# Path Difference Optimization of 5G Millimeter Wave Communication Networks in Malaysia
## 3 Rain Attenuation  
Rainfall affects wireless channels operating at 10 GHz and above, with this impact being more pronounced in tropical regions due to heavy rainfall. The size of raindrops and the rate of rainfall influence signal attenuation. In the literature, several rain attenuation prediction models exist, including empirical, statistical, fade-slope, physical, and optimization models [34; 35; 36; 37]. Each model estimates rain attenuation based on different environmental characteristics. In this paper, we employ a statistical model to predict rain attenuation because it provides realistic values in tropical regions such as Malaysia. Malaysia's tropical climate is characterized by uniform temperatures, frequent heavy rains, and thunderstorms. Rainfall rates primarily depend on the seasonal monsoons, which consist of the northeast monsoon from October to March and the southeast monsoon from April to September [33]. The ITU-R statistical model is utilized to estimate rain attenuation for mmWave frequencies ranging from 1 GHz to 100 GHz over path differences of up to 60 km. In this model, rain attenuation depends on the path difference, operating frequency, rain rate, polarization, and path reduction factor [38; 39; 40; 41]. The model excludes attenuation due to snowfall, fog, and hail. Consequently, the ITU-R model proves to be the most accurate in predicting rain attenuation in Malaysia. According to the ITU-R model, the path loss due to rainfall in the outdoor region can be defined as the product of the specific attenuation (\(\gamma_{A}\)) and the effective propagation path length (\(R_{eff}\)) [42]. Therefore, the total attenuation (\(\alpha\)) is  
\[\alpha=\gamma_{A}*R_{eff} \tag{1}\] \begin{table}
\begin{tabular}{p{142.3 pt} p{142.3 pt} p{142.3 pt} p{142.3 pt}} \hline \hline
**Author \& Ref. No.** & **Frequency** & **Objectives** & **Key Findings** \\ \hline [PERSON], et al., [22] & 5.9 GHz \& & The impact of dust and sand on vehicle to vehicle communication was considered and estimated the path loss at various frequencies. & Signal attenuation increases with the operating frequency, particle size and concentration of dust and sand increases. \\ \hline [PERSON], et al., [25] & 60 GHz and 70 GHz & & The impact of weather i.e., rainy and winter seasons of Bangladesh was considered to estimate the signal attenuation. & Signal attenuation in winter season was higher than in rainy season. The dry atmosphere and cold weather increases the mmWave signal attenuation. \\ \hline [PERSON]. [PERSON], et al., [28] & 60 GHz & & Impact of rain and snow on vehicle to everything was considered to estimate the signal attenuation using ITU model and cross verified the results using the NYUSIM simulator. \\ \hline [PERSON], et al., [33] & 38 GHz & & The impact of rain on the signal propagation was estimated using the ITU-R model and 2D video meter. \\ \hline \hline \end{tabular}
\end{table} 
Table 1: _Cont._The specific attenuation depends on the intensity of the rainfall, which is estimated from the rain rate \((A)\) after some percentage of time through the power law relationship, which is given as  
\[\gamma_{A}=K.A^{\beta} \tag{2}\]  
where \(K\) is a constant and \(\beta\) depends on the operating frequency and polarization of the signal. The \(K\) and \(\beta\) values for mmWave frequencies from 1 GHz to 1000 GHZ are listed in the lookup table [41] for both vertical and horizontal polarization. The Malaysian Meteorological Department maintains a database of general weather forecast data. The rainfall rate after a particular time percentage, i.e., 0.01%, is considered in this paper when estimating the path attenuation. The effective path length is always less than the actual path length, and is defined as the product of the distance between the transmitter and receiver \((R)\) and the path reduction factor due to rainfall \((p_{r})\) after a particular time period.