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

(1. State Grid Shandong Electric Power Co., Ltd., Jinan 250000;2. NARI Technology Development Co., Ltd.,Nanjing 211000, China;3. Institute of Advanced Technology, Nanjing University of Posts andTelecommunications, Nanjing 210023, China)

Clc Number:

TN929.5;TM76

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    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.

    Reference
    Related
    Cited by
Get Citation

张文栋,刘周峰,谢宏福,王 茗,孙玉杰,沈晓风,段接迎,周 霞.基于改进遗传算法的电力无线专网4G、5G基站布点规划优化方法[J].电力需求侧管理英文版,2024,26(1):67-72.

Copy
Related Videos

Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:August 20,2023
  • Revised:October 04,2023
  • Adopted:
  • Online: February 19,2024
  • Published:
Article QR Code