Application of improved immune algorithm in wireless network base station location planning optimization

MA Bao-luo; JIA Zhen-hong; QIN Xi-zhong; CAO Chuan-ling; NIU Hong-mei

doi:10.13873/J.1000-9787(2016)05-0154-04

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Application of improved immune algorithm in wireless network base station location planning optimization

更新时间：2025-09-11

- Application of improved immune algorithm in wireless network base station location planning optimization
- Vol. 35, Issue 5, Pages: 154-157+160(2016)
- 作者机构：
  
  1. 新疆大学信息科学与工程学院
  2. 中国移动通信集团新疆有限公司
- 作者简介：
- 基金信息：
- DOI：10.13873/J.1000-9787(2016)05-0154-04
  CLC： TN929.5;TP18
- Published：2016
- 稿件说明：
移动端阅览
[1]马宝罗,贾振红,覃锡忠,曹传玲,牛洪梅.改进免疫算法在无线网络基站选址优化中的应用[J].传感器与微系统,2016,35(05):154-157+160.

MA Bao-luo, JIA Zhen-hong, QIN Xi-zhong, et al. Application of improved immune algorithm in wireless network base station location planning optimization[J]. 2016, 35(5): 154-157+160.
[1]马宝罗,贾振红,覃锡忠,曹传玲,牛洪梅.改进免疫算法在无线网络基站选址优化中的应用[J].传感器与微系统,2016,35(05):154-157+160. DOI： 10.13873/J.1000-9787(2016)05-0154-04.

MA Bao-luo, JIA Zhen-hong, QIN Xi-zhong, et al. Application of improved immune algorithm in wireless network base station location planning optimization[J]. 2016, 35(5): 154-157+160. DOI： 10.13873/J.1000-9787(2016)05-0154-04.

摘要

为了最小化网络建设成本、提高用户的服务质量

提出了一种基于矢量距离免疫计算的基站选址问题求解方案。设计了基于矢量距离的抗体浓度计算方法

采用了反学习的种群初始化策略

给出了问题求解的数学模型。主要工作是准确确定基站的位置和数目

以达到建站代价最小、且满足用户覆盖率和系统容量的目的。仿真结果表明:所提算法有更突出的全局搜索能力和快速收敛性

能更好地实现用较低的建站成本满足用户覆盖率和系统容量。

Abstract

In order to minimize network construction cost

improve quality of user’s service

a solution for base station location planning based on vector distance immune computation is proposed. The method for antibody concentration calculation based on vector distance is designed

a population initialization strategy based on opposition-based learning is adopted

mathematical model for problem solving is presented. The main task is to accurately determine locations and numbers of base stations

in order to reach the purpose of the minimum cost

and meet user coverage rate and system capacity. Simulation results shows that the proposed algorithm has outstanding global searching ability and fast convergence ability

can well meet user’s coverage rate needs and system capacity with low cost of station construction relatively.

关键词

Keywords

references

基于免疫算法的TD-SCDMA网络基站选址优化 [J]. 张英杰,毛赐平,俎云霄,孙先佑. 通信学报 . 2014(05)

基于免疫算法的电力通信网线路规划方法 [J]. 石悦,郭少勇,邱雪松. 北京邮电大学学报 . 2014(02)

基于免疫克隆算法的认知无线电多信道联合感知方法 [J]. 夏巧桥,田茂,汪鼎文,陈曦. 电子与信息学报 . 2014(01)

无线传感器网络中基于免疫补体优化的感知资源分配算法 [J]. 王献荣,苏小玲. 传感器与微系统 . 2014(01)

多目标优化量子免疫算法求解基站选址问题 [J]. 朱思峰,陈国强,张新刚,李强. 华中科技大学学报(自然科学版) . 2012(01)

基于免疫计算的WCDMA网络基站选址优化 [J]. 朱思峰,刘芳,柴争义. 电子与信息学报 . 2011(06)

基于新型免疫算法的污水处理过程最优控制 [J]. 叶洪涛,罗飞,许玉格,杨红,梁瑾. 华南理工大学学报(自然科学版) . 2010(02)

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