Research on machine learning for channel estimation, especially neural network solutions
for wireless communications, is attracting significant current interest. This is because …

Least square (LS) channel estimation employed in various communications systems suffers
from performance degradation especially in low signal-to-noise ratio (SNR) regions. This is …

The growth of frequency bandwidths and applications with the forthcoming generations of
wireless networks will give rise to a multitude of wireless transmission scenarios, topologies …

For estimating the MIMO channels for both the uplink and the downlink, we used residual
deep neural network. The proposed residual deep neural network (ResNET) channel …

Improving the accuracy of channel estimation is a significant topic in the context of wireless
communications. For training-based channel estimations, increasing the length of a training …

Channel estimation is a critical component of vehicular communications systems, especially
in high-mobility scenarios. The IEEE 802.11 p standard uses preamble-based channel …

Wireless networks need channel estimation (CE) to function well. Deep learning (DL) has
improved 5G and future-generation network communication reliability and computational …

With the rapid development of wireless communication technology, intelligent
communication has become one of the mainstream research directions after the fifth …

Employing 1-bit analog-to-digital converters (ADCs) is necessary for large-bandwidth
massive multiple-antenna systems to maintain reasonable power consumption. However …

Deep learning (DL)-based channel estimation has achieved remarkable success. However,
most existing works focus on the white Gaussian noise which are inapplicable for cell-edge …