Electronic Science and Technology ›› 2019, Vol. 32 ›› Issue (10): 13-16.doi: 10.16180/j.cnki.issn1007-7820.2019.10.003

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Sparse Adaptive Compressed Sensing Channel Estimation in Millimeter Wave MIMO Systems

WANG Fengling1,WU Yun1,ZHI Jia2   

  1. 1. College of Information Science and Technology,DonghuaUniversity,Shanghai 201620,China
    2. Shanghai Academy of Spaceflight Technology,Shanghai 201109,China
  • Received:2018-10-11 Online:2019-10-15 Published:2019-10-29
  • Supported by:
    National Natural Science Foundation of China(61671143)


With the sparse characteristics of millimeter-wave MIMO systems, channel estimation can be transformed to the problem of sparse signal reconstruction. When solving the problem of millimeter-wave MIMO sparse channel estimation, the traditional OMP method requires the signal sparsity as a priori information, which is difficult to meet in practical systems. The StOMP algorithm was introduced in this paper. The threshold was determined according to the sparse prior information known by the signal. Combined with the dynamic threshold adjustment, a new StOMP-D algorithm was proposed to realize the sparse adaptive millimeter-wave MIMO channel estimation. The simulation results showed that compared with the traditional LS method, the performance of the proposed algorithm was significantly improved, and the performance of the OMP method with known sparsity was very close. It had obvious advantages when the sparsity was unknown.

Key words: millimeter-wave, MIMO, compressedcensing, sparseadaptive, angledomain, greedy algorithm

CLC Number: 

  • TN928