Accurate signal detection is one of the most important requirements of wireless
communication systems. The two most important processes of the signal detection are …

In this letter, we propose a novel deep learning based approach for joint channel estimation
and signal detection in orthogonal frequency division multiplexing (OFDM) systems by …

In this paper, we propose a deep learning aided approach for signal detection in orthogonal
frequency-division multiplexing (OFDM) systems with time-varying channels. The method …

This letter presents our initial results in deep learning for channel estimation and signal
detection in orthogonal frequency-division multiplexing (OFDM) systems. In this letter, we …

Deep learning (DL) algorithms can enhance wireless communication system efficiency and
address numerous physical layer challenges. Channel state estimation (CSE) and signal …

In this letter, we propose a deep learning-assisted approach for signal detection in uplink
orthogonal frequency-division multiplexing (OFDM) systems over time-varying channels. In …

The last decade has witnessed the rapid growth of deep learning (DL) applications in
wireless communications, especially for channel estimation and signal detection. However …

In this letter, we propose a model-driven deep learning (DL) approach that combines DL
with the expert knowledge to replace the existing orthogonal frequency-division multiplexing …

The evolution of data driven optimization has been shown advantageous in many
applications. In this paper, we propose a deep learning architecture for the wireless …

The orthogonal frequency division multiplexing (OFDM) technique has received wide
attention because of its high spectrum utilization. However, the drawback of inter-subcarrier …