mlsanityData to 7 Oct 2026

Contextual Memory-Enhanced Source Coding for Low-SNR Communications

arXiv 2605.04400 ↗First posted 6 May 2026cs.IT cs.LG math.ITcited by 0

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Abstract (arXiv)

Separate Source-Channel Coding (SSCC) remains vulnerable in noisy text transmission due to the fragility of autoregressive source decoding, especially when Arithmetic Coding (AC) relies on Large Language Model (LLM)-based probability estimation. This letter proposes a Memory-Augmented Source Coding (MASC) scheme that internalizes contextual patterns into a source model. Specifically, MASC employs a shared Parameterized Contextual Memory (PCM) for multi-order n-gram patterns, and a Mixture-of-Memory-Experts Router (MMER) for sparse, hidden-state-dependent routing over memory experts. This adaptive activation refines source probability estimation, shortens codelength, and mitigates decoding sensitivity to residual channel errors. Experiments over Rayleigh fading and AWGN channels demonstrate its effectiveness.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 17 of its 30 references that are in the map. First posted on arXiv 6 May 2026.

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References · 17

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5 more
  1. 2023Semantic Communication with Memorycited by 12
  2. 2022Adaptive Bit Rate Control in Semantic Communication with Incremental Knowledge-based HARQcited by 10
  3. 2025Separate Source Channel Coding Is Still What You Need: An LLM-based Rethinkingcited by 5
  4. 2022A Sequence Repetition Node-Based Successive Cancellation List Decoder for 5G Polar Codes: Algorithm and Implementationcited by 2
  5. 2026In-Context Source and Channel Codingcited by 1

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