Unveiling Covert Semantics: Joint Source-Channel Coding Under a Covertness Constraint
<|reference_start|>Unveiling Covert Semantics: Joint Source-Channel Coding Under a Covertness Constraint: The fundamental limit of Semantic Communications (joint source-channel coding) is established when the transmission needs to be kept covert from an external warden. We derive information-theoretic achievability and matching converse results and we show that source and channel coding separation holds for this setup. Furthermore, we show through an experimental setup that one can train a deep neural network to achieve covert semantic communication for the classification task. Our numerical experiments confirm our theoretical findings, which indicate that for reliable joint source-channel coding the number of transmitted source symbols can only scale as the square-root of the number of channel uses.<|reference_end|>
@article{bounhar2024unveiling,
    title={Unveiling Covert Semantics: Joint Source-Channel Coding Under a
  Covertness Constraint},
    author={Abdelaziz Bounhar, Mireille Sarkiss, Mich`ele Wigger},
    journal={arXiv preprint arXiv:2406.13466},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.13466},
    primaryClass={cs.IT math.IT}
}