Selectively Triggered Cooperative Spectrum Sensing in Wireless Cognitive Network

doi:10.3969/j.issn.1000-3428.2017.03.016

Abstract

Abstract: In Wireless Cognitive Network(WCN),conventional cooperative spectrum sensing algorithms are used to enhance the accuracy of spectrum sensing,but cooperative spectrum sensing algorithm increases communication costs and the energy consumption of secondary users.For this reason,a Selective Trigger Cooperative Spectrum Sensing(STCSS) algorithm is proposed,this algorithm determines whether to trigger the secondary cooperative spectrum sensing based on the threshold of current spectrum sensing energy.This makes cooperative spectrum sensing is triggered only when necessary,thereby reduces energy consumption and communication overhead.Simulation results show that,compared with Cooperative Spectrum Sensing(CSS) and Fine And Fast Sensing Algorithm(FAF),STCSS algorithm enhances the detection probability and reduces energy consumption and overhead of communication.

Key words: cooperative spectrum sensing, Wireless Cognitive Network(WCN), energy consumption, detection probability, communication cost

摘要： 在无线认知网络中,常规协作频谱感知算法用于增强频谱感知的准确性,但是该算法增加了通信成本以及认知用户的能量消耗。为此,提出一种选择触发协作频谱感知算法(STCSS)。该算法基于当前频谱感知能量阈值判定是否触发二次协作频谱感知,使得协作频谱感知仅在必要时被触发从而降低能量消耗与通信成本。仿真结果表明,对比协作频谱感知算法与精细快速感知算法,STCSS算法可提高检测概率,减少能量消耗以及通信成本。

关键词: 协作频谱感知, 无线认知网络, 能量消耗, 检测概率, 通信成本

CLC Number:

TP393.17

PENG Yi,CUI Ziru,CHEN Changkai. Selectively Triggered Cooperative Spectrum Sensing in Wireless Cognitive Network[J]. Computer Engineering, doi: 10.3969/j.issn.1000-3428.2017.03.016.

彭艺,崔自如,陈昌凯. 无线认知网络中的选择触发协作频谱感知[J]. 计算机工程, doi: 10.3969/j.issn.1000-3428.2017.03.016.

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References

参考文献［1］李映雪.认知无线电中的频谱感知技术研究［D］.北京:北京邮电大学,2013. ［2］Ping Yang,Yue Xiao.An Improved Matched-filter Based Detection Algorithm for Space-time Shift Keying Systems［J］.IEEE Signal Processing Letters,2012,19(5):271-274. ［3］Flury M.Synchronization for Impulse-radio UWB with Energy-detectionand Multi-user Interference:Algorithms and Application to IEEE 802.15.4a［J］.IEEE Transactions on Signal Processing,2011,59(11):5458-5472. ［4］Yang Mingchuan,Li Yuan.Cyclostationary Feature Detection Based Spectrum Sensing Algorithm Under Complicated Electromagnetic Environment in Cognitive Radio Networks［J］.China Communications,2015,12(9):35-44. ［5］Huang Xinlin,Wang Gang,Hu Fei,et al.Multitask Spectrum Sensing in Cognitive Radio Network via Spatiotemporal Data Mining［J］.IEEE Transactions on Vehicular Technology,2013,62(3):809-823. ［6］李转,任旭虎.基于信任度函数的认知无线电频谱感知算法研究［J］.通信与网络,2012,38(6):108-114. ［7］胡晓宁,仵国锋,胡捍英.认知无线电系统协作频谱感知机制优化［J］.计算机工程,2011,37(18):68-70. ［8］Peh E C Y,Liang Y C,Guan Y L,et al.Cooperative Spectrum Sensing in Cognitive Radio Networks with Weighted Decision Fusion Schemes［J］.IEEE Vehicular Technology Conference,2010,9(12):1-5. ［9］刘仕奇,陈崇谦,李海宏,等.基于双门限能量检测的认知无线电协作频谱感知［J］.电波科学学报,2013,28(3):420-424. ［10］邹卫霞,丁奇,周正,等.基于特征值极限分布的双门限频谱感知算法［J］.系统工程与电子技术,2012,34(3):588-591. ［11］Wang Haijun,Su Xin.Cooperative Spectrum Sensing Algorithms Based on Correlation Matrix in Cognitive Radio Networks［J］.Information Technology Journal,2013,12(6):1239-124. ［12］李明源,李鸥,孙武剑.基于噪声不确定性的双门限协作频谱感知算法［J］.计算机工程,2014,40(4):81-86. ［13］杨明极,吴琼.信噪比比较的协作频谱感知算法［J］.哈尔滨理工大学学报,2013,18(2):105-108. ［14］童莉.基于无线传感器能量消耗模型与均衡机制研究［D］.北京:北方工业大学,2015. ［15］马恒.认知无线电中频谱检测技术研究［J］.无线电工程,2014,44(3):77-80. ［16］张阳.基于频谱感知的自适应跳频抗干扰通信系统的仿真研究［D］.成都:电子科技大学,2014. 编辑刘冰

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