In this paper, a decision-directed (DD)-channel estimation (CE) algorithm by employing
deep learning (DL) is proposed for high mobility vehicular environments. The proposed …

The techniques used in deep learning for channel estimation are generally model-centric.
These models have changed significantly over the years with each iteration yielding a better …

The accurate channel state information (CSI) is important to realize the high-reliability and
high-efficiency transmission. So far, most of the conventional methods reconstruct CSI on …

Channel estimation plays an important role in the system performance of wireless networks.
With the rapid development and wide application of 5G technology, traditional channel …

In this paper, we present a deep learning-based technique for channel estimation. By
treating the time-frequency grid of the channel response as a low-resolution 2D-image, we …

Radio frequency (RF) estimation plays a significant role in cellular network's planning and
optimization. The conventional methods for RF estimation are mainly based on radio …

As the demand for high-speed and reliable wireless communication continues to grow, 5G
technology has emerged as a promising solution to meet these requirements. However …

In this work, we propose a convolutional neural network (CNN) based low-complexity
approach for downlink (DL) channel estimation (CE) in frequency division duplex systems. In …

As the key to wireless communication, channel estimation has become a hot research topic
in recent years. In this paper, we propose a deep learning method based on the channel …

In this paper, we investigate neural network-based channel estimation strategies for point-to-
point multi-input multi-output (MIMO) systems. In an attempt to keep computational …