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Separate Source Channel Coding Is Still What You Need: An LLM-based Rethinking

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arxiv 2501.04285 v4 pith:KP4NFQTD submitted 2025-01-08 cs.IT eess.SPmath.IT

classification cs.ITeess.SPmath.IT
keywords channelcodingsourcecommunicationjsccseparatessccchallenges
verification ladder T0 review T1 audit T2 compute T3 formal
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Along with the proliferating research interest in Semantic Communication (SemCom), Joint Source Channel Coding (JSCC) has dominated the attention due to the widely assumed existence in efficiently delivering information semantics. Nevertheless, this paper challenges the conventional JSCC paradigm, and advocates for adoption of Separate Source Channel Coding (SSCC) to enjoy the underlying more degree of freedom for optimization. We demonstrate that SSCC, after leveraging the strengths of Large Language Model (LLM) for source coding and Error Correction Code Transformer (ECCT) complemented for channel decoding, offers superior performance over JSCC. Our proposed framework also effectively highlights the compatibility challenges between SemCom approaches and digital communication systems, particularly concerning the resource costs associated with the transmission of high precision floating point numbers. Through comprehensive evaluations, we establish that empowered by LLM-based compression and ECCT-enhanced error correction, SSCC remains a viable and effective solution for modern communication systems. In other words, separate source and channel coding is still what we need!

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  1. LightCom: A Generative AI-Augmented Framework for QoE-Oriented Communications

    eess.SP 2025-07 conditional novelty 4.0 of 10

    A generative AI receiver can reconstruct QoE-acceptable images from low-pass-filtered, weakly channel-coded transmissions, giving large simulated SNR and coverage gains over JPEG and LDPC baselines.

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