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基于NSGA-II算法的机动通信系统站址规划方法
引用本文:颜陆红,郭文普,徐东辉,杨海宇.基于NSGA-II算法的机动通信系统站址规划方法[J].计算机应用研究,2022,39(1):226-230+235.
作者姓名:颜陆红  郭文普  徐东辉  杨海宇
作者单位:火箭军工程大学 作战保障学院,西安710025
摘    要:针对机动通信中通信节点可移动和复杂地形影响通信信号等特点,提出不规则地形条件下处于无线宽带工作模式的机动通信系统基站选址规划方法。首先,通过分析机动通信场景确定站址规划的数学模型;其次,使用改进的NSGA-Ⅱ算法求解选址方案;最后,根据用户需求选定最佳方案。仿真实验结果表明,该方法能够减小有效覆盖损失和通信中断风险,改进后算法能够保证优化过程的多样性并改善优化效果,场景参数和用户偏好都会对规划的最终结果产生影响。所用方法能够综合考虑系统的覆盖能力和机动特性,为用户推荐符合需求的方案并快速适应需求的变化。

关 键 词:机动通信系统  站址规划  NSGA-Ⅱ  多目标优化
收稿时间:2021/6/17 0:00:00
修稿时间:2021/12/22 0:00:00

Base station location planning method of mobile communication system based on NSGA-II
Yan Luhong,Guo Wenpu,Xu Donghui and Yang Haiyu.Base station location planning method of mobile communication system based on NSGA-II[J].Application Research of Computers,2022,39(1):226-230+235.
Authors:Yan Luhong  Guo Wenpu  Xu Donghui and Yang Haiyu
Affiliation:(College of Operational Support,Rocket Force University of Engineering,Xi’an 710025,China)
Abstract:Aiming at the characteristics of mobile nodes and complex terrain affecting signals in mobile communication, this paper proposed a base station location planning method for the mobile communication system in wireless broadband mode and irregular terrain. Firstly, this paper analyzed the mobile communication scenarios to establish the mathematical model. Secondly, it used the improved NSGA-II to find the base station location schemes. Finally, it selected the best scheme according to the need of the user. Simulation experiments show that the method can reduce the loss of coverage and the risk of communication interruption. The improved algorithm can ensure the diversity of the optimization process and improve the optimization effect, and both scenario parameters and user preferences will affect the final result. The proposed method can consider the coverage and mobility characteristics, recommend the planning scheme that meets the user''s need, and quickly adapt to the changes in the need of the user.
Keywords:mobile communication system  base station location planning  NSGA-Ⅱ  multi-objective optimization
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