We propose a novel neural waveform compression method to catalyze emerging speech semantic communications. By introducing nonlinear transform and variational modeling, we effectively capture the dependencies within speech frames and estimate the …
As one novel approach to realize end-to-end wireless image semantic transmission, deep learning-based joint source-channel coding (deep JSCC) method is emerging in both deep learning and communication communities. However, current deep JSCC image …
The recent deep learning-based joint source-channel coding (deep JSCC) framework has shown superior performance on end-to-end wireless image transmission without suffering from the “cliff effect”. However, a fundamental limit of current deep JSCC …
Semantic communications have shown great potential to boost the end-to-end transmission performance. To further improve the system efficiency, in this paper, we propose a class of novel semantic coded transmission (SCT) schemes over multiple-input …
In this paper, we propose a new class of high-efficiency semantic coded transmission methods for end-to-end speech transmission over wireless channels. We name the whole system as deep speech semantic transmission (DSST). Specifically, we introduce a …
In this paper, we aim to redesign the vision Transformer (ViT) as a new backbone to realize semantic image transmission, termed wireless image transmission transformer (WITT). Previous works build upon convolutional neural networks (CNNs), which are …
In this paper, we design a new class of high-efficiency deep joint source-channel coding methods to achieve end-to-end video transmission over wireless channels. The proposed methods exploit nonlinear transform and conditional coding architecture to …
The last 70 years have witnessed the transition of communication from Shannon's theoretical concept to current high-efficiency practical systems. Classical communication systems address the capability-deficiency issue mainly by module stacking and …
Classical communication paradigms focus on accurately transmitting bits over a noisy channel, and Shannon theory provides a fundamental theoretical limit on the rate of reliable communications. In this approach, bits are treated equally, and the …
We consider the wireless text transmission using joint source-channel coding (JSCC). Classical source coding only considers the syntactic information based on probabilistic models, ignoring the meaning of source messages. Neural network based joint …