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On matrix completion-based channel estimators for massive MIMO systems

Journal Article


Abstract


  • Large-scale symmetric arrays such as uniform linear arrays (ULA) have been widely used in wireless communications for improving spectrum efficiency and reliability. Channel state information (CSI) is critical for optimizing massive multiple-input multiple-output(MIMO)-based wireless communication systems. The acquisition of CSI for massive MIMO faces challenges such as training shortage and high computational complexity. For millimeter wave MIMO systems, the low-rankness of the channel can be utilized to address the challenge of training shortage. In this paper, we compared several channel estimation schemes based on matrix completion (MC) for symmetrical arrays. Performance and computational complexity are discussed and compared. By comparing the performance in different scenarios, we concluded that the generalized conditional gradient with alternating minimization (GCG-Alt) estimator provided a low-cost, robust solution, while the alternating direction method of multipliers (ADMM)-based hybrid methods achieved the best performance when the array response was perfectly known.

Authors


  •   Ding, Mingjun (external author)
  •   Yang, Xiaodong (external author)
  •   Hu, Rui (external author)
  •   Xiao, Zhitao (external author)
  •   Tong, Jun
  •   Xi, Jiangtao

Publication Date


  • 2019

Citation


  • M. Ding, X. Yang, R. Hu, Z. Xiao, J. Tong & J. Xi, "On matrix completion-based channel estimators for massive MIMO systems," Symmetry, vol. 11, (11) pp. 1377-1-1377-18, 2019.

Scopus Eid


  • 2-s2.0-85075506454

Start Page


  • 1377-1

End Page


  • 1377-18

Volume


  • 11

Issue


  • 11

Place Of Publication


  • Switzerland

Abstract


  • Large-scale symmetric arrays such as uniform linear arrays (ULA) have been widely used in wireless communications for improving spectrum efficiency and reliability. Channel state information (CSI) is critical for optimizing massive multiple-input multiple-output(MIMO)-based wireless communication systems. The acquisition of CSI for massive MIMO faces challenges such as training shortage and high computational complexity. For millimeter wave MIMO systems, the low-rankness of the channel can be utilized to address the challenge of training shortage. In this paper, we compared several channel estimation schemes based on matrix completion (MC) for symmetrical arrays. Performance and computational complexity are discussed and compared. By comparing the performance in different scenarios, we concluded that the generalized conditional gradient with alternating minimization (GCG-Alt) estimator provided a low-cost, robust solution, while the alternating direction method of multipliers (ADMM)-based hybrid methods achieved the best performance when the array response was perfectly known.

Authors


  •   Ding, Mingjun (external author)
  •   Yang, Xiaodong (external author)
  •   Hu, Rui (external author)
  •   Xiao, Zhitao (external author)
  •   Tong, Jun
  •   Xi, Jiangtao

Publication Date


  • 2019

Citation


  • M. Ding, X. Yang, R. Hu, Z. Xiao, J. Tong & J. Xi, "On matrix completion-based channel estimators for massive MIMO systems," Symmetry, vol. 11, (11) pp. 1377-1-1377-18, 2019.

Scopus Eid


  • 2-s2.0-85075506454

Start Page


  • 1377-1

End Page


  • 1377-18

Volume


  • 11

Issue


  • 11

Place Of Publication


  • Switzerland