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arXiv · 1905.03916

Channel Covariance Matrix Estimation via Dimension Reduction for Hybrid MIMO MmWave Communication Systems

Rui Hu·Jun Tong·Jiangtao Xi·Qinghua Guo·Yanguang Yu
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Abstract

Hybrid massive MIMO structures with lower hardware complexity and power consumption have been considered as a potential candidate for millimeter wave (mmWave) communications. Channel covariance information can be used for designing transmitter precoders, receiver combiners, channel estimators, etc. However, hybrid structures allow only a lower-dimensional signal to be observed, which adds difficulties for channel covariance matrix estimation. In this paper, we formulate the channel covariance estimation as a structured low-rank matrix sensing problem via Kronecker product expansion and use a low-complexity algorithm to solve this problem. Numerical results with uniform linear arrays (ULA) and uniform squared planar arrays (USPA) are provided to demonstrate the effectiveness of our proposed method.

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Rui Hu, Jun Tong, Jiangtao Xi, Qinghua Guo, Yanguang Yu. 2019-06-24. Channel Covariance Matrix Estimation via Dimension Reduction for Hybrid MIMO MmWave Communication Systems. https://arxiv.org/abs/1905.03916

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