Variable-Length Joint Source-Channel Coding for Semantic Communication
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866912701315284992 |
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| author | Zhou, Yujie Wang, Rulong Xiao, Yong Li, Yingyu Shi, Guangming |
| author_facet | Zhou, Yujie Wang, Rulong Xiao, Yong Li, Yingyu Shi, Guangming |
| contents | This paper investigates a key challenge faced by joint source-channel coding (JSCC) in digital semantic communication (SemCom): the incompatibility between existing JSCC schemes that yield continuous encoded representations and digital systems that employ discrete variable-length codewords. It further results in feasibility issues in achieving physical bit-level rate control via such JSCC approaches for efficient semantic transmission. In this paper, we propose a novel end-to-end coding (E2EC) framework to tackle it. The semantic coding problem is formed by extending the information bottleneck (IB) theory over noisy channels, which is a tradeoff between bit-level communication rate and semantic distortion. With a structural decomposition of encoding to handle code length and content respectively, we can construct an end-to-end trainable encoder that supports the direct compression of a data source into a finite codebook. To optimize our E2EC across non-differentiable operations, e.g., sampling, we use the powerful policy gradient to support gradient-based updates. Experimental results illustrate that E2EC achieves high inference quality with low bit rates, outperforming representative baselines compatible with digital SemCom systems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_07826 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Variable-Length Joint Source-Channel Coding for Semantic Communication Zhou, Yujie Wang, Rulong Xiao, Yong Li, Yingyu Shi, Guangming Information Theory This paper investigates a key challenge faced by joint source-channel coding (JSCC) in digital semantic communication (SemCom): the incompatibility between existing JSCC schemes that yield continuous encoded representations and digital systems that employ discrete variable-length codewords. It further results in feasibility issues in achieving physical bit-level rate control via such JSCC approaches for efficient semantic transmission. In this paper, we propose a novel end-to-end coding (E2EC) framework to tackle it. The semantic coding problem is formed by extending the information bottleneck (IB) theory over noisy channels, which is a tradeoff between bit-level communication rate and semantic distortion. With a structural decomposition of encoding to handle code length and content respectively, we can construct an end-to-end trainable encoder that supports the direct compression of a data source into a finite codebook. To optimize our E2EC across non-differentiable operations, e.g., sampling, we use the powerful policy gradient to support gradient-based updates. Experimental results illustrate that E2EC achieves high inference quality with low bit rates, outperforming representative baselines compatible with digital SemCom systems. |
| title | Variable-Length Joint Source-Channel Coding for Semantic Communication |
| topic | Information Theory |
| url | https://arxiv.org/abs/2511.07826 |