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!
@article{arxiv.2501.04285,
title = {Separate Source Channel Coding Is Still What You Need: An LLM-based Rethinking},
author = {Tianqi Ren and Rongpeng Li and Ming-min Zhao and Xianfu Chen and Guangyi Liu and Yang Yang and Zhifeng Zhao and Honggang Zhang},
journal= {arXiv preprint arXiv:2501.04285},
year = {2025}
}