Joint Coding-Modulation for Digital Semantic Communications via Variational Autoencoder

TL;DR

This paper introduces a joint coding-modulation framework using variational autoencoders for digital semantic communications, effectively learning discrete modulation strategies that adapt to channel conditions, outperforming existing methods.

Contribution

It proposes a novel VAE-based joint coding-modulation approach that addresses digital modulation non-differentiability and enhances semantic communication efficiency.

Findings

Outperforms state-of-the-art digital semantic coding methods.

Reduces performance gap with analog semantic communication at higher modulation orders.

Adapts modulation strategies to channel conditions effectively.

Abstract

Semantic communications have emerged as a new paradigm for improving communication efficiency by transmitting the semantic information of a source message that is most relevant to a desired task at the receiver. Most existing approaches typically utilize neural networks (NNs) to design end-to-end semantic communication systems, where NN-based semantic encoders output continuously distributed signals to be sent directly to the channel in an analog fashion. In this work, we propose a joint coding-modulation (JCM) framework for digital semantic communications by using variational autoencoder (VAE). Our approach learns the transition probability from source data to discrete constellation symbols, thereby avoiding the non-differentiability problem of digital modulation. Meanwhile, by jointly designing the coding and modulation process together, we can match the obtained modulation strategy with the operating channel condition. We also derive a matching loss function with information-theoretic meaning for end-to-end training. Experiments on image semantic communication validate the superiority of our proposed JCM framework over the state-of-the-art quantization-based digital semantic coding-modulation methods across a wide range of channel conditions, transmission rates, and modulation orders. Furthermore, its performance gap to analog semantic communication reduces as the modulation order increases while enjoying the hardware implementation convenience.