Ensemble Regression for 1-Bit Channel Estimation
- Resource Type
- Conference
- Authors
- Elsheikh, Ahmed; Ibrahim, Ahmed S.; Ismail, Mahmoud H.
- Source
- 2022 5th International Conference on Communications, Signal Processing, and their Applications (ICCSPA) Communications, Signal Processing, and their Applications (ICCSPA), 2022 5th International Conference on. :1-5 Dec, 2022
- Subject
- Communication, Networking and Broadcast Technologies
Computing and Processing
Fields, Waves and Electromagnetics
Robotics and Control Systems
Signal Processing and Analysis
Training
Adaptation models
Power demand
Computational modeling
Channel estimation
Signal processing algorithms
Signal processing
Analog-to-digital converters
Ensemble Regression
- Language
- ISSN
- 2767-7702
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.