Optimization method for 4G and 5G base station layout planning for electric power wireless private network based on improved genetic algorithm

张文栋; 刘周峰; 谢宏福; 王 茗; 孙玉杰; 沈晓风; 段接迎; 周 霞

doi:10.3969/j.issn.1009-1831.2024.01.011

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Optimization method for 4G and 5G base station layout planning for electric power wireless private network based on improved genetic algorithm

更新时间：2026-03-05

- Optimization method for 4G and 5G base station layout planning for electric power wireless private network based on improved genetic algorithm
- Vol. 26, Issue 1, (2024)
- 作者机构：
  
  1. 国网山东省电力公司,济南,250000
  2. 国电南瑞科技股份有限公司,南京,211000
  3. 南京邮电大学先进技术研究院,南京,210023
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.1009-1831.2024.01.011
  CLC：
- Published：2024
- 稿件说明：
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张文栋, 刘周峰, 谢宏福, et al. Optimization method for 4G and 5G base station layout planning for electric power wireless private network based on improved genetic algorithm[J]. 2024, 26(1).
DOI：

张文栋, 刘周峰, 谢宏福, et al. Optimization method for 4G and 5G base station layout planning for electric power wireless private network based on improved genetic algorithm[J]. 2024, 26(1). DOI： 10.3969/j.issn.1009-1831.2024.01.011.

摘要

在电力4G无线专网中引入5G，进行4G、5G融合组网，对提高电力业务通信效率具有重要意义。首先阐述了5G在电力系统中的应用及4G、5G组网方式。然后，综合考虑电力自有业务、电力业务通信需求、电力基站建设成本、基站运行成本，构建了电力无线专网4G、5G基站布点优化模型，对4G、5G基站进行优化布点。其次对遗传算法中编码、初始化种群操作进行优化设计和改进，大幅减少算法迭代次数，提高收敛速度，降低了模型的求解复杂度。最后基于改进模型对电力4G、5G基站布点优化模型进行求解，可以快速给出4G、5G基站优化方案，满足电力通信覆盖率和经济性等要求。仿真算例验证所提模型、改进算法的合理性和有效性。

Abstract

The introduction of 5G into the electric power 4G wireless private network and the integration of 4 great significance for improving the efficiency of electric power business communication. Firstly application of G and 5G networks are of 5G in the power system and 4G and 5G networking methods is descirbed. Then

comprehensively considering the power own business

power business communication requirements

power base station construction costs

and base station operating costs

the power wireless private network 4G and 5G base station layout optimization models are constructed

and then optimize the layout of 4G and 5G base stations. Secondly

optimize the design and improvement of the coding and initialization population operations in the genetic algorithm

which greatly reduces the number of algorithm iterations

improves the convergence speed

and reduces the complexity of the model. Finally

the improved model solves the optimization model of power 4G and 5G base station layout. It can quickly give 4G and 5G base station optimization solutions to meet the requirements of power communication coverage and economy. Rationality and effectiveness of the proposed model and improved algorithm are verified by simulation examples.

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