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Modification of Distance Factor in Rain Attenuation Prediction for Short Range Millimetre-wave Links
IEEE Antennas and Wireless Propagation Letters ( IF 3.7 ) Pub Date : 2020-06-01 , DOI: 10.1109/lawp.2020.2987462
Asma Ali Hussein Budalal , Md Rafiqul Islam , Khaizuran Abdullah , Tharek Abdul Rahman

Prediction accuracy of rain attenuation on short-range millimeter-wave (mm-wave) terrestrial links is of the utmost importance for signal strength prediction and link budget of 5G systems and beyond. This letter contributes to the prediction of rain attenuation over millimeter-wave frequencies for a short-range path (less than 1 km). Interestingly, rain-induced attenuation predicted by utilizing ITU-R P.530-17 largely overestimates the measured data at 26 and 38 GHz with 300 m path length in Malaysia. This is due to the inclusion of the distance factor, which ranges between 2.5 (f = 38 GHz) and 2.54 (26 GHz). The behavior of the distance factor is investigated thoroughly, and it is found that the maximum values of the distance factor are inconsistent for the path lengths less than 1 km. Consequently, a modification for the distance factor r in ITU-R P530.17 has been proposed. The rain attenuation data measured are utilized to validate and improve the proposed modifications. In addition, available rain attenuation measurements at 25 GHz for 223 m path length in Japan and 75 GHz for 10 m path length in Korea are also utilized for validation. Subsequently, several available measurements from different locations are used to validate the accuracy of the proposed model and are found in good agreement.

中文翻译:

短距离毫米波链路降雨衰减预测中距离因子的修正

短程毫米波 (mm-wave) 地面链路上雨衰的预测精度对于 5G 及更高系统的信号强度预测和链路预算至关重要。这封信有助于预测短程路径(小于 1 公里)毫米波频率上的雨衰。有趣的是,利用 ITU-R P.530-17 预测的降雨引起的衰减在很大程度上高估了马来西亚 300 m 路径长度的 26 和 38 GHz 测量数据。这是由于包含了距离因子,其范围在 2.5 (f = 38 GHz) 和 2.54 (26 GHz) 之间。对距离因子的行为进行了深入研究,发现距离因子的最大值对于小于 1 km 的路径长度是不一致的。最后,已提议对 ITU-R P530.17 中的距离因子 r 进行修改。测量的雨衰数据用于验证和改进提议的修改。此外,还利用在日本 223 m 路径长度的 25 GHz 和韩国 10 m 路径长度 75 GHz 下可用的雨衰测量值进行验证。随后,使用来自不同位置的几个可用测量来验证所提出模型的准确性,并且发现它们具有良好的一致性。
更新日期:2020-06-01
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