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

Francisco Calles-Esteban, Alvaro Antonio Olmedo, Carlos J Hellín, Adrián Valledor, Josefa Gómez, Abdelhamid Tayebi
Author Information
  1. Francisco Calles-Esteban: Computer Science Department, Universidad de Alcalá, 28801 Alcala de Henares, Spain. ORCID
  2. Alvaro Antonio Olmedo: Computer Science Department, Universidad de Alcalá, 28801 Alcala de Henares, Spain. ORCID
  3. Carlos J Hellín: Computer Science Department, Universidad de Alcalá, 28801 Alcala de Henares, Spain. ORCID
  4. Adrián Valledor: Computer Science Department, Universidad de Alcalá, 28801 Alcala de Henares, Spain. ORCID
  5. Josefa Gómez: Computer Science Department, Universidad de Alcalá, 28801 Alcala de Henares, Spain. ORCID
  6. Abdelhamid Tayebi: Computer Science Department, Universidad de Alcalá, 28801 Alcala de Henares, Spain. ORCID

Abstract

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.

Keywords

Grants

  1. Projects CM/JIN/2021-033 and PIUAH22/IA-024/Vice rectorate for Research and Knowledge Transfer of the University of Alcala and the Comunidad de Madrid (Spain).

Word Cloud

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