In trainable wireless communications systems, the use of deep learning for over-the-air
training aims to address the discontinuity in backpropagation learning caused by the …

Autoencoder-based communication systems use neural network channel models to
backwardly propagate message reconstruction error gradients across an approximation of …

Channel estimation is one of the essential tasks of realizing reconfigurable intelligent
surface (RIS)-aided communication systems. However, the RIS introduces a high-dimension …

End-to-end learning of communications systems is a fascinating novel concept that has so
far only been validated by simulations for block-based transmissions. It allows learning of …

Channel modeling is a critical topic when considering accurately designing or evaluating the
performance of a communications system. Most prior work in designing or learning new …

The quality of channel estimation (CE) is critical to the performence of wireless
communication systems. In addition to the conventional model based CE methods appeared …

To tackle the sub-optimization problem of the conventional block structure communication
systems, recently, a novel concept named end-to-end communication system that can …

Sparse code multiple access (SCMA) has excellent application prospects in satellite-
terrestrial links because of its high spectral efficiency and accsess capacity. In end-to-end …

Machine learning is a highly promising tool to design the physical layer of wireless
communication systems, but it usually requires that a channel model is known. As data rates …

This paper proposes a deep learning (DL)-aided multicarrier (MC) system operating on
fading channels, where both modulation and demodulation blocks are modeled by deep …