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一种基于过采样的单通道MPSK信号盲分离算法

崔荣涛 李辉 万坚 戴旭初

崔荣涛, 李辉, 万坚, 戴旭初. 一种基于过采样的单通道MPSK信号盲分离算法[J]. 电子与信息学报, 2009, 31(3): 566-569. doi: 10.3724/SP.J.1146.2007.01792
引用本文: 崔荣涛, 李辉, 万坚, 戴旭初. 一种基于过采样的单通道MPSK信号盲分离算法[J]. 电子与信息学报, 2009, 31(3): 566-569. doi: 10.3724/SP.J.1146.2007.01792
Cui Rong-tao, Li Hui, Wan Jian, Dai Xu-chu. An Over-sampling Based Blind Separation Algorithm of Single Channel MPSK Signals[J]. Journal of Electronics & Information Technology, 2009, 31(3): 566-569. doi: 10.3724/SP.J.1146.2007.01792
Citation: Cui Rong-tao, Li Hui, Wan Jian, Dai Xu-chu. An Over-sampling Based Blind Separation Algorithm of Single Channel MPSK Signals[J]. Journal of Electronics & Information Technology, 2009, 31(3): 566-569. doi: 10.3724/SP.J.1146.2007.01792

一种基于过采样的单通道MPSK信号盲分离算法

doi: 10.3724/SP.J.1146.2007.01792

An Over-sampling Based Blind Separation Algorithm of Single Channel MPSK Signals

  • 摘要: 针对单通道接收两个MPSK混合信号的盲分离问题,该文提出了一种基于过采样的盲分离新算法。该算法基于最优贝叶斯估计准则,利用粒子滤波对发送的符号和一些参数进行序贯估计,从而实现了混合信号的分离。算法通过对接收信号的过采样,利用了更多的接收波形信息,有效地抑制了噪声的影响。仿真实验表明,新算法具有良好的误码率性能。该文同时还从极大似然的角度,对分离算法的性能进行了分析,给出了算法的误码率性能界。
  • Li Yuanqing, Amari S, Cichocki A, Daniel W C H, and XieShengli. Undetermined blind source separation based onSparse Representation[J].IEEE Trans. on Signal Processing.2006, 54(2):423-437[2]Theis F J, Lang E W, and Puntonet C G. A geometricalgorithm for overcomplete linear ICA[J].Neurocomputing.2004, 56:381-398[3]蔡权伟, 魏平, 肖先赐. 基于模型拟合的重叠信号分离方法[J].电子学报, 2005, 33(10): 1794-1798.[4]Heidari S and Nikias C L. Co-channel interference mitigationin the time-scale domain: the CIMTS algorithm[J].IEEETrans. on Signal Processing.1996, 44(9):2151-2162[5]Warner E S and Proudler I K. Single-channel blind signalseparation of filtered MPSK signals[J].IEEE Proceedings,Radar, Sonar and Navigation.2003, 150(6):396-402[6]Liu Kai, Li Hui, Dai Xuchu, and Xu Xiaodong. Single channelblind signal separation of cofrequency MPSK signals[C].Proceedings of International Conference on Communication,Internet and Information Technology (CIIT 2006), St.Thomas, USVI, USA, Nov. 2006: 42-46.[7]Arulampalam M S, Maskell S, Gordon N, and Clapp T. Atutorial on particle filters for online nonlinear/non-gaussianbayesian tracking[J].IEEE Trans. on Signal Processing.2002,50(2):174-188[8]Liu J S and Chen R. Sequential monte carlo methods fordynamic systems[J]. Journal of American StatisticalAssociation, 1998, 93(443): 1032-1043.[9]Forney G D. Maximum-likelihood sequence estimation ofdigital sequences in the presence of intersymbolinterference[J]. IEEE Trans. on Information Theory, 1972,IT-18(3): 363-378.
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出版历程
  • 收稿日期:  2007-11-20
  • 修回日期:  2008-04-28
  • 刊出日期:  2009-03-19

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