Design and Implementation of an Innovative High-Performance Radio Propagation Simulation Tool

Gómez, Josefa; Hellín, Carlos J.; Valledor, Adrián; Barranquero, Marcos; Cuadrado-Gallego, Juan J.; Tayebi, Abdelhamid

doi:10.1109/access.2023.3310825

Cited by 2 publications

(2 citation statements)

References 39 publications

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“…In this context, research has focused on the development of a web-based tool aimed at enhancing signal coverage and quality in various environments through the utilization of genetic algorithms for antenna location optimization. Versions of this tool have been previously introduced by the authors, as evidenced in some of their works [21,22]. Particularly, in [23], a version solving the APP using genetic algorithms and integrating propagation losses through the Hata model [24] from a propagation server was presented.…”

Section: Introductionmentioning

confidence: 99%

Optimizing Antenna Positioning for Enhanced Wireless Coverage: A Genetic Algorithm Approach

Calles-Esteban,

Olmedo,

Hellín

et al. 2024

Sensors

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The precise placement of antennas is essential to ensure effective coverage, service quality, and network capacity in wireless communications, particularly given the exponential growth of mobile connectivity. The antenna positioning problem (APP) has evolved from theoretical approaches to practical solutions employing advanced algorithms, such as evolutionary algorithms. This study focuses on developing innovative web tools harnessing genetic algorithms to optimize antenna positioning, starting from propagation loss calculations. To achieve this, seven empirical models were reviewed and integrated into an antenna positioning web tool. Results demonstrate that, with minimal configuration and careful model selection, a detailed analysis of antenna positioning in any area is feasible. The tool was developed using Java 17 and TypeScript 5.1.6, utilizing the JMetal framework to apply genetic algorithms, and features a React-based web interface facilitating application integration. For future research, consideration is given to implementing a server capable of analyzing the environment based on specific area selection, thereby enhancing the precision and objectivity of antenna positioning analysis.

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Section: Introductionmentioning

confidence: 99%

Optimizing Antenna Positioning for Enhanced Wireless Coverage: A Genetic Algorithm Approach

Calles-Esteban,

Olmedo,

Hellín

et al. 2024

Sensors

Self Cite

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“…In [16], based on the prior knowledge of the scenario digital elevation model and the combination of various individual propagation models available in the literature, a hybrid propagation model for macrocell coverage predictions in densely built-up areas is presented. Recently, the improvement of an advanced radio propagation simulation platform based on ray launching and empirical/semi-empirical methods to analyze macrocellular environments has been presented [17]. Most published works focused only on the acceleration of forward or backward techniques.…”

Section: Introductionmentioning

confidence: 99%

Three-Dimensional Ray-Tracing-Based Propagation Prediction Model for Macrocellular Environment at Sub-6 GHz Frequencies

Liu,

Zhao,

Guo

et al. 2024

Electronics

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This paper presents a 3D ray-tracing model using geometrical optics and the uniform theory of diffraction in radio channel characterizations of macrocellular environments. On the basis of the environmental information obtained from a digitized map, the model is effectively applied. A technique considering multiple reflections and diffractions through the ray path classification is utilized in this model. Ray paths belonging to each ray category are determined using different methods. The proposed model is justified (the prediction accuracy of the model is better than 6.5 dB) with measurement data for the two scenarios and can provide reliable theory as a basis for radio wave propagation prediction and network planning in urban macrocellular environments.

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Design and Implementation of an Innovative High-Performance Radio Propagation Simulation Tool

Cited by 2 publications

References 39 publications

Optimizing Antenna Positioning for Enhanced Wireless Coverage: A Genetic Algorithm Approach

Optimizing Antenna Positioning for Enhanced Wireless Coverage: A Genetic Algorithm Approach

Three-Dimensional Ray-Tracing-Based Propagation Prediction Model for Macrocellular Environment at Sub-6 GHz Frequencies

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