空军工程大学学报（自然科学版）2017，Vol.18Issue(4)：73-78,6.DOI:10.3969/j.issn.1009-3516.2017.04.013
认知无线传感器网络新型SVM频谱感知策略
A New SVM Spectrum Sensing Strategy Based on Cognitive Wireless Sensor Networks
摘要
Abstract
This paper explains the feasibility of applying support vector machine based on cognitive wireless sensor network.Under condition of the wireless environment of low SNR and complex noise, aimed at the problems that single identification method fails to reach relatively accurate results, based on Hidden Markov Model, HMM, this paper optimizes the traditional spectrum sensing algorithm of SVM by adopting multiple classifiers ensemble to reduce identification error and strengthen identification robustness, and by adopting least square method to turn linear inequality constraints into linear constraints so as to get optimal hyperplane to distinguish primary signal from noise and then decide primary user state.Finally, its performance is compared with traditional energy detecting algorithm.The simulation results show that the spectrum sensing performance based on SVM is closer to the theoretical value, is more reliable and accurate than that of the energy detection, the error rate is 1.6%, the detection probability is 18 percent higher than the energy detection under condition of low SNR, and has more favorable detection performance and robustness.关键词
认知无线传感器网络/频谱感知/支持向量机/隐马尔可夫模型/能量检测Key words
cognitive wireless sensor networks/spectrum sensing/support vector machine/Hidden Markov model/energy detection分类
信息技术与安全科学引用本文复制引用
王晓东,陈长兴,任晓岳,林兴..认知无线传感器网络新型SVM频谱感知策略[J].空军工程大学学报（自然科学版）,2017,18(4):73-78,6.基金项目
陕西省自然科学基础研究计划(2014JM8344) （2014JM8344）
