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Neural networks applications for the prediction of propagation path loss in urban environments

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5 Author(s)

This paper presents neural network based models for the prediction of propagation path loss in urban environment. The neural networks are designed separately for line-of-sight (LOS) and non-line-of-sight (NLOS) cases. The performance of the neural models is compared to that of the COST231-Walfisch-Ikegami model, the Walfisch-Bertoni model and the single regression model, based on the absolute mean error, standard deviation and the root mean squared error between predicted and measured values.

Published in:

Vehicular Technology Conference, 2001. VTC 2001 Spring. IEEE VTS 53rd  (Volume:1 )

Date of Conference:

9-9 May 2001