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

Hybrid massive MIMO structures with lower hardware complexity and power consumption have been considered as potential candidates for millimeter wave (mmWave) communications. Channel covariance information can be used for designing transmitter precoders, receiver combiners, channel estimators, etc. H...

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Veröffentlicht in:Sensors (Basel, Switzerland) Jg. 19; H. 15; S. 3368
Hauptverfasser: Hu, Rui, Tong, Jun, Xi, Jiangtao, Guo, Qinghua, Yu, Yanguang
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Switzerland MDPI AG 31.07.2019
MDPI
Schlagworte:
Arrays
channel covariance estimation
Communication
Decomposition
Design
Dictionaries
Economic models
Estimating techniques
hybrid MIMO
Information processing
millimeter wave communications
Transmitters
Canada
United States > US
millimeter wave communications
hybrid MIMO
channel covariance estimation
ISSN:1424-8220, 1424-8220
Online-Zugang:Volltext
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Zusammenfassung:Hybrid massive MIMO structures with lower hardware complexity and power consumption have been considered as potential candidates 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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ISSN:1424-8220
1424-8220
DOI:10.3390/s19153368