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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Vydané v:Sensors (Basel, Switzerland) Ročník 19; číslo 15; s. 3368
Hlavní autori: Hu, Rui, Tong, Jun, Xi, Jiangtao, Guo, Qinghua, Yu, Yanguang
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Switzerland MDPI AG 31.07.2019
MDPI
Predmet:
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
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Popis
Shrnutí: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.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:1424-8220
1424-8220
DOI:10.3390/s19153368