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 inJournal of communications and networks Vol. 20; no. 4; pp. 374 - 382
Main Authors Kim, Hwanjin, Choi, Junil
Format Journal Article
LanguageEnglish
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 AccessGet full text
ISSN1229-2370
1976-5541
DOI10.1109/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).
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
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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...
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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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