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...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-07-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/19/15/3368 |
| _version_ | 1798039677036396544 |
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| author | Rui Hu Jun Tong Jiangtao Xi Qinghua Guo Yanguang Yu |
| author_facet | Rui Hu Jun Tong Jiangtao Xi Qinghua Guo Yanguang Yu |
| author_sort | Rui Hu |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-11T21:57:08Z |
| format | Article |
| id | doaj.art-dba168dc79684ac89969f023c246a43a |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T21:57:08Z |
| publishDate | 2019-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-dba168dc79684ac89969f023c246a43a2022-12-22T04:01:04ZengMDPI AGSensors1424-82202019-07-011915336810.3390/s19153368s19153368Channel Covariance Matrix Estimation via Dimension Reduction for Hybrid MIMO MmWave Communication SystemsRui Hu0Jun Tong1Jiangtao Xi2Qinghua Guo3Yanguang Yu4School of Electrical, Computer and Telecommunications Engineering, University of Wollongong, Wollongong, NSW 2522, AustraliaSchool of Electrical, Computer and Telecommunications Engineering, University of Wollongong, Wollongong, NSW 2522, AustraliaSchool of Electrical, Computer and Telecommunications Engineering, University of Wollongong, Wollongong, NSW 2522, AustraliaSchool of Electrical, Computer and Telecommunications Engineering, University of Wollongong, Wollongong, NSW 2522, AustraliaSchool of Electrical, Computer and Telecommunications Engineering, University of Wollongong, Wollongong, NSW 2522, AustraliaHybrid 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.https://www.mdpi.com/1424-8220/19/15/3368millimeter wave communicationshybrid MIMOchannel covariance estimation |
| spellingShingle | Rui Hu Jun Tong Jiangtao Xi Qinghua Guo Yanguang Yu Channel Covariance Matrix Estimation via Dimension Reduction for Hybrid MIMO MmWave Communication Systems Sensors millimeter wave communications hybrid MIMO channel covariance estimation |
| title | Channel Covariance Matrix Estimation via Dimension Reduction for Hybrid MIMO MmWave Communication Systems |
| title_full | Channel Covariance Matrix Estimation via Dimension Reduction for Hybrid MIMO MmWave Communication Systems |
| title_fullStr | Channel Covariance Matrix Estimation via Dimension Reduction for Hybrid MIMO MmWave Communication Systems |
| title_full_unstemmed | Channel Covariance Matrix Estimation via Dimension Reduction for Hybrid MIMO MmWave Communication Systems |
| title_short | Channel Covariance Matrix Estimation via Dimension Reduction for Hybrid MIMO MmWave Communication Systems |
| title_sort | channel covariance matrix estimation via dimension reduction for hybrid mimo mmwave communication systems |
| topic | millimeter wave communications hybrid MIMO channel covariance estimation |
| url | https://www.mdpi.com/1424-8220/19/15/3368 |
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