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一种N维数据块正交调制及其解调识别方法的研究
引用本文:杨发权,李赞,罗中良,李红艳,赫本建,高锐.一种N维数据块正交调制及其解调识别方法的研究[J].中山大学学报(自然科学版),2012,51(3):18-22.
作者姓名:杨发权  李赞  罗中良  李红艳  赫本建  高锐
作者单位:1. 西安电子科技大学综合业务网理论及关键技术国家重点实验室,陕西西安710071;佛山科技学院电子与信息工程学院,广东佛山528000
2. 西安电子科技大学综合业务网理论及关键技术国家重点实验室,陕西西安,710071
3. 惠州学院电子科学系,广东惠州,516007
基金项目:国家科技重大专项资助项目(2010ZX03006-002-04);国家自然科学基金资助项目(61072070);教育部博士学科点基金资助项目(20110203110011);ISN国家重点实验室自主课题资助项目(ISN1101002);高等学校学科创新引智计划资助项目(B08038);广东省自然科学基金资助项目(10151601501000005);惠州市科技计划资助项目(2010B020008011,2010B020008016)
摘    要: 提出一种N维数据块正交调制方法并对其调制解调识别方法进行研究。研究基于普通正交调制识别基础上,从接收信号聚类样品中提取基本特征矢量以估计数据块信号参数实现数据块解调,通过矩阵转换实现信号调制方式的识别,在高斯白噪声信道条件下访真结果表明该方法对N维数据块正交调制信号具有较好的识别性能。

关 键 词:N维数据块正交调制  聚累样品  解调  识别
收稿时间:2011-10-18;

One Block Orthogonal Modulations of N-dimensional and Its Method Research of Demodulation Identification
YA Faquan , LI Zan , LUO Zhongliang , LI Hongyan , HAO Benjian , GAO Rui.One Block Orthogonal Modulations of N-dimensional and Its Method Research of Demodulation Identification[J].Acta Scientiarum Naturalium Universitatis Sunyatseni,2012,51(3):18-22.
Authors:YA Faquan  LI Zan  LUO Zhongliang  LI Hongyan  HAO Benjian  GAO Rui
Institution:1(1.State Key Laboratory of Integrated Service Networks,Xidian University,Xian 710071,China; 2.School of Electronic and lnformation Engineering,Foshan University,Foshan 528000,China; 3.Department of Electronic Science,Huizhou University,Huizhou 516007,China)
Abstract:One method of N-dimensional block orthogonal was presented and the research of demodulation identification method was made.Based-on ordinary orthogonal modulation recognition,the research realized data block demodulation from the received signal samples extracted basic feature vector to estimate the signal parameters and achieved recognition of signal modulation through the matrix conversion,The simulations results under the conditions of an additive Gauss white noise channel,show that the method has a good performance of recognition to signal of N-dimensional block orthogonal modulation:
Keywords:block orthogonal modulations of N-dimensional  clustering example  demodulation  identification
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