摘要
为了探索无线信道的传播特征并建立相应的无线信道模型,针对无线信道的"指纹"特征建模及场景识别问题,提出基于无迹卡尔曼神经网络的信道建模方法.首先采用霍特林变换对信道传播数据进行预处理,实现数据从复数域到实数域的转换,然后利用主元分析对数据进行降维,得到降维数据后,采用无迹卡尔曼神经网络进行无线信道"指纹"特征建模,最后根据模型的输出值建立无线信道的评价指标,对测量的信道数据进行场景划分以及场景识别.仿真结果表明:无迹卡尔曼神经网络所建信道模型可准确对无线信道进行类别划分和场景识别.
In order to explore the propagative characteristics of wireless channel and establish corresponding wireless channel model,in this paper, in view of the ＂fingerprint＂ characteristics of wireless channel modeling and recognition problem for the scene, we put forward the modeling method of wireless channel which is based on Unscented Kalman Filter Neural Network（UKFNN）. Firstly, we use Karhunen-Loeve（K-L） to deal with channel transmission data,to realize the change of data from complex domain to real domain, and then use Principal Component Analysis（PCA） for data dimension reduction, after getting the dimension-reduced data, UKFNN is applied to build the characteristic model of wireless channel. Lastly, we establish the evaluation index of wireless channel according to the model-based output, and use the evaluation index to classify and recognize different scenes. The simulation results show that the model based on UKFNN can classify and recognize different scenes accurately.
出处
《数学的实践与认识》
北大核心
2016年第14期225-234,共10页
Mathematics in Practice and Theory
基金
国家自然科学基金(51375520
51374268
51404051
61174015)
重庆市自然科学基金重点项目(cstc2012jjB40006)
重庆市重大应用技术开发项目(cstc2013yykfC0034)
重庆市优秀人才科技训练计划(cstc2013kjrcqnrc40008)
重庆市高校创新团队项目(KJTD201324)
重庆高校优秀成果转化项目(KJZH14218)
重庆市教委科学技术研究项目(KJ1401301)
关键词
无线信道
霍特林变换
主元分析
无迹卡尔曼神经网络
wireless channel
karhunen-loeve
principal component analysis
unscented kalman filter neural network
