计算机科学 ›› 2025, Vol. 52 ›› Issue (6A): 241000015-4.doi: 10.11896/jsjkx.241000015

• 网络&通信 • 上一篇    下一篇

基于聚类模型的C-RAN组网规划方法研究

李恒毅1,2, 杨国1, 魏波1, 陈虹君1,2   

  1. 1 成都锦城学院电子信息学院 成都 611731
    2 成都锦城学院四川省专家工作站 成都 611731
  • 出版日期:2025-06-16 发布日期:2025-06-12
  • 通讯作者: 李恒毅(35820486@qq.com)
  • 基金资助:
    四川省科技厅重点研发计划(2022YFS0109)

Research on the Method of C-RAN Networking Planning Based on Clustering Model

LI Hengyi1,2, YANG Guo1, WEI Bo1, CHEN Hongjun1,2   

  1. 1 College of Electronic Information Engineering,Chengdu Jincheng College,Chengdu 611731,China
    2 Sichuan Expert Workstation of Chengdu Jincheng College,Chengdu 611731,China
  • Online:2025-06-16 Published:2025-06-12
  • About author:LI Hengyi,born in 1981,master,asso-ciate professor.His main research in-terests include mobile communication and Internet of Things application technology.
  • Supported by:
    Key Research and Development Program of the Science and Technology Department of Sichuan Province(2022YFS0109).

摘要: 随着5G通信网络的快速部署,其在信息化社会建设中的重要性日益凸显。5G异构化网络技术和集中式C-RAN组网方式的应用,虽然带来了高效的小区边缘协同处理和成本节约,但也引发了前传网络体量过大和传输线路建设成本增加的问题。为解决这一问题,提出一种基于聚类算法和启发式算法的基站工程规划方法,对C-RAN基站的最佳部署位置进行研究。该方法通过构建K-means聚类模型,以基站与AAU/RRU间的欧氏距离作为约束,寻求最优的基站部署位置。在仿真与结果分析中结合手肘法判断最优聚类K值。以此为依据确定的C-RAN站点位置部署较为合理,能够保证连接到每一个无线收发点,并且消耗的光缆成本最低。此方法具有较好的可推广性,能够为未来的移动通信网络规划和建设提供有益的参考。

关键词: C-RAN组网, 基站规划, K-means聚类, 手肘法, 粒子群优化算法

Abstract: With the rapid deployment of 5G communication networks,their importance in the construction of an information-based society has become increasingly prominent.The application of 5G heterogeneous network technology and centralized C-RAN networking has brought efficient cell edge coordinated processing and cost savings,but it has also led to issues such as an excessively large frontend network scale and increased transmission line construction costs.To address this problem,this paper proposes a base station engineering planning method based on clustering and heuristic algorithms to investigate the optimal deployment locations for C-RAN base stations.This method constructs a K-means clustering model,using the Euclidean distance between base stations and AAU/RRU as a constraint,to seek the optimal base station deployment locations.In the simulation and result analysis,the Elbow method is combined to determine the optimal clustering K value.The C-RAN site locations determined based on this are more reasonable,ensuring connectivity to each wireless transceiver point while minimizing the cost of optical cable consumption.This method has good generalizability and can provide useful references for future mobile communication network planning and construction.

Key words: C-RAN networking, Base station planning, K-means clustering, Elbow method, Particle swarm optimization algorithm

中图分类号: 

  • TN915.02
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