Feature Extraction for Neural Network Wave Propagation Loss Models from Field Measurements and Digital Elevation Map (Special Issue on Microwave and Millimeter Wave Technology)

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概要

• 論文の詳細を見る

• This paper presents algorithms for extracting the values of relevant parameters from field measurements and 3-dimensional geographical data to be used in neural network modeling of wave propagation loss in microcells. The algorithms extract the feature values from 3-dimensional elevation maps and vector maps based on the theory in Computational Geometry. The neural networks trained on these parameters as their input approximate the function of wave propagation loss and can produce predictions with high accuracy. Some experimental results which show the superior performance of our approach over COST-231 method in actual PCS cell sites operating in the city of Seoul are presented.

• 社団法人電子情報通信学会の論文
• 1999-07-25

著者

• Yang Seomin

  Next Generation Protocol Team Electronics And Telecommunications Research Institute

• YANG Seomin

  Kwangwoon University

• LEE Hyukjoon

  Kwangwoon University

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• Feature Extraction for Neural Network Wave Propagation Loss Models from Field Measurements and Digital Elevation Map (Special Issue on Microwave and Millimeter Wave Technology)

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