scholarly journals Scaling of Rain Attenuation Models: A Survey

2021 ◽  
Vol 11 (18) ◽  
pp. 8360
Author(s):  
Md Abdus Samad ◽  
Dong-You Choi
Keyword(s):  
Elevation Angle ◽  
Rain Attenuation ◽  
Comparative Investigation ◽  
Vital Role ◽  
Research Field ◽  
Frequency Scaling ◽  
Survey Paper ◽  
Attenuation Models ◽  
Working Procedure

The scaling of rain attenuation methods is promising to quickly estimate power degradation in radio links due to rain with known findings from previous measurements. Although the frequency scaling of rain attenuation technique was introduced ages ago, it has not been addressed adequately. Furthermore, some emerging scaling techniques have recently been proposed in the literature through polarization, elevation angle, and pathlength parameters. A survey paper might play a vital role in order to comprehend all these study areas systematically. However, a survey paper on this research field is currently unavailable in the literature. This review categorizes all the research works using the inherent properties of scaling techniques. Furthermore, this study presents a comparative investigation of parameter-based scaling techniques by considering their working procedure, applicable frequency ranges, and innovative ideas incorporated with all of these models.

scholarly journals Characterization of Rain Specific Attenuation and Frequency Scaling Method for Satellite Communication in South Korea

2017 ◽  
Vol 2017 ◽  
pp. 1-16 ◽  
Author(s):  
Sujan Shrestha ◽  
Dong-You Choi
Keyword(s):  
South Korea ◽  
Satellite Communication ◽  
Rain Rate ◽  
Rain Attenuation ◽  
Frequency Scaling ◽  
Scaling Method ◽  
Ka Band ◽  
Specific Attenuation ◽  
Rain Specific Attenuation ◽  
Attenuation Models

The attenuation induced by rain is prominent in the satellite communication at Ku and Ka bands. The paper studied the empirical determination of the power law coefficients which support the calculation of specific attenuation from the knowledge of rain rate at Ku and Ka band for Koreasat 6 and COMS1 in South Korea that are based on the three years of measurement. Rain rate data was measured through OTT Parsivel which shows the rain rate of about 50 mm/hr and attenuation of 10.7, 11.6, and 11.3 dB for 12.25, 19.8, and 20.73 GHz, respectively, for 0.01% of the time for the combined values of rain rate and rain attenuation statistics. Comparing with the measured data illustrates the suitability for estimation of signal attenuation in Ku and Ka band whose validation is done through the comparison with prominent rain attenuation models, namely, ITU-R P.618-12 and ITU-R P. 838-3 with the use of empirically determined coefficient sets. The result indicates the significance of the ITU-R recommended regression coefficients of rain specific attenuation. Furthermore, the overview of predicted year-wise rain attenuation estimation for Ka band in the same link as well as different link is studied which is obtained from the ITU-R P. 618-12 frequency scaling method.

Rain Attenuation Models for Mobile Satellite Communication in Sudan

2020 ◽  
Author(s):  
Arafa Omer Norain Malik ◽  
Mohammad Kamrul Hasan ◽  
Rashid A. Saeed ◽  
Rania A. Mokhtar ◽  
Siti Norul Huda Sheikh Abdullah ◽  
...  
Keyword(s):  
Satellite Communication ◽  
Rain Attenuation ◽  
Attenuation Models ◽  
Mobile Satellite ◽  
Mobile Satellite Communication

scholarly journals Transfer Learning for Prognostics and Health Management (PHM) of Marine Air Compressors

2021 ◽  
Vol 9 (1) ◽  
pp. 47
Author(s):  
Magnus Gribbestad ◽  
Muhammad Umair Hassan ◽  
Ibrahim A. Hameed
Keyword(s):  
Transfer Learning ◽  
Data Transfer ◽  
Health Management ◽  
Correct Diagnosis ◽  
Vital Role ◽  
Research Field ◽  
Remaining Useful Life ◽  
Prognostic Models ◽  
Classification Problems ◽  
Air Compressors

Prognostics is an engineering discipline focused on predicting the time at which a system or a component will no longer perform its intended function. Due to the requirements of system safety and reliability, the correct diagnosis or prognosis of abnormal condition plays a vital role in the maintenance of industrial systems. It is expected that new requirements in regard to autonomous ships will push suppliers of maritime equipment to provide more insight into the conditions of their systems. One of the stated challenges with these systems is having enough run-to-failure examples to build accurate-enough prognostic models. Due to the scarcity of enough reliable data, transfer learning is established as a successful approach to improve and reduce the need to labelled examples. Transfer learning has shown excellent capabilities in image classification problems. Little work has been done to explore and exploit the use of transfer learning in prognostics. In this paper, various deep learning models are used to predict the remaining useful life (RUL) of air compressors. Here, transfer learning is applied by building a separate prognostics model trained on turbofan engines. It has been found that several of the explored transfer learning architectures were able to improve the predictions on air compressors. The research results suggest transfer learning as a promising research field towards more accurate and reliable prognostics.

Analysis of Selected Earth-Space Rain Attenuation Models for a Tropical Station

2016 ◽  
Vol 3 (2) ◽  
pp. 383 ◽  
Author(s):  
A. I. O. Yussuff
Keyword(s):  
Prediction Models ◽  
Measurement Data ◽  
Daily Rainfall ◽  
Rain Attenuation ◽  
Propagation Path ◽  
Tropical Regions ◽  
Earth Space ◽  
Budget Analysis ◽  
Link Budget ◽  
Attenuation Models

The restrained use of millimeter bands is due to severe rain attenuation. Attenuation is caused when rain cells intersects radio wave’s propagation path; resulting in deep fades. The effect of rainfall is more severe in tropical regions characterized by heavy rainfall intensity and large raindrops; hence, rain attenuation analyses are essential to study rain fade characteristics for use in earth-space link budget analysis, for outage prediction resulting from rain attenuation. Tropical regions are particularly challenged with signal outage, necessitating the formulation and development of suitable prediction model(s) for the region. Therefore, extensive knowledge of the propagation phenomena mitigating system availability and signal quality in these bands are required. Daily rainfall data were collected from the Nigerian Meteorological Services for Lagos for spanning January to December 2010. Results showed that although, the ITU-R model out-performed the other prediction models under consideration, none of prediction models matched the measurement data.

scholarly journals Short-term prediction of rain attenuation level and volatility in Earth-to-Satellite links at EHF band

2008 ◽  
Vol 15 (4) ◽  
pp. 631-643 ◽  
Author(s):  
L. de Montera ◽  
C. Mallet ◽  
L. Barthès ◽  
P. Golé
Keyword(s):  
Time Series ◽  
Prediction Error ◽  
Nonlinear Models ◽  
Garch Model ◽  
Rain Attenuation ◽  
Frequency Scaling ◽  
Attenuation Level ◽  
Satellite Links ◽  
Short Term Prediction ◽  
The Cost

Abstract. This paper shows how nonlinear models originally developed in the finance field can be used to predict rain attenuation level and volatility in Earth-to-Satellite links operating at the Extremely High Frequencies band (EHF, 20–50 GHz). A common approach to solving this problem is to consider that the prediction error corresponds only to scintillations, whose variance is assumed to be constant. Nevertheless, this assumption does not seem to be realistic because of the heteroscedasticity of error time series: the variance of the prediction error is found to be time-varying and has to be modeled. Since rain attenuation time series behave similarly to certain stocks or foreign exchange rates, a switching ARIMA/GARCH model was implemented. The originality of this model is that not only the attenuation level, but also the error conditional distribution are predicted. It allows an accurate upper-bound of the future attenuation to be estimated in real time that minimizes the cost of Fade Mitigation Techniques (FMT) and therefore enables the communication system to reach a high percentage of availability. The performance of the switching ARIMA/GARCH model was estimated using a measurement database of the Olympus satellite 20/30 GHz beacons and this model is shown to outperform significantly other existing models. The model also includes frequency scaling from the downlink frequency to the uplink frequency. The attenuation effects (gases, clouds and rain) are first separated with a neural network and then scaled using specific scaling factors. As to the resulting uplink prediction error, the error contribution of the frequency scaling step is shown to be larger than that of the downlink prediction, indicating that further study should focus on improving the accuracy of the scaling factor.

scholarly journals Rain Attenuation Scaling in South Korea: Experimental Results and Artificial Neural Network

Electronics ◽  
2021 ◽  
Vol 10 (16) ◽  
pp. 2030 ◽  
Author(s):  
Md Abdus Samad ◽  
Feyisa Debo Diba ◽  
Dong-You Choi
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
South Korea ◽  
Rain Attenuation ◽  
Experimental Results ◽  
International Telecommunication Union ◽  
International Telecommunication ◽  
Artificial Neural ◽  
Attenuation Models ◽  
Artificial Neural Network Ann

Scaling rain attenuation parameters will significantly benefit the quick monitoring of rain attenuation in a particular channel with previously known results or in situ setup attenuation measurements. Most of the rain attenuation scaling techniques have been derived for slant links. In this study, we also applied frequency and polarization scaling techniques for terrestrial link applications. We collected real measured datasets from research paper publications and examined those datasets using International Telecommunication Union-Radiocommunication sector (ITU-R) models (P.530-17, P.618-13). Our analyzed results show that existing long-term frequency and polarization scaling rain attenuation models (ITU-R P.618-13 for slant links and ITU-R P.530-17 for terrestrial links) show reduced performance for frequency and polarization scaling measured locations in South Korea. Hence, we proposed a new scaling technique using artificial neural networks from the measured rain attenuation data of slant and terrestrial links in South Korea. The experimental results confirm that the proposed Artificial Neural Network (ANN)-based scaling model shows satisfactory performance to predict attenuation for frequency and vertical polarization scaling.

scholarly journals Modeling of the Marine atmosphere and its impact on Ka-band channels

2022 ◽  
Vol 355 ◽  
pp. 03046
Author(s):  
Zheng Liu ◽  
Fu-an Sun ◽  
Bin Zhou
Keyword(s):  
Rainfall Intensity ◽  
Elevation Angle ◽  
Estimation Method ◽  
Atmospheric Environment ◽  
Marine Atmosphere ◽  
Frequency Channel ◽  
Ka Band ◽  
Variation Characteristics ◽  
Attenuation Models ◽  
Atmosphere Environment

The sea atmosphere environment will affect the Ka frequency channel in TT&C. Firstly, this paper briefly introduces the Marine atmospheric environment. Attenuation models of water vapor solubility and rainfall intensity are established. The variation characteristics of atmospheric environment and the estimation method of rainfall intensity are studied. Finally, the influence of Marine atmosphere on Ka-band channel is simulated and analyzed. The simulation results show that different elevation angles have different effects on Ka-band channels. The influence result decreases gradually with the elevation Angle increasing.

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