Channel AoA estimation for massive MIMO systems using one-bit ADCs
Although massive multiple-input multiple-output (MIMO) can enhance the overall system performance significantly, it could suffer from high cost and power consumption issues due to using a large number of radio frequency (RF) chains. Two different approaches are commonly exploited to overcome these i...
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| Published in | Journal of communications and networks Vol. 20; no. 4; pp. 374 - 382 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Seoul
Editorial Department of Journal of Communications and Networks
01.08.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 한국통신학회 |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1229-2370 1976-5541 |
| DOI | 10.1109/JCN.2018.000053 |
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| Abstract | Although massive multiple-input multiple-output (MIMO) can enhance the overall system performance significantly, it could suffer from high cost and power consumption issues due to using a large number of radio frequency (RF) chains. Two different approaches are commonly exploited to overcome these issues. The first approach is using hybrid beamforming, which consists of analog and digital beamforming, to reduce the total number of RF chains. The second approach is adopting low-resolution analog-todigital converters (ADCs) for each RF chain. For both approaches, channel estimation becomes a difficult task. This paper addresses the problem of channel angle of arrival (AoA) estimation in massive MIMO using both hybrid beamforming and one-bit magnitude-aided (OMA) ADCs. An iterative algorithm is developed to estimate the channel AoA, and the appropriate threshold per iteration is analyzed. Numerical results show that the proposed technique can achieve sufficient AoA estimation performance with practical values of the signal-to-noise ratio (SNR). |
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| AbstractList | Although massive multiple-input multiple-output (MIMO) can enhance the overall system performance significantly, it could suffer from high cost and power consumption issues due to using a large number of radio frequency (RF) chains. Two different approaches are commonly exploited to overcome these issues. The first approach is using hybrid beamforming, which consists of analog and digital beamforming, to reduce the total number of RF chains. The second approach is adopting low-resolution analog-todigital converters (ADCs) for each RF chain. For both approaches, channel estimation becomes a difficult task. This paper addresses the problem of channel angle of arrival (AoA) estimation in massive MIMO using both hybrid beamforming and one-bit magnitudeaided (OMA) ADCs. An iterative algorithm is developed to estimate the channel AoA, and the appropriate threshold per iteration is analyzed. Numerical results show that the proposed technique can achieve sufficient AoA estimation performance with practical values of the signal-to-noise ratio (SNR). Although massive multiple-input multiple-output(MIMO) can enhance the overall system performance significantly,it could suffer from high cost and power consumption issues due tousing a large number of radio frequency (RF) chains. Two differentapproaches are commonly exploited to overcome these issues. The first approach is using hybrid beamforming, which consists ofanalog and digital beamforming, to reduce the total number of RFchains. The second approach is adopting low-resolution analog-todigitalconverters (ADCs) for each RF chain. For both approaches,channel estimation becomes a difficult task. This paper addressesthe problem of channel angle of arrival (AoA) estimation in massiveMIMO using both hybrid beamforming and one-bit magnitudeaided(OMA) ADCs. An iterative algorithm is developed to estimatethe channel AoA, and the appropriate threshold per iterationis analyzed. Numerical results show that the proposed techniquecan achieve sufficient AoA estimation performance with practicalvalues of the signal-to-noise ratio (SNR). KCI Citation Count: 2 Although massive multiple-input multiple-output (MIMO) can enhance the overall system performance significantly, it could suffer from high cost and power consumption issues due to using a large number of radio frequency (RF) chains. Two different approaches are commonly exploited to overcome these issues. The first approach is using hybrid beamforming, which consists of analog and digital beamforming, to reduce the total number of RF chains. The second approach is adopting low-resolution analog-todigital converters (ADCs) for each RF chain. For both approaches, channel estimation becomes a difficult task. This paper addresses the problem of channel angle of arrival (AoA) estimation in massive MIMO using both hybrid beamforming and one-bit magnitude-aided (OMA) ADCs. An iterative algorithm is developed to estimate the channel AoA, and the appropriate threshold per iteration is analyzed. Numerical results show that the proposed technique can achieve sufficient AoA estimation performance with practical values of the signal-to-noise ratio (SNR). |
| Author | Hwanjin Kim Junil Choi |
| Author_xml | – sequence: 1 givenname: Hwanjin surname: Kim fullname: Kim, Hwanjin organization: Department of Electrical Engineering, Pohang University of Science and Technology – sequence: 2 givenname: Junil surname: Choi fullname: Choi, Junil organization: Department of Electrical Engineering, Pohang University of Science and Technology |
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| Snippet | Although massive multiple-input multiple-output (MIMO) can enhance the overall system performance significantly, it could suffer from high cost and power... Although massive multiple-input multiple-output(MIMO) can enhance the overall system performance significantly,it could suffer from high cost and power... |
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| SubjectTerms | Angle of arrival Array signal processing Beamforming Chains channel angle of arrival (AoA) estimation Channel estimation Converters Estimation hybrid beamforming Iterative algorithms Iterative methods massive multiple-input multiple-output (MIMO) MIMO (control systems) MIMO communication one-bit magnitude-aidedanalog-to-digital converters (ADCs) Power consumption Power demand Quantization (signal) Radio frequency Signal to noise ratio 전자/정보통신공학 |
| Title | Channel AoA estimation for massive MIMO systems using one-bit ADCs |
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