TY - GEN
T1 - Learning a Low-Complexity Channel Estimator for One-Bit Quantization
AU - Fesl, Benedikt
AU - Koller, Michael
AU - Turan, Nurettin
AU - Utschick, Wolfgang
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/11/1
Y1 - 2020/11/1
N2 - A low-complexity convolutional neural network (CNN) channel estimator has been proposed recently, which was designed based on assumptions on the underlying channel model. In this work, we investigate how one-bit quantized observations affect this CNN estimator. In contrast to many other approaches, we propose a technique to obtain only one CNN estimator for a whole range of signal-to-noise ratio (SNR) values. We compare the performance of this estimator with a linear minimum mean square error (LMMSE) estimator based on the Bussgang decomposition and also with a state-of-the-art maximum a posteriori (MAP) approach, which exploits an approximate sparsity of the channels.
AB - A low-complexity convolutional neural network (CNN) channel estimator has been proposed recently, which was designed based on assumptions on the underlying channel model. In this work, we investigate how one-bit quantized observations affect this CNN estimator. In contrast to many other approaches, we propose a technique to obtain only one CNN estimator for a whole range of signal-to-noise ratio (SNR) values. We compare the performance of this estimator with a linear minimum mean square error (LMMSE) estimator based on the Bussgang decomposition and also with a state-of-the-art maximum a posteriori (MAP) approach, which exploits an approximate sparsity of the channels.
KW - channel estimation
KW - machine learning
KW - one-bit quantization
KW - spatial channel model
UR - http://www.scopus.com/inward/record.url?scp=85106669916&partnerID=8YFLogxK
U2 - 10.1109/IEEECONF51394.2020.9443563
DO - 10.1109/IEEECONF51394.2020.9443563
M3 - Conference contribution
AN - SCOPUS:85106669916
T3 - Conference Record - Asilomar Conference on Signals, Systems and Computers
SP - 393
EP - 397
BT - Conference Record of the 54th Asilomar Conference on Signals, Systems and Computers, ACSSC 2020
A2 - Matthews, Michael B.
PB - IEEE Computer Society
T2 - 54th Asilomar Conference on Signals, Systems and Computers, ACSSC 2020
Y2 - 1 November 2020 through 5 November 2020
ER -