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多速率DS-CDMA系统中基于Kalman滤波的盲多用户检测 被引量:2

Blind Multiuser Detection in Multirate DS-CDMA System Based on Kalman Filter
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摘要 在讨论可变扩频增益多速率直接序列码分多址(DS-CDMA)系统信号模型的同时,为了保证该检测器能适用于多径衰落信道环境,提出了基于Kalman滤波的盲多速率多用户检测器,并给出了Kalman滤波算法的实现步骤与最大值合并过程。仿真结果表明,与现有的一些盲自适应多用户检测器相比,本文提出的检测器在多速率环境下具有更为好的抗多址干扰、抗多径干扰能力,且能更快地收敛。 On discussing the signal model of variable spread spectrum gain muhirate DS-CDMA system, this paper proposes a multirate blind multiuser channel estimation algorithm based on Kalman filter to guarantee it to adapt to multi-path fading channel. The implementation steps of the proposed algorithm and combination produce of maximum value are described in detail. Simulation results prove that, compared with other proposed detectors in multirate system, the proposed algorithm can attain better anti-multi-address interference, anti-multi-path interference performance, and faster convergence .
出处 《计算机与现代化》 2009年第4期81-84,共4页 Computer and Modernization
关键词 多用户检测 KALMAN滤波 DS-CDMA multiuser detection blind Kalman filter DS-CDMA
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  • 1Kapoor S, Gollamudi S, Nagaraj S. Adaptive multiuser detection and beamforming for interference suppression in CDMA mobile radio systems [J]. IEEE Trans. on Vehicular Technology, 1999,48(5): 1341 - 1355.
  • 2Honig M, Madhow U, Verdu S. Blind adaptive multiuser detection [J]. IEEE Trans. on Information Theory, 1995, 41(4):944-960.
  • 3Roy S. Subspace blind adaptive multiuser detection for CDMA[J]. IEEE Trans. on Communications, 2000, 48(1): 169 - 175.
  • 4Lim T J, Ma Y. The Kalman filter as the optimum linear minimum mean squared error multiuser CDMA detector [J].IEEE Trans. on Information Theory, 2000, 46(7): 2561 - 2566.
  • 5Lim T J, Rasmussen L K. Adaptive symbol and parameter estimation in asynchronous multiuser CDMA detectors [J]. IEEE Trans. on Communications, 1997, 45(1): 213 - 220.
  • 6Madhow U, Honig M. MMSE interference suppression for direct-sequence spread-spectrum CDMA [J]. IEEE Trans. on Communications, 1994, 42(4): 3178 - 3188.
  • 7Zhang X D, Wei W. Blind adaptive multiuser detection based on Kalman filtering [J]. IEEE Trans. on Signal Processing, 2002,50(1): 87 - 95.
  • 8Kapoor S, Gollamudi S, Nagaraj S. Adaptive multiuser detection and beamforming for interference suppression in CDMA mobile radio systems[J]. IEEE Trans. on Vehicular Technology, 1999, 48(5): 1341-1355.
  • 9Honig M, Madhow U, Verdu S. Blind adaptive multiuser detection [J]. IEEE Trans. on Information Theory, 1995, 41 (4): 944-960.
  • 10Lim T J, Ma Y. The Kalman filter as the optimum linear minimum mean squared error multiuser CDMA detector [J]. IEEE Trans. Information Theory, 2000, 46(7): 2561-2566.

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  • 1唐涛,黄永梅.改进的EKF算法在目标跟踪中的运用[J].光电工程,2005,32(9):16-18. 被引量:14
  • 2肖艳军,李建勋,薛阳.Outlier Rejecting Multirate Model for State Estimation[J].Journal of Shanghai Jiaotong university(Science),2006,11(1):18-21. 被引量:1
  • 3Bizup D F,Brandt-Pearce M.Comparison of IMM and robust filters in impulsive noise environments[J].IEEE Trans on Signals,Systems and Computers,2002,2:1792-1796.
  • 4Julier S J,Uhlmann J K.A new extension of the kalman filter to nonlinear systems[C].Proc.of Aerosense:the11th International Sumposium on Aerospace/Defence Sensing,Si-mulation and Controls,Orlando,Florida:SPIE Press,1997,306(8):182-193.
  • 5KalmanR E. A new approach to linear filtering and predic- tion problems[J]. Journal of Basic Engineering, 1960,82 (1) :35-45.
  • 6Ljung L. Asymptotic behavior of the extended Kalman filter as a parameter estimator for linear systems [ J 1. IEEE Transactions on Automatic Control, 1979,24( 1 ) :36-50.
  • 7Kerr T H. Streamlining measurement iteration for EKF tar- get tracking[J]. IEEE Transactions on Aerospace and E- lectronic Systems, 1991,27(2) :408-421.
  • 8Reece S. Nonlinear Kalman filtering with semi-parametric Biscay distribution[ J]. IEEE Transactions on Signal Pro- cessing, 2001,49 ( 11 ) :2445-2453.
  • 9Reece S. Qualitative Model-Based Multi-sensor Data Fu- sion: The Qualitative Kalman Filter [ M ]. University of Oxford, 1998 : 15-21.
  • 10赵凯,王爱平,吴刚.非高斯噪声下Kalman滤波熵理论算法研究[J].计算机技术与发展,2008,18(6):40-42. 被引量:2

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