Research on Radio Network Intelligent Frequency Selection Technology Based on an Adaptive Genetic Algorithm

Wenjun Wang

doi:10.11959/j.issn.1000-0801.2015056

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Research on Radio Network Intelligent Frequency Selection Technology Based on an Adaptive Genetic Algorithm

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

- Research on Radio Network Intelligent Frequency Selection Technology Based on an Adaptive Genetic Algorithm
- Telecommunications Science Vol. 31, Issue 3, Pages: 61-66(2015)
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- DOI：10.11959/j.issn.1000-0801.2015056
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- Published Online：2015-03，
  
  Published：20 March 2015
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Wenjun Wang. Research on Radio Network Intelligent Frequency Selection Technology Based on an Adaptive Genetic Algorithm[J]. Telecommunications science, 2015, 31(3): 61-66.
DOI：

Wenjun Wang. Research on Radio Network Intelligent Frequency Selection Technology Based on an Adaptive Genetic Algorithm[J]. Telecommunications science, 2015, 31(3): 61-66. DOI： 10.11959/j.issn.1000-0801.2015056.

摘要

针对无线电网络使用频率日益紧张的现状，提出了一种基于自适应遗传算法的智能选频技术，从智能优化的角度考虑对无线网络进行整体选频，在基本遗传算法的基础上，对遗传操作进行改进，对最优个体进行保护以确保收敛性，从而克服了传统选频算法的不足，可有效避免陷入局部最优并最终趋于全局优化。理论分析和仿真研究表明，与传统选频算法相比，新算法在解决大规模网络选频问题时，效率和精度更高，且稳定性也显著增强。

Abstract

In order to solve the problem of selecting frequency more and more difficultly for radio network

an intelligent frequency selection technology based on an adaptive genetic algorithm was proposed.Frequencies were selected for whole radio network from the perspective of intelligent optimization.On the basis of the standard genetic algorithm

this novel method improved genetic operators

and the preservation of the optimal individual algorithm to ensure the diversity of the population was introduced.Therefore

the arithmetic which did well in avoiding some deficiencies of the traditional frequency selection algorithm prevented local optimization and ran into overall optimization ultimately.Theoretical analysis and simulation results show that the new algorithm in solving the problem of frequency selection for large-scale network has higher efficiency and precision than the traditional algorithm

and stability is significantly enhanced.

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references

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