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Acquisition of channel state information for mmWave massive MIMO: traditional and machine learning-based approaches

Abstract

The accuracy of channel state information (CSI) acquisition directly affects the performance of millimeter wave (mmWave) communications. In this article, we provide an overview on CSI acquisition, including beam training and channel estimation for mmWave massive multiple-input multiple-output systems. The beam training can avoid the estimation of a high-dimension channel matrix, while the channel estimation can flexibly exploit advanced signal processing techniques. In addition to introducing the traditional and machine learning-based approaches in this article, we also compare different approaches in terms of spectral efficiency, computational complexity, and overhead.

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Acknowledgements

This work was supported by National Natural Science Foundation of China (Grant Nos. 62071116, 61960206005).

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Correspondence to Chenhao Qi or Geoffrey Ye Li.

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Qi, C., Dong, P., Ma, W. et al. Acquisition of channel state information for mmWave massive MIMO: traditional and machine learning-based approaches. Sci. China Inf. Sci. 64, 181301 (2021). https://doi.org/10.1007/s11432-021-3247-2

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  • DOI: https://doi.org/10.1007/s11432-021-3247-2

Keywords

  • beam training
  • channel estimation
  • machine learning
  • massive MIMO
  • millimeter wave (mmWave) communications