A Hybrid path loss prediction model based on artificial neural networks using empirical models for LTE and LTE-A at 800 MHz and  2600 MHz

D´Assunção, Adaildo Gomes; Cavalcanti, Bruno J.; Cavalcante, Gustavo A.; Mendonça, Laércio M. de; Cantanhede, Gabriel Moura; Oliveira, Marcelo M.M.de

A Hybrid path loss prediction model based on artificial neural networks using empirical models for LTE and LTE-A at 800 MHz and 2600 MHz

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dc.contributor.author	D´Assunção, Adaildo Gomes
dc.contributor.author	Cavalcanti, Bruno J.
dc.contributor.author	Cavalcante, Gustavo A.
dc.contributor.author	Mendonça, Laércio M. de
dc.contributor.author	Cantanhede, Gabriel Moura
dc.contributor.author	Oliveira, Marcelo M.M.de
dc.date.accessioned	2021-02-19T20:19:58Z
dc.date.available	2021-02-19T20:19:58Z
dc.date.issued	2017-09
dc.description.resumo	This article presents the analysis of a hybrid, error correction-based, neural network model to predict the path loss for suburban areas at 800 MHz and 2600 MHz, obtained by combining empirical propagation models, ECC-33, Ericsson 9999, Okumura Hata, and 3GPP’s TR 36.942, with a feedforward Artificial Neural Network (ANN). The performance of the hybrid model was compared against regular versions of the empirical models and a simple neural network fed with input parameters commonly used in related works. Results were compared with data obtained by measurements performed in the vicinity of the Federal University of Rio Grande do Norte (UFRN), in the city of Natal, Brazil. In the end, the hybrid neural network obtained the lowest RMSE indexes, besides almost equalizing the distribution of simulated and experimental data, indicating greater similarity with measurements	pt_BR
dc.identifier.citation	CAVALCANTI, Bruno J.; CAVALCANTE, Gustavo A.; MENDONÇA, Laércio M. de; CANTANHEDE, Gabriel M.; OLIVEIRA, Marcelo M.M. de; D’ASSUNÇÃO, Adaildo G.. A Hybrid Path Loss Prediction Model based on Artificial Neural Networks using Empirical Models for LTE And LTE-A at 800 MHz and 2600 MHz. Journal of Microwaves, Optoelectronics And Electromagnetic Applications, [S.L.], v. 16, n. 3, p. 708-722, set. 2017. Disponível em: https://www.scielo.br/scielo.php?script=sci_arttext&pid=S2179-10742017000300708&lng=en&tlng=en. Acesso em: 20 out. 2020. http://dx.doi.org/10.1590/2179-10742017v16i3925.	pt_BR
dc.identifier.doi	10.1590/2179-10742017v16i3925
dc.identifier.issn	2179-1074
dc.identifier.uri	https://repositorio.ufrn.br/handle/123456789/31577
dc.language	en	pt_BR
dc.publisher	Scielo	pt_BR
dc.rights	Attribution-NonCommercial 3.0 Brazil	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc/3.0/br/	*
dc.subject	Artificial Neural Networks – ANN	pt_BR
dc.subject	Long Term Evolution – LTE	pt_BR
dc.subject	Long Term Evolution Advanced – LTE-A	pt_BR
dc.subject	Propagation models	pt_BR
dc.subject	Path loss	pt_BR
dc.title	A Hybrid path loss prediction model based on artificial neural networks using empirical models for LTE and LTE-A at 800 MHz and 2600 MHz	pt_BR
dc.type	article	pt_BR