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<p>Finding the optimal placement of Base Transceiver Stations (BTSs) is a significant challenge in deploying radio communication networks for Public Safety and Defense based on the TETRA (Terrestrial Trunked Radio) standard. Due to the multitude of variables involved, this problem is widely recognized in the literature as computationally complex. Traditional approaches often rely on radio propagation prediction tools (software) and depend heavily on the designer’s experience and intuition to determine the most effective BTS locations. This paper presents a solution based on bio-inspired computation—specifically, the Particle Swarm Optimization (PSO) algorithm—employing a total fitness function that simultaneously considers both coverage and cost-efficiency. Among the propagation models studied for this project, the Okumura-Hata model—selected through a prior measurement campaign—was used to estimate the received power and evaluate the coverage percentage within the region of interest. To evaluate the proposed method, we considered a region of interest of 290 km<InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(^{2}\)</EquationSource> <EquationSource Format="MATHML"><math> <mmultiscripts> <mrow /> <mrow /> <mn>2</mn> </mmultiscripts> </math></EquationSource> </InlineEquation>, which can be fully served by three BTSs. The optimization results demonstrate that allocating only two of these BTSs already achieves 90% coverage of the area. This represents a significant reduction in infrastructure while still meeting the coverage level typically required for public-safety systems.</p>

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Optimal placement of base transceiver stations for public safety and defense radio networks using PSO

  • 期刊论文

  • 发表日期：

    2025年12月17日

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  • Ubiraci Barretto,
  • Fabrício G. S. Silva

摘要

Finding the optimal placement of Base Transceiver Stations (BTSs) is a significant challenge in deploying radio communication networks for Public Safety and Defense based on the TETRA (Terrestrial Trunked Radio) standard. Due to the multitude of variables involved, this problem is widely recognized in the literature as computationally complex. Traditional approaches often rely on radio propagation prediction tools (software) and depend heavily on the designer’s experience and intuition to determine the most effective BTS locations. This paper presents a solution based on bio-inspired computation—specifically, the Particle Swarm Optimization (PSO) algorithm—employing a total fitness function that simultaneously considers both coverage and cost-efficiency. Among the propagation models studied for this project, the Okumura-Hata model—selected through a prior measurement campaign—was used to estimate the received power and evaluate the coverage percentage within the region of interest. To evaluate the proposed method, we considered a region of interest of 290 km \(^{2}\) 2 , which can be fully served by three BTSs. The optimization results demonstrate that allocating only two of these BTSs already achieves 90% coverage of the area. This represents a significant reduction in infrastructure while still meeting the coverage level typically required for public-safety systems.