Station placement design method and station placement design program

The site design method employs a genetic algorithm to optimize wireless base station placement, ensuring compliance with installation conditions and improving communication quality and cost efficiency.

WO2026115728A1PCT designated stage Publication Date: 2026-06-04NT T INC
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Patent Information

Authority / Receiving Office
WO · WO
Patent Type
Applications
Current Assignee / Owner
NT T INC
Filing Date
2024-11-29
Publication Date
2026-06-04

AI Technical Summary

Technical Problem

The challenge of determining optimal wireless base station placement to balance coverage, capacity, and cost, while adhering to installation conditions, is not adequately addressed by existing methods, leading to inefficiencies and suboptimal communication performance.

Method used

A site design method and program using a genetic algorithm to generate and evolve base station placement patterns, ensuring compliance with installation requirements by encoding installation or non-installation of base stations as binary genetic information, and optimizing communication quality and equipment costs through an objective function.

Benefits of technology

This approach ensures that the final base station placement design satisfies installation conditions, enhances communication quality, and optimizes equipment costs, providing a more efficient and globally optimal solution compared to local search or exhaustive methods.

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    Figure JP2024042406_04062026_PF_FP_ABST
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Abstract

Provided are a station placement design method and a station placement design program capable of station placement design satisfying a condition of installation of a wireless base station. In this station installation design method, a wireless terminal 2 and installation candidate points 13 are arranged in a target area, and a condition setting that sets an installation-essential condition indicating whether installation of a wireless base station 4 is essential is performed for each installation candidate point 13. Subsequently, a generation change that updates a plurality of individuals of the population by using a genetic algorithm method is performed on the basis of an evaluation using an objective function for each individual of the population. The generation change is performed so that each individual included in the updated group satisfies the installation-essential condition. Each individual has genetic information representing installation / non-installation of the wireless base station 4 at each installation candidate point 13. Subsequently, an individual is selected from the population after the generation change has been performed a plurality of times, thereby obtaining a station placement design pattern corresponding to the individual. The objective function is calculated on the basis of the wireless communication quality of the wireless terminal 2 when the wireless base station 4 is installed at the installation candidate point 13.
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