Least Squares Constant Modulus Blind Adaptive Beamforming with Sparse Constraint

DOI Web Site 参考文献18件
  • LI Jun
    College of Physical Science and Technology, Central China Normal University (CCNU)
  • XU Hongbo
    College of Physical Science and Technology, Central China Normal University (CCNU)
  • XIA Hongxing
    College of Physical Science and Technology, Central China Normal University (CCNU)
  • LIU Fan
    College of Physical Science and Technology, Central China Normal University (CCNU)
  • LI Bo
    Department of Electronic Science & Technology, Huazhong University of Science and Technology (HUST)

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Beamforming with sparse constraint has shown significant performance improvement. In this letter, a least squares constant modulus blind adaptive beamforming with sparse constraint is proposed. Simulation results indicate that the proposed approach exhibits better performance than the well-known least squares constant modulus algorithm (LSCMA).

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