基于离散粒子群优化算法的合作感知调度方案

张星; 王野; 杨艺; 张钦宇

doi:10.11959/j.issn.1000-436x.2017046

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基于离散粒子群优化算法的合作感知调度方案

学术通信 | 更新时间：2024-06-05

- 基于离散粒子群优化算法的合作感知调度方案
- Cooperative spectrum sensing scheduling scheme based on discrete particle swarm optimization algorithm
- 通信学报 2017年38卷第7期页码：175-185
- 作者机构：
  
  哈尔滨工业大学（深圳）电子与信息工程学院，广东深圳 518055
- 作者简介：
  
  [ "张星（1992-），女，四川宜宾人，哈尔滨工业大学（深圳）硕士生，主要研究方向为认知无线电网络。" ]
  [ "王野（1983-），男，黑龙江佳木斯人，哈尔滨工业大学（深圳）助理教授，主要研究方向为认知无线电和认知网络。" ]
  [ "杨艺（1985-），男，黑龙江哈尔滨人，哈尔滨工业大学（深圳）博士生，主要研究方向为认知无线电和认知网络。" ]
  [ "张钦宇（1972-），男，江苏扬州人，哈尔滨工业大学（深圳）教授，主要研究方向为认知无线电、5G移动通信、深空通信、信息论等。" ]
- 基金信息：
  
  国家自然科学基金资助项目(61501140)
- DOI：10.11959/j.issn.1000-436x.2017046
  中图分类号： TN925
- 网络首发：2017-07，
  
  纸质出版：2017-07-25
- 稿件说明：
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张星, 王野, 杨艺, 等. 基于离散粒子群优化算法的合作感知调度方案[J]. 通信学报, 2017,38(7):175-185.

Xing ZHANG, Ye WANG, Yi YANG, et al. Cooperative spectrum sensing scheduling scheme based on discrete particle swarm optimization algorithm[J]. Journal on Communications, 2017, 38(7): 175-185.
张星, 王野, 杨艺, 等. 基于离散粒子群优化算法的合作感知调度方案[J]. 通信学报, 2017,38(7):175-185. DOI： 10.11959/j.issn.1000-436x.2017046.

Xing ZHANG, Ye WANG, Yi YANG, et al. Cooperative spectrum sensing scheduling scheme based on discrete particle swarm optimization algorithm[J]. Journal on Communications, 2017, 38(7): 175-185. DOI： 10.11959/j.issn.1000-436x.2017046.

摘要

采用CTMC模型分析了网络状态的统计特性，考虑各个次用户感知能力的差异性，分别从主用户和次用户的角度出发，建立了2个关于次用户调度方案的整数规划问题。提出了通过离散粒子群优化算法求解所建问题，并与传统的随机调度方案和基于信噪比的贪婪调度方案进行了比较。仿真结果表明，所提调度方案获得的感知性能更高。

Abstract

The statistical characteristics of the network state changes were analyzed by using the CTMC model.Considering the difference of each secondary user’s sensing ability

two integer programming problems on cooperative sensing scheduling scheme were established from two aspects:the primary users and the secondary users respectively.A discrete particle swarm optimization algorithm was proposed to solve the integer programming problems

and compared with the traditional random scheduling scheme and greedy scheduling scheme based on SNR.The simulation results show that the cooperative sensing scheduling scheme based on discrete particle swarm optimization algorithm is superior to random scheduling scheme and greedy scheduling scheme based on the SNR

which gets a higher spectrum sensing accuracy.

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Keywords

references

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