Ensemble Regression for 1-Bit Channel Estimation

Employing 1-bit analog-to-digital converters (ADCs) is necessary for large-bandwidth massive multiple-antenna systems to maintain reasonable power consumption. However, conducting channel estimation with such 1-bit ADCs and with low complexity is a challenging task. In this paper, we propose to empl...

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Bibliographic Details
Main Authors: Elsheikh, Ahmed, Ibrahim, Ahmed S., Ismail, Mahmoud H.
Format: Conference Proceeding
Language:English
Subjects:
Adaptation models
Analog-to-digital converters
Channel estimation
Computational modeling
Ensemble Regression
Power demand
Signal processing
Signal processing algorithms
Training
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Summary:Employing 1-bit analog-to-digital converters (ADCs) is necessary for large-bandwidth massive multiple-antenna systems to maintain reasonable power consumption. However, conducting channel estimation with such 1-bit ADCs and with low complexity is a challenging task. In this paper, we propose to employ an Ensemble Regression (ER) model to conduct low-complexity and high-quality channel estimation. The amount of proposed computations are less than 3% of that proposed by similar deep learning (DL) methods, and in turn requires approximately 4% of the power consumed in computations while maintaining the same level of performance.
ISSN:2767-7702
DOI:10.1109/ICCSPA55860.2022.10018988