基于离散粒子群优化算法的合作感知调度方案

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

通信学报 ›› 2017, Vol. 38 ›› Issue (7): 175-185.doi: 10.11959/j.issn.1000-436x.2017046

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

哈尔滨工业大学（深圳）电子与信息工程学院，广东深圳 518055

修回日期:2016-09-13 出版日期:2017-07-01 发布日期:2017-08-25
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。
基金资助:
国家自然科学基金资助项目(61501140)

Cooperative spectrum sensing scheduling scheme based on discrete particle swarm optimization algorithm

Xing ZHANG,Ye WANG,Yi YANG,Qin-yu ZHANG

College of Electronic and Information Engineering,Harbin Institute of Technology Shenzhen,Shenzhen 518055,China

Revised:2016-09-13 Online:2017-07-01 Published:2017-08-25
Supported by:
The National Natural Science Foundation of China(61501140)

摘要/Abstract

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。

关键词: 认知无线电, 多授权认知无线电网络, 合作感知调度, 离散粒子群优化算法

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.

Key words: cognitive radio, cognitive radio network with multiple licensed network, cooperative sensing scheduling, discrete particle swarm optimization

中图分类号:

TN925

张星,王野,杨艺,张钦宇. 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,Qin-yu ZHANG. Cooperative spectrum sensing scheduling scheme based on discrete particle swarm optimization algorithm[J]. Journal on Communications, 2017, 38(7): 175-185.

图/表 14

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表1

仿真参数及取值"

参数	含义	取值
M	LN个数	3
N_m	各个LN共享的信道数	4,4,4]
K	参与感知的SU个数	6
N_RFC	每个SU感知的LN个数	2
$λ_{p}^{m}$ /(个·s^-1)	PU的到达速率	0.5,0.5,0.5]
$μ_{p}^{m}$ /(个·s^-1)	PU的离开速率	0.5,0.5,0.5]
λ_s/(个·s^-1)	SU的到达速率	1
μ_s/(个·s^-1)	SU的离开速率	0.5
h_BS/m	基站高度	32
h_MS/m	SU的高度	1.5
F_m/MHz	LN的中心频率	1 900,2 300,3 400]
N	粒子群大小	100

表1

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参考文献 13

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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

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