Rain Rate and Rain Attenuation Analysis Over Millimeter Waves (28, 38, 60, 70, and 120 GHz) in Microwave 5G/6G Terrestrial Systems
Transactions on Emerging Telecommunications Technologies, cilt.37, sa.8, 2026 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 37 Sayı: 8
- Basım Tarihi: 2026
- Doi Numarası: 10.1002/ett.70469
- Dergi Adı: Transactions on Emerging Telecommunications Technologies
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
- Anahtar Kelimeler: 5G/6G communication systems, frequency bands, prediction models, propagation path, rain attenuation, rain rate, raindrop size distribution
- Kocaeli Üniversitesi Adresli: Evet
Özet
This study aims to examine the utilization of millimeter-wave (mm-Wave) communications in fifth generation (5G) and sixth generation (6G) communication systems in regions with high rainfall rates. The international telecommunication union (ITU) has identified several frequencies, including 28, 38, 60, 70, and 120 GHz, as appropriate and candidate frequencies for the operation of 5G and 6G technologies. Therefore, it is of utmost importance to precisely estimate the attenuation caused by rainfall. A set of attenuation estimation models considering different attenuation factors is proposed for more reliable results. Furthermore, frequency scaling techniques are used to extrapolate rain attenuation from one frequency to another. This paper provides a comprehensive analysis of rain attenuation, considering various factors such as raindrop size, rainfall rate, path length, signal frequency, and polarization type. Additionally, we conduct simulations of rain attenuation models and do a comparative analysis of these models using candidate frequencies. Furthermore, we utilize the artificial neural network (ANN) model to enhance the precision of frequency scaling estimations. The performance evaluation of the previous frequency scaling models and the ANN model was conducted within the frequency range of 28 to 38 GHz. This evaluation is carried out using the mean value and standard deviation of real rain data. The results show that the ANN model outperforms the ITU-R and power-law models in predicting rain attenuation at 38 GHz. The ANN model demonstrated a low percentage error margin of 0.625%, compared to 4.94% for the power-law model and 19.14% for the ITU-R model under certain conditions. Even under more challenging scenarios, the ANN model maintained a 4.94% error margin, while the power-law and ITU-R models showed higher deviations of 11.73% and 17.90%, respectively. Additionally, we enhance the ITU-R frequency scaling formula for the purpose of applications involving mobility between two specific locations.