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arXiv · 2511.07826

Variable-Length Joint Source-Channel Coding for Semantic Communication

Yujie Zhou·Rulong Wang·Yong Xiao·Yingyu Li·Guangming Shi
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Abstract

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.

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Yujie Zhou, Rulong Wang, Yong Xiao, Yingyu Li, Guangming Shi. 2025-11-11. Variable-Length Joint Source-Channel Coding for Semantic Communication. https://arxiv.org/abs/2511.07826

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