Aiming at the difficulty of the deep neural network (DNN) adapting to channel changes in
communication systems, a channel synchronization deep neural network (CSDNN) based …

A new frame synchronization technique based on convolutional neural network (CNN) is
proposed for synchronized networks. To estimate the exact packet arrival time, the receiver …

In orthogonal frequency division multiplexing (OFDM) systems, the existing timing
synchronization (TS) methods are challenged by high computational complexity, large …

With the development of the Internet of Things and the Industrial Internet, more and more
devices require stable and reliable wireless connections. When traditional communication …

In this letter, a lightweight one-dimensional convolutional neural network (1-D CNN)-based
timing synchronization (TS) method is proposed to reduce the computational complexity and …

In this paper, we propose a novel distributed deep learning (DL) network for signal
classification to achieve accurate time–frequency synchronization in wireless …

Multi-path fading seriously affects the accuracy of timing synchronization (TS) in orthogonal
frequency division multiplexing (OFDM) systems. To tackle this issue, we propose a …

This paper proposes a supervised convolutional neural network (CNN) based symbol timing
synchronization method using the spectrogram image for preamble-less orthogonal …

Timing synchronization (TS) is one of the key tasks in orthogonal frequency division
multiplexing (OFDM) systems. However, multi-path uncertainty corrupts the TS correctness …

End-to-end learning-based communications systems are more likely to achieve the global
optimal performance. In this work, we implement a complete communications system as an …