A Propagation Model for Mixed Paths Using Dyadic Green's Functions: A Case Study Over the River for a City–River–Forest Path

Silva, Diego Kasuo Nakata da; Eras, Leslye Estefania Castro; Moreira, António; Correia, Luıs M.; Barros, Fabrício José Brito; Cavalcante, Gervásio P. S.

doi:10.1109/lawp.2018.2875333

Cited by 8 publications

(6 citation statements)

References 11 publications

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“…However, to use ML models, it is necessary to realize data acquisition, which will be employed to train different models. In addition, to the best of the authors’ acknowledge, few are the works that collect data to represent signal propagation in an Amazon wooded environment, as seen in [ 14 , 15 , 16 , 17 , 18 , 19 ].…”

Section: Introductionmentioning

confidence: 99%

Application of Artificial Neural Networks for Prediction of Received Signal Strength Indication and Signal-to-Noise Ratio in Amazonian Wooded Environments

Barbosa,

Cruz,

Macedo

et al. 2024

Sensors

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The presence of green areas in urbanized cities is crucial to reduce the negative impacts of urbanization. However, these areas can influence the signal quality of IoT devices that use wireless communication, such as LoRa technology. Vegetation attenuates electromagnetic waves, interfering with the data transmission between IoT devices, resulting in the need for signal propagation modeling, which considers the effect of vegetation on its propagation. In this context, this research was conducted at the Federal University of Pará, using measurements in a wooded environment composed of the Pau-Mulato species, typical of the Amazon. Two machine learning-based propagation models, GRNN and MLPNN, were developed to consider the effect of Amazonian trees on propagation, analyzing different factors, such as the transmitter’s height relative to the trunk, the beginning of foliage, and the middle of the tree canopy, as well as the LoRa spreading factor (SF) 12, and the co-polarization of the transmitter and receiver antennas. The proposed models demonstrated higher accuracy, achieving values of root mean square error (RMSE) of 3.86 dB and standard deviation (SD) of 3.8614 dB, respectively, compared to existing empirical models like CI, FI, Early ITU-R, COST235, Weissberger, and FITU-R. The significance of this study lies in its potential to boost wireless communications in wooded environments. Furthermore, this research contributes to enhancing more efficient and robust LoRa networks for applications in agriculture, environmental monitoring, and smart urban infrastructure.

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Section: Introductionmentioning

confidence: 99%

Application of Artificial Neural Networks for Prediction of Received Signal Strength Indication and Signal-to-Noise Ratio in Amazonian Wooded Environments

Barbosa,

Cruz,

Macedo

et al. 2024

Sensors

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“…Electromagnetic modeling of wave propagation over a mixed ground surface has been extensively investigated in recent years, in examples of river‐to‐forest mixed‐path, complex sea surface, and so on 8,9 . Study reveals when the radio wave traverses a coastline from the land to the sea or vice versa, the radio wave is strongly influenced by the abrupt change of the surface impedances at the operating frequencies of MF and HF 10,11 .…”

Section: Introductionmentioning

confidence: 99%

The mode‐conversion coefficient of ELF wave propagation due to land‐to‐sea transition

Xu¹,

Zhu³

et al. 2020

Int J Numerical Modelling

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The mode‐conversion coefficient is studied to investigate the ELF wave propagation over a mixed land‐to‐sea path. As partition by the consideration of reflection influence from the ionosphere layer, we assume the propagation can be regarded as being subjected to two different models over mixed paths, in terms of the propagation distance in the range of ELF far‐field and near‐field regions, respectively. Both of the mentioned stratified models can be represented as cascaded transmission networks at the abrupt junctions. In conformity with previous study to formulate the far‐field propagation as a cascaded terrestrial waveguide with abrupt height and ground impedance changes, the presented study proposed an equivalent cascaded network to exploit the concept of mode‐conversion for near‐field propagation across discontinuity. Representative parameters of ground types in contrast are supportive to demonstrate the interference of abrupt impedance‐change at ELF band. The presented analysis provide with computational schemes to obtain synthetic fields of ELF wave propagation, which could be extended to more realistic model over multi‐segmental mixed paths.

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“…Existem diversos modelos determinísticos de radiopropagação que simulam ambientes reais não homogêneos [2]- [15]. Trabalhos com não homogeneidade em apenas uma dimensão, por exemplo, regiões com estratificação horizontal, são bem conhecidos na literatura [2]- [6].…”

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“…Problemas de propagação mais comuns em aplicações são aqueles com regiões não homogêneas em duas direções, estes casos são às vezes chamados de regiões mistas. Exemplos de trabalhos que modelam estas situações podem ser encontrados em [8]- [15]. Em [8] os autores analisam a propagação em uma região mista composta pelos meios solo e água, sendo que a aproximação destes é feita por simples impedâncias superficiais equivalentes.…”

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“…Métodos baseados em equações parabólicas também têm sido utilizados eficientemente para estudo da propagação em regiões mistas entre mares e ilhas em [12]- [13] e ruas e florestas em [14]. Também podemos encontrar na literatura modelos baseados em funções diádicas de Green que utilizam a aproximação de superposição de espalhamento [15]. A maioria destes métodos é válida apenas para determinadas faixas de frequências, e alguns efeitos são considerados de forma aproximada, como por exemplo, os efeitos de difrações em obstáculos.…”

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Radiação de Linhas de Corrente Magnética e Elétrica em uma Região Mista com Quatro Meios

Costa,

Oliveira,

Lima

et al. 2023

Anais Do XLI Simpósio Brasileiro De Telecomunicações E Processamento De Sinais

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Resumo-Este trabalho apresenta um modelo numérico para análise da radiação bidimensional de linhas de corrente em uma região mista com quatro meios diferentes. Os meios estão localizados em cada quadrante do plano de análise, e as linhas de corrente magnética e elétrica estão no segundo quadrante. O problema foi inicialmente modelado pelas equações de Maxwell e o método da função de Green. As equações integrais obtidas foram resolvidas pelo Método dos Momentos (MoM). Os resultados mostram um exemplo de aplicação em microondas, onde a região mista é formada por ar, água, solo e floresta, e a frequência de operação é 521 MHz. Palavras-chave-radiacao bidimensional, polarizaçao, meios não homogeneos, funçoes de Green, Método dos Momentos.

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A Propagation Model for Mixed Paths Using Dyadic Green's Functions: A Case Study Over the River for a City–River–Forest Path

Cited by 8 publications

References 11 publications

Application of Artificial Neural Networks for Prediction of Received Signal Strength Indication and Signal-to-Noise Ratio in Amazonian Wooded Environments

Application of Artificial Neural Networks for Prediction of Received Signal Strength Indication and Signal-to-Noise Ratio in Amazonian Wooded Environments

The mode‐conversion coefficient of ELF wave propagation due to land‐to‐sea transition

Radiação de Linhas de Corrente Magnética e Elétrica em uma Região Mista com Quatro Meios

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