In this study, a deep learning bidirectional long short-term memory (BiLSTM) recurrent
neural network-based channel state information estimator is proposed for 5G orthogonal …

Using deep learning technologies, the channel estimate for an orthogonal frequency
division multiplexing system (OFDM) based on pilots is done in this work. To be more …

This study proposes an online deep learning‐based channel state estimator for OFDM
wireless communication systems by employing the deep learning long short‐term memory …

The advanced neural network methods solve significant signal estimation and channel
characterization difficulties in the next-generation 5G wireless communication systems. The …

Channel estimation plays a critical role in the system performance of wireless networks. In
addition, deep learning has demonstrated significant improvements in enhancing the …

Recently much research work has focused on employing deep learning (DL) algorithms to
perform channel estimation in the upcoming 6G communication systems. However, these DL …

At cellular wireless communication systems, channel estimation (CE) is one of the key
techniques that are used in Orthogonal Frequency Division Multiplexing modulation …

The combination of non-orthogonal multiple access (NOMA) and reconfigurable intelligent
surface (RIS) technologies is proposed to meet the demands of data rate, latency, and …

In the fifth-generation (5G) networks, multiple input multiple-output (MIMO) systems are
further developed to enhance transmission reliability. However, channel estimation is one of …

In this letter we apply deep learning tools to conduct channel estimation for an orthogonal
frequency division multiplexing (OFDM) system based on downlink pilots. To be specific, a …