Dynamic spectrum allocation for cognitive radio sensor networks based on improved genetic algorithm

Chang CAI; Yafang WANG; Bingmei MIAO; Hui JIANG

doi:10.11959/j.issn.1000-0801.2017217

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Dynamic spectrum allocation for cognitive radio sensor networks based on improved genetic algorithm

research and development | 更新时间：2024-06-05

- Dynamic spectrum allocation for cognitive radio sensor networks based on improved genetic algorithm
- Telecommunications Science Vol. 33, Issue 8, Pages: 85-93(2017)
- 作者机构：
- 作者简介：
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- DOI：10.11959/j.issn.1000-0801.2017217
  CLC： TP393
- Published Online：2017-08，
  
  Published：15 August 2017
- 稿件说明：
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Chang CAI, Yafang WANG, Bingmei MIAO, et al. Dynamic spectrum allocation for cognitive radio sensor networks based on improved genetic algorithm[J]. Telecommunications science, 2017, 33(8): 85-93.
DOI：

Chang CAI, Yafang WANG, Bingmei MIAO, et al. Dynamic spectrum allocation for cognitive radio sensor networks based on improved genetic algorithm[J]. Telecommunications science, 2017, 33(8): 85-93. DOI： 10.11959/j.issn.1000-0801.2017217.

摘要

将认知无线电中的动态频谱分配技术应用在无线传感网中，针对工作在ISM（industrial，scientific and medical）频段的无线传感网面临的频谱资源紧缺问题，提出一种基于改进自适应遗传算法的动态频谱分配方案。该算法以图论着色模型为基础，以最大带宽收益和最小切换频率为目标函数，在交叉和变异过程中采用自适应交叉概率和变异概率代替固定的交叉概率和变异概率。仿真结果表明，与传统遗传算法和颜色敏感图论着色算法相比，该算法可以实现提高频谱利用率、降低能量消耗的预期目标。

Abstract

ISM (industrial scientific and medical) bands where wireless sensor network works faced with the shortage of spectrum resources problems.Aimed at this case

dynamic spectrum allocation in cognitive radio technology was applied in wireless sensor network.A dynamic frequency spectrum allocation scheme was proposed.The algorithm was a modified adaptive genetic algorithm which was based on graph coloring model.In addition

the objective functions of the algorithm were maximum bandwidth gains and minimum spectrum handoff

besides

in the crossover and mutation process

adaptive crossover probability and mutation probability was used instead of the fixed.Experimental results confirm that compared with the traditional genetic algorithm and color sensitive graph coloring algorithm

the proposed algorithm can achieve the expected goal of improving the spectral efficiency and reducing energy consumption.

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references

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