sDAC -- Semantic Digital Analog Converter for Semantic Communications
Zhicheng Bao, Chen Dong, Xiaodong Xu

TL;DR
This paper introduces sDAC, a novel semantic digital analog converter that enables robust, bidirectional conversion between digital and analog signals in semantic communication systems, independent of specific models or channels.
Contribution
The paper presents sDAC, a generative module that seamlessly integrates semantic and digital communications, addressing the limitations of traditional quantization methods.
Findings
sDAC demonstrates strong generative capabilities.
sDAC shows robustness across various channel conditions.
sDAC is compatible with multiple semantic models and modulation methods.
Abstract
In this paper, we propose a novel semantic digital analog converter (sDAC) for the compatibility of semantic communications and digital communications. Most of the current semantic communication systems are based on the analog modulations, ignoring their incorporation with digital communication systems, which are more common in practice. In fact, quantization methods in traditional communication systems are not appropriate for use in the era of semantic communication as these methods do not consider the semantic information inside symbols. In this case, any bit flip caused by channel noise can lead to a great performance drop. To address this challenge, sDAC is proposed. It is a simple yet efficient and generative module used to realize digital and analog bi-directional conversion. On the transmitter side, continuous values from the encoder are converted to binary bits and then can be…
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Taxonomy
TopicsNeural Networks and Applications · Advanced Computational Techniques and Applications · Robotics and Automated Systems
MethodsFLIP
