计算机工程

• 人工智能及识别技术 • 上一篇    下一篇

基于人工物理优化的认知子载波资源分配

张正球 1,汪宏海 2   

  1. (1.福建师范大学软件学院,福州 350027; 2.浙江旅游职业学院,杭州 311231)
  • 收稿日期:2015-03-05 出版日期:2016-03-15 发布日期:2016-03-15
  • 作者简介:张正球(1978-),男,讲师,主研方向为智能计算、认知无线电网络;汪宏海,副教授。
  • 基金项目:

    福建省教育厅JK类科技基金资助项目(JK2010010);福建省自然科学基金资助项目(2011J01339)。

Cognitive Subcarrier Resource Allocation Based on Artificial Physics Optimization

ZHANG Zhengqiu  1,WANG Honghai  2   

  1. (1.Faculty of Software,Fujian Normal University,Fuzhou 350027,China;2.Tourism College of Zhejiang,Hangzhou 311231,China)
  • Received:2015-03-05 Online:2016-03-15 Published:2016-03-15

摘要:

针对基于正交频分复用的认知无线电网络子载波资源分配存在收敛较慢的问题,基于该问题的NP特性,提出一种基于人工物理优化的求解算法。给出资源分配问题的模型和求解步骤,并根据问题特点,设计多元离散编码方式、种群初始化方法、微粒作用力方程和约束处理方式。实验结果表明,该算法可减少系统所需的总发射功率,提高子载波分配的效果。

关键词: 人工物理优化, 认知无线电网络, 子载波分配, 正交频分复用, NP-hard问题

Abstract:

Aiming at the subcarrier resource allocation problem of cognitive radio network based on Orthogonal Frequency Division Multiplexing(OFDM),and considering the NP feature of the problem,an algorithm based on Artificial Physics Optimization(APO) is presented.The model of the problem and the solving process of the algorithm are given.Polyandry discrete encoding,population initialization method,and particle force equation are designed for problem solving.Experimental results show that the proposed algorithm can reduce the total transmitting power required by the system,improving subcarrier allocation.

Key words: Artificial Physics Optimization(APO), cognitive radio network, subcarrier allocation, Orthogonal Frequency Division Multiplexing(OFDM), NP-hard problem

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