Feature Extraction for Neural Network Wave Propagation Loss Models from Field Measurements and Digital Elevation Map

Seomin YANG  Hyukjoon LEE  

IEICE TRANSACTIONS on Electronics   Vol.E82-C   No.7   pp.1260-1266
Publication Date: 1999/07/25
Online ISSN: 
Print ISSN: 0916-8516
Type of Manuscript: Special Section PAPER (Special Issue on Microwave and Millimeter Wave Technology)
Category: Propagation and Scattering
neural network,  propagation-loss model,  feature extraction,  

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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.