通信学报 ›› 2014, Vol. 35 ›› Issue (5): 44-48.doi: 10.3969/j.issn.1000-436x.2014.05.006

• 学术论文 • 上一篇    下一篇

基于免疫算法的TD-SCDMA网络基站选址优化

张英杰1,2,毛赐平1,2,俎云霄3,孙先佑1,2   

  1. 1 湖南大学 信息科学与工程学院,湖南 长沙 410082
    2 湖南大学 通信节能研究所,湖南 长沙 410082
    3 北京邮电大学 电子工程学院,北京 100876
  • 出版日期:2014-05-25 发布日期:2017-07-24
  • 基金资助:
    国家自然科学基金资助项目;湖南省自然科学基金资助项目

Immune algorithm-based base station location optimization in the TD-SCDMA network

Ying-jie ZHANG1,2,Ci-ping MAO1,2,Yun-xiao ZU3,Xian-you SUN1,2   

  1. 1 School of Information Science and Engineering, Hunan University, Changsha 410082, China
    2 Institute for Communications Energy Conservation, Hunan University, Changsha 410082, China
    3 School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
  • Online:2014-05-25 Published:2017-07-24
  • Supported by:
    The National Natural Science Foundation of China;The Natural Science Foundation of Hunan Pro-vince

摘要:

针对已有3G 基站选址优化算法的不足和 TD-SCDMA 网络的特点,提出了一种基于免疫算法的TD-SCDMA 网络基站选址优化方案。建立了基站选址问题的数学模型,设计了基于反学习的种群初始化方案和精英交叉策略,给出了免疫优化算法框架。实验结果表明,该算法不仅能够以较小的建站代价获得较高的网络覆盖率,而且算法具有较好的收敛性。

关键词: 免疫算法, 反学习, TD-SCDMA网络, 基站选址

Abstract:

According to the defects of the existing 3G base station location optimization algorithms and the characteris-tics of the TD-SCDMA network, an optimization program was proposed for TD-SCDMA network base station location based on immune algorithm. A mathematical model of base station location was established. A population initialization program based on opposition-based learning and an elite crossover strategy were also designed, and the immune optimi-zation algorithm framework was presented. The experiments' result shows that the algorithm cannot only get higher net-work coverage with a relatively smaller consideration, but also have better convergence.

Key words: immune algorithm, opposition-based learning, TD-SCDMA network, base station location

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