Blind Separation of PCMA Signals Based on GA-IPF
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    Abstract:

    Aiming at the blind separation problem of non-cooperative receiving PCMA signals, Improved Particle Filtering based on Genetic Algorithm (GA-IPF) is proposed. Based on the particle filter algorithm framework, the algorithm establishes multiple state distributions to approximate the true posterior probability density. At the same time, genetic algorithm is introduced instead of resampling to generate new particles, which increases particle diversity and avoids particle depletion during resampling. Simulation results show that when the carrier-to-noise ratio is greater than 9 dB, the separation accuracy is over 95%, compared with QRD-M Gibbs and other algorithms, the signal acquisition capability of the algorithm is improved by 4 dB, and the algorithm complexity is reduced by nearly 60%.

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张珊珊,陈刚,鲁华祥,邓琪.基于GA-IPF的PCMA信号盲分离算法.计算机系统应用,2019,28(9):196-202

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History
  • Received:March 05,2019
  • Revised:April 02,2019
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  • Online: September 09,2019
  • Published: September 15,2019
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