Investigation of the Unified Rain Attenuation Prediction Method With Data From Tropical Climates

Abdulrahman, A. Y.; Rahman, Tharek Abd; Rafiqul, Islam Md.; Olufeagba, B. J.; Abdulrahman, T. A.; Akanni, Jimoh; Amuda, S. A. Y.

doi:10.1109/lawp.2014.2329778

Cited by 20 publications

(17 citation statements)

References 8 publications

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“…PIA can be computed from SA by using the effective path length ( L eff ), which is calculated following the method detailed in Abdulrahman et al () and Bryant et al (), as given below:

L = \frac{H_{r} - H_{s}}{\sin θ} \times C

…”

Section: Introductionmentioning

confidence: 99%

Characterization of GSAT‐14 Satellite Ka‐Band Microwave Signal Attenuation Due to Precipitation Over a Tropical Coastal Station in the Southern Peninsular Region of the Indian Subcontinent

et al. 2020

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This paper focuses on study of attenuation of microwave propagation at Ka‐band frequencies due to precipitation over an Indian Tropical station, Thiruvananthapuram (8.5°N, 76.8°E). The station is located on the gateway of S‐W Indian monsoon into the subcontinent characterized with prolonged rain for a period of about 9 months. A satellite link has been established at Thumba, Thiruvananthapuram, between Ka‐band receiver operating at 20.2 and 30.5 GHz and GSAT‐14 as part of Indian Space Research Organization's Ka‐band propagation experiment. The concurrent measurements of Ka‐band signals and the precipitation, using a collocated laser precipitation monitor instrument, were carried out during the entire period of Indian monsoon. The study focuses on quantifying the dependence of Ka‐band attenuation on rain rate during the rain‐dominated premonsoon and summer monsoon seasons. The observed attenuation has been evaluated with ITU model.

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“…PIA can be computed from SA by using the effective path length ( L eff ), which is calculated following the method detailed in Abdulrahman et al () and Bryant et al (), as given below:

L = \frac{H_{r} - H_{s}}{\sin θ} \times C

…”

Section: Introductionmentioning

confidence: 99%

Characterization of GSAT‐14 Satellite Ka‐Band Microwave Signal Attenuation Due to Precipitation Over a Tropical Coastal Station in the Southern Peninsular Region of the Indian Subcontinent

et al. 2020

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“…Olufeagba, T.A. Abdulrahman, J. Akanni, and S.A.Y. Amuda, [13] updated the necessity for integrating crop-climate structures and also clarified that the integration can assist to overcome current difficulties like mismatch between farmer's requirement and obtainable predictions, risks and time related doubts, task in achieving institutional, financial and political provision, etc. This literature observed the incorporated methods so far established and strongly sustained the integration of crop weather representations for improvement of the predictions.…”

Section: Literature Surveymentioning

confidence: 99%

“…The general formula of accuracy, precision, and recall for determining weather forecasting and crop detection rate is given in Eqs. (12), (13), and (14). …”

Section: Performance Measurementioning

confidence: 99%

Deep Learning Based Weighted SOM to Forecast Weather and Crop Prediction for Agriculture Application

Mohan¹,

Patil²

2018

IJIES

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Abstract:One of the most experimentally difficult problem in the world is weather forecasting, which is a basic mechanism in meteorology. Especially in data mining system, there are different information mining strategies are available, for example, K-Means, Artificial Neural Network (ANN) and Support Vector Machine (SVM), etc. These weather predicting strategies are financially high and also very inconsistent for large datasets. To overcome these issues, an effective dimensionality reducing strategy: Self Organizing Map (SOM) is proposed along with Latent Dirichlet Allocation (LDA). The SOM strategy is one of the proper dimensionality reducing strategy to highlight the self-arranging outline. After reducing the measurement, the dimensionality reduced information are used to forecast climate for a reasonable outcome. A reasonable season for an appropriate crop is arranged with the guide of Deep Neural Network (DNN) classification system. This research work depends on finding appropriate information model, which helps in accomplishing high precision and simplification for value forecast. Finally, the experimental outcome shows that the proposed approach improved accuracy in weather and crop prediction up to 7-23% compared to the existing methods.

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“…Rainfall is a significant impediment that obstructs the propagation of mm‐wave signals from transmitter to receiver. Millimeter‐wave signals can be absorbed, scattered, depolarized, and diffracted by rain . This can restrict the propagation of mm‐wave signals, causing high signal attenuation loss through the effective propagation path length (km) measured in dB/km.…”

Section: Introductionmentioning

confidence: 99%

“…Rain attenuation harshly increases when the frequency, rain density, or effective length are increased. This attenuation reduces the reliability, availability, and degraded the overall performance of the communications link . As a result, rain attenuation is a real and concerning issue facing the implementation of mm‐waves, especially in tropical regions with consistent heavy rainfall.…”

Section: Introductionmentioning

confidence: 99%

Rain attenuation of millimetre wave above 10 GHz for terrestrial links in tropical regions

Shayea

Rahman

Azmi

et al. 2018

Trans Emerging Tel Tech

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Millimeter waves (mm‐waves) within frequency bands of 10 to 86 GHz will be used for both microwave and access link fifth‐generation (5G) systems. Thus, it is very important to investigate these bands to ensure reliability when 5G is applied in tropical regions like Malaysia in the coming few years. One of the major obstacles facing the propagation of mm‐waves in tropical regions is the rain attenuation. Rainfall results in the absorption, scattering, and diffraction of radio waves. This contributes to increased transmission losses and a reduction in the received signal levels. The effect is more severe in tropical regions that are characterized by intense heavy rainfall and large raindrop sizes. This paper provides a general overview on rain attenuation of mm‐wave bands. It highlights the nature of rain in tropical regions and its effects on the propagation of mm‐waves. It also reports the latest measurement studies focused on rain attenuation in mm‐wave frequency bands and the prediction methods used to estimate rain attenuation in mm‐waves. It contributes to the understanding of channel behavior and the characterization of mm‐wave bands during rainfall in tropical regions, especially in Malaysia. This study further strives to determine research gaps in this field as well as the future work and various propagation measurement systems that can be used to conduct real measurements and to develop prediction models for rain attenuation in mm‐waves for 5G systems. Furthermore, this paper analyzes the rain rate and rain attenuation on the basis of real measurement data conducted in Universiti Teknologi Malaysia at Skudai Campus, Malaysia. The analyzed results indicated that the rain attenuation at 38 GHz is critical and it can result in 18.4 dB/km as specific rain attenuation at 0.01% percentage of the time.

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Investigation of the Unified Rain Attenuation Prediction Method With Data From Tropical Climates

Cited by 20 publications

References 8 publications

Characterization of GSAT‐14 Satellite Ka‐Band Microwave Signal Attenuation Due to Precipitation Over a Tropical Coastal Station in the Southern Peninsular Region of the Indian Subcontinent

Characterization of GSAT‐14 Satellite Ka‐Band Microwave Signal Attenuation Due to Precipitation Over a Tropical Coastal Station in the Southern Peninsular Region of the Indian Subcontinent

Deep Learning Based Weighted SOM to Forecast Weather and Crop Prediction for Agriculture Application

Rain attenuation of millimetre wave above 10 GHz for terrestrial links in tropical regions

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