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arXiv · 2608.07897

Semantic-Aided Iterative Decoding for Uplink Non-Orthogonal Transmission

Wenjing Wei·Chentao Yue·Branka Vucetic·Yonghui Li
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Abstract

This paper proposes semantic-aided iterative decoding (Sem-IR) for uplink non-orthogonal transmission of a shared natural-language source. K users each hold one segment of a common sentence and superimpose low-density parity-check (LDPC) coded transmissions over an additive white Gaussian noise (AWGN) channel. At the base station, an iterative elementary signal estimator (ESE) and K parallel LDPC decoders progressively cancel inter-user interference. As high-power users pass both parity and language-plausibility checks earlier, their decoded bytes form a reliable linguistic prefix for the remaining users; a fine-tuned ByT5 byte-level language model exploits this prefix to predict byte posteriors for the unconverged user. The byte posteriors are marginalized to bit-level log-likelihood ratios and convex-combined with the LDPC posteriors inside the iterative loop. The resulting feedback closes the loop between the language model and the physical-layer iteration. Simulations show that Sem-IR outperforms orthogonal time-division access (TDMA) and the same NOMA receiver without semantic feedback in block error rate (BLER), yielding an order-of-magnitude reduction over NOMA at 8 dB.

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Wenjing Wei, Chentao Yue, Branka Vucetic, Yonghui Li. 2026-08-08. Semantic-Aided Iterative Decoding for Uplink Non-Orthogonal Transmission. https://arxiv.org/abs/2608.07897

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