A Low Rank Channel Estimation Scheme in Massive Multiple-Input Multiple-Output
Aiming at the problem of computational complexity of channel estimation, this paper proposes a low-complexity block matching pursuit (BMP) algorithm based on antenna grouping and block sparsity for frequency division duplex (FDD) massive Multiple-input Multiple-output orthogonal frequency division m...
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MDPI AG
2018-10-01
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| Series: | Symmetry |
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| Online Access: | http://www.mdpi.com/2073-8994/10/10/507 |
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doaj-7b0bd5e5031447cfb76f3a3323cc37ad2020-11-24T21:07:28ZengMDPI AGSymmetry2073-89942018-10-01101050710.3390/sym10100507sym10100507A Low Rank Channel Estimation Scheme in Massive Multiple-Input Multiple-OutputWaleed Shahjehan0Syed Waqar Shah1Jaime Lloret2Antonio Leon3Department of Electrical Engineering, University of Engineering & Technology, Peshawar 814 KPK, PakistanDepartment of Electrical Engineering, University of Engineering & Technology, Peshawar 814 KPK, PakistanIntegrated Management Coastal Research Institute, Universitat Politecnica de Valencia, C/Paranimf n° 1, Gandia, 46730 Valencia, SpainDepartment of Communications, Universitat Politecnica de Valencia, Camino Vera s/n, 46022 Valencia, SpainAiming at the problem of computational complexity of channel estimation, this paper proposes a low-complexity block matching pursuit (BMP) algorithm based on antenna grouping and block sparsity for frequency division duplex (FDD) massive Multiple-input Multiple-output orthogonal frequency division multiplexing (OFDM) systems. The system coherence time may be exceeded as a result of time consumption when adopting an orthogonal pilot symbol in the time domain. To solve this problem, an antenna grouping transmission scheme is proposed to reduce the total channel estimation time by sacrificing the observed data length. The simulation results show that the proposed BMP algorithm has good anti-noise performance, and it can accurately determine the non-zero position of the sparse vector and adaptively determine the sparsity of the channel, which effectively translates to improved channel estimation performance and better overall system performance than the existing algorithms.http://www.mdpi.com/2073-8994/10/10/507massive MIMOcomputational complexitychannel estimationblock sparsityfrequency division duplexing |
| collection |
DOAJ |
| language |
English |
| format |
Article |
| sources |
DOAJ |
| author |
Waleed Shahjehan Syed Waqar Shah Jaime Lloret Antonio Leon |
| spellingShingle |
Waleed Shahjehan Syed Waqar Shah Jaime Lloret Antonio Leon A Low Rank Channel Estimation Scheme in Massive Multiple-Input Multiple-Output Symmetry massive MIMO computational complexity channel estimation block sparsity frequency division duplexing |
| author_facet |
Waleed Shahjehan Syed Waqar Shah Jaime Lloret Antonio Leon |
| author_sort |
Waleed Shahjehan |
| title |
A Low Rank Channel Estimation Scheme in Massive Multiple-Input Multiple-Output |
| title_short |
A Low Rank Channel Estimation Scheme in Massive Multiple-Input Multiple-Output |
| title_full |
A Low Rank Channel Estimation Scheme in Massive Multiple-Input Multiple-Output |
| title_fullStr |
A Low Rank Channel Estimation Scheme in Massive Multiple-Input Multiple-Output |
| title_full_unstemmed |
A Low Rank Channel Estimation Scheme in Massive Multiple-Input Multiple-Output |
| title_sort |
low rank channel estimation scheme in massive multiple-input multiple-output |
| publisher |
MDPI AG |
| series |
Symmetry |
| issn |
2073-8994 |
| publishDate |
2018-10-01 |
| description |
Aiming at the problem of computational complexity of channel estimation, this paper proposes a low-complexity block matching pursuit (BMP) algorithm based on antenna grouping and block sparsity for frequency division duplex (FDD) massive Multiple-input Multiple-output orthogonal frequency division multiplexing (OFDM) systems. The system coherence time may be exceeded as a result of time consumption when adopting an orthogonal pilot symbol in the time domain. To solve this problem, an antenna grouping transmission scheme is proposed to reduce the total channel estimation time by sacrificing the observed data length. The simulation results show that the proposed BMP algorithm has good anti-noise performance, and it can accurately determine the non-zero position of the sparse vector and adaptively determine the sparsity of the channel, which effectively translates to improved channel estimation performance and better overall system performance than the existing algorithms. |
| topic |
massive MIMO computational complexity channel estimation block sparsity frequency division duplexing |
| url |
http://www.mdpi.com/2073-8994/10/10/507 |
| work_keys_str_mv |
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1716762813895016448 |