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计算机工程 ›› 2013, Vol. 39 ›› Issue (2): 61-66. doi: 10.3969/j.issn.1000-3428.2013.02.012

• 网络与通信 • 上一篇    下一篇

超短波无线网络规划方法研究

程 权 1,2,廖名学 1,胡晓惠 1,何晓新 1   

  1. (1. 中国科学院软件研究所天基综合信息系统重点实验室,北京 100190;2. 中国科学院研究生院,北京 100049)
  • 收稿日期:2012-02-10 修回日期:2012-05-21 出版日期:2013-02-15 发布日期:2013-02-13
  • 作者简介:程 权(1990-),男,硕士研究生,主研方向:无线网络规划;廖名学,助理研究员;胡晓惠、何晓新,研究员

Research on Ultra-short Wave Wireless Network Planning Method

CHENG Quan 1,2, LIAO Ming-xue 1, HU Xiao-hui 1, HE Xiao-xin 1   

  1. (1. Science and Technology on Integrated Information System Laboratory, Institute of Software, Chinese Academy of Sciences, Beijing 100190, China; 2. Graduate University of Chinese Academy of Sciences, Beijing 100049, China)
  • Received:2012-02-10 Revised:2012-05-21 Online:2013-02-15 Published:2013-02-13

摘要: 为改进超短波无线网络的构建方式,研究在给定若干必要网络节点的条件下,增加机动节点构成最优网络的方法。为平衡网络的建设成本、可靠性和通信质量的关系,设计一个分层优化模型,并提出分层多目标优化近似算法求解该模型,根据目标函数的优先层次求得满足约束条件的近似最优解。仿真结果表明,该算法能找到与最优解近似甚至相同的解。与GLiD算法相比,其规划的网络成本更低,可靠性和通信质量更好。

关键词: 超短波, 无线网络规划, 分层多目标优化, 近似算法, 贪心算法, 动态规划

Abstract: In order to improve the traditional way of ultra-short wave wireless network construction, this paper studies how to form the optimal network by adding mobile nodes to a group of necessary nodes. In order to achieve the balance of network construction cost, reliability and communication quality, it designs a hierarchical optimization model. To solve this model, it proposes a hierarchical multi-objective optimization approximation algorithm. According to the priority levels of objective functions, the algorithm can achieve the approximate optimal solution which meets constraints. Simulation results show that this algorithm can effectively achieve the approximate or even the same solution as the optimal solution. Compared with the GLiD algorithm, this algorithm can plan a better network with less construction cost, higher reliability and better communication quality.

Key words: ultra-short wave, wireless network planning, hierarchical multi-objective optimization, approximation algorithm, greedy algorithm, dynamic planning

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