Convolutional neural networks (CNNs) have been widely adopted in various fields and the
wireless communication domain is no exception; researchers leveraged CNNs for …

Aiming at the problem that the downlink channel estimation performance is limited due to the
fast time-varying and non-stationary characteristics in the high-speed mobile scenarios, we …

Convolutional neural networks (CNNs) have been widely adopted in various fields and the
wireless communication domain is no exception; researchers leveraged CNNs for …

The use of machine learning methods to tackle challenging physical layer signal processing
tasks has attracted significant attention. In this work, we focus on the use of neural networks …

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

Deep Learning has rendered overwhelming potential to support the rising interest of high
dependability and maximum capacity wireless communication systems. Channel estimation …

Channel estimation is a fundamental challenge in wireless communication systems, as
accurate knowledge of the communication channel is essential for achieving reliable data …

Channel estimation forms one of the central component in current Orthogonal Frequency
Division Multiplexing (OFDM) systems that aims to eliminate the inter-symbol interference by …

The channel estimation (CE) in wireless receivers is one of the most critical and
computationally complex signal processing operations. Recently, various works have shown …

When using orthogonal frequency-division multiplexing (OFDM) for communication in
channels with high resistance to inter-symbol interference (ISI), conventional channel …