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The Allocation of Base Stations with Region Clustering and Single-Objective Nonlinear Optimization

Author

Listed:
  • Jian Chen

    (School of Mechanical Engineering, Yangzhou University, Yangzhou 225127, China)

  • Jiajun Tian

    (School of Mechanical Engineering, Yangzhou University, Yangzhou 225127, China)

  • Shuheng Jiang

    (School of Mechanical Engineering, Yangzhou University, Yangzhou 225127, China)

  • Yunsheng Zhou

    (School of Mechanical Engineering, Yangzhou University, Yangzhou 225127, China)

  • Hai Li

    (School of Mechanical Engineering, Yangzhou University, Yangzhou 225127, China)

  • Jing Xu

    (School of Mechanical Engineering, Yangzhou University, Yangzhou 225127, China)

Abstract

For the problem of 5G network planning, a certain number of locations should be selected to build new base stations in order to solve the weak coverage problems of the existing network. Considering the construction cost and some other factors, it is impossible to cover all the weak coverage areas so it is necessary to consider the business volume and give priority to build new stations in the weak coverage areas with high business volume. Aimed at these problems, the clustering of weak point data was carried out by using k-means clustering algorithm. With the objective function as the minimization of the total construction cost of the new base stations, as well as the constraints as the minimal distance between adjacent base stations and the minimal coverage of the communication traffic, the single-objective nonlinear programming models were established to obtain the layout of macro and micro base stations in order to illustrate the impact of the shape of the station coverage area, the circular and the “shamrock” shaped coverage areas were compared in this paper. For the “shamrock” base station, a secondary clustering was undertaken to judge the main directions of the three sector coverage areas. Then, an improved model taking the coverage overlapping into consideration was proposed to correct the coverage area of different sectors. Finally, the optimal layout was obtained by adjusting the distribution of all base stations globally. The results show that the optimal planning method proposed in this paper has good practicability, which also provides a very good reference for solving similar allocation problems of dynamic resources.

Suggested Citation

  • Jian Chen & Jiajun Tian & Shuheng Jiang & Yunsheng Zhou & Hai Li & Jing Xu, 2022. "The Allocation of Base Stations with Region Clustering and Single-Objective Nonlinear Optimization," Mathematics, MDPI, vol. 10(13), pages 1-19, June.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:13:p:2257-:d:849241
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    References listed on IDEAS

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    1. Rudolf Mathar & Michael Schmeink, 2001. "Optimal Base Station Positioning and Channel Assignment for 3G Mobile Networks by Integer Programming," Annals of Operations Research, Springer, vol. 107(1), pages 225-236, October.
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    Cited by:

    1. Jian Chen & Yongkun Shi & Jiaquan Sun & Jiangkuan Li & Jing Xu, 2023. "Base Station Planning Based on Region Division and Mean Shift Clustering," Mathematics, MDPI, vol. 11(8), pages 1-22, April.

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