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

Sensors, ISSN: 1424-8220, Vol: 24, Issue: 7
2024
  • 0
    Citations
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    Usage
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    Captures
  • 2
    Mentions
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    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Captures
    1
  • Mentions
    2
    • Blog Mentions
      1
      • Blog
        1
    • News Mentions
      1
      • 1

Most Recent News

New Findings from Universidad de Alcala in the Area of Sensor Research Described (Optimizing Antenna Positioning for Enhanced Wireless Coverage: A Genetic Algorithm Approach)

2024 APR 16 (NewsRx) -- By a News Reporter-Staff News Editor at NewsRx Life Science Daily -- Researchers detail new data in sensor research. According

Article Description

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.

Bibliographic Details

Calles-Esteban, Francisco; Olmedo, Alvaro Antonio; Hellín, Carlos J; Valledor, Adrián; Gómez, Josefa; Tayebi, Abdelhamid

MDPI AG

Chemistry; Computer Science; Physics and Astronomy; Biochemistry, Genetics and Molecular Biology; Engineering

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