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학술지 Rain Attenuation Prediction Model for Terrestrial Links Using Gaussian Process Regression
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저자
장기정, 윤영근, 김준석, 김종호, 황강욱
발행일
202111
출처
IEEE Communications Letters, v.25 no.11, pp.3719-3723
ISSN
1089-7798
출판사
IEEE
DOI
https://dx.doi.org/10.1109/LCOMM.2021.3109619
협약과제
21HH9300, 275~450㎓ 대역 초근접 다중경로 전파 채널 모델 개발, 김종호
초록
Rainfall is considered as one of the most crucial atmospheric elements that cause attenuation in signal propagation, especially in high-frequency range for fifth-generation (5G) and beyond wireless networks. To unveil the complex relationships between rain attenuation and other factors including rainfall rate, we propose a new rain attenuation prediction model for terrestrial line-of-sight (LoS) propagation using Gaussian Process Regression (GPR). In the proposed model the Recommendation ITU-R P.530 (called the ITU-R model) is used as the mean function in GPR, and to capture the deviation of measured rain attenuation from the ITU-R model we develop a latent function in GPR motivated from the ITU-R model. We validate with the ITU-R study group 3 databank (DBSG3) that the proposed model provides high prediction accuracy.
KSP 제안 키워드
Atmospheric elements, Fifth Generation(5G), Frequency Range, Gaussian process regression, High Frequency(HF), ITU-R model, International telecommunications union radiocommunication(ITU-R), Latent function, Line-Of-Sight(LOS), Prediction accuracy, Proposed model