSSI power difference of NPSD between rainy days and dry days. (**c**) RSRP power difference of NPSD between rainy days and dry days. (**d**) RSRQ power difference of NPSD between rainy days and dry days. (**e**) SNR power difference of NPSD between rainy days and dry days. Figure 15: Signal measurements during rain (10–12 May): (**a**) NPSD for signal measurements. (**b**) RSSI power difference of NPSD between rainy days and dry days. (**c**) RSRP power difference of NPSD between rainy days and dry days. (**d**) RSRQ power difference of NPSD between rainy days and dry days. (**e**) SNR power difference of NPSD between rainy days and dry days. The power spectral density increase at low frequencies on RSSI and SNR can be attributed to rain-related effects. Firstly, multipath scattering occurs when radio waves reflect off various surfaces such as buildings and the ground, leading to the superposition of multiple signal copies at the receiver. During rainy conditions, the increased atmospheric moisture can further enhance these scattering effects, disrupting the original signal pattern. Secondly, rain-induced attenuation is a critical factor affecting signal propagation. Rain-drops absorb and scatter the radio waves, causing a decrease in signal strength. Different propagation paths might have different rain-caused attenuation. RSRP is a measure of the power level of the LTE reference signals, providing a direct indication of the signal strength from the serving cell. RSSI captures the total average signal power, which includes not only the reference symbols but also interference. In NLoS scenarios, the variations in RSRP caused by rainfall can be less pronounced due to the complex nature of microwave propagation and the daily variations observed. Interference is also influenced by rainfall, and the rainfall effects on the reference signal and interference might be different and result in a higher observed power in the low-frequency range of RSSI. RSRQ is an indicator of signal quality, and it can be derived from RSRP and RSSI, as shown in Equation (1). Consequently, the impact of rainfall on RSRQ may be drowned, given that both metrics are intertwined. SNR measures the ratio of received signal strength to noise level. Rainfall can affect both components of the SNR differently, which may lead to a higher proportion of low-frequency components in the signal spectrum. The NPSD and the difference between the rain event and the dry period in Dataset3 are shown in Figure 16. The reference dry days are from 31 March at 12 p.m. to 2 April at 12 p.m. During rainy periods, there is more power in frequencies below 0.0417 (\(\times\)1/3600) Hz for both RSSI and SNR measurements. Spectral analysis of the three datasets indicates that rainy days generally exhibit more power at lower frequencies in both RSSI and SNR measurements. Lower frequencies correspond to longer time intervals, and the increased power at these frequencies suggests that signal measurement patterns during rain occur over extended periods compared to dry days. This indicates that rainfall disrupts the signal patterns that typically  
Figure 16: Signal measurements during rain (4–6 April): (**a**) NPSD for signal measurements. (**b**) RSSI power difference of NPSD between rainy days and dry days. (**c**) RSRP power difference of NPSD between rainy days and dry days. (**d**) RSRQ power difference of NPSD between rainy days and dry days. (**e**) SNR power difference of NPSD between rainy days and dry days. emerge within shorter time intervals, reinforcing the conclusion that rainfall influences signal measurements.