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arXiv · 2601.17731

S-MDMA: Sensitivity-Aware Model Division Multiple Access for Satellite-Ground Semantic Communication

Hui Cao·Rui Meng·Shujun Han·Song Gao·Xiaodong Xu·Ping Zhang
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Abstract

Satellite-ground semantic communication (SemCom) is expected to play a pivotal role in convergence of communication and AI (ComAI), particularly in enabling intelligent and efficient multi-user data transmission. However, the inherent bandwidth constraints and user interference in satellite-ground systems pose significant challenges to semantic fidelity and transmission robustness. To address these issues, we propose a sensitivity-aware model division multiple access (S-MDMA) framework tailored for bandwidth-limited multi-user scenarios. The proposed framework first performs semantic extraction and merging based on the MDMA architecture to consolidate redundant information. To further improve transmission efficiency, a semantic sensitivity sorting algorithm is presented, which can selectively retain key semantic features. In addition, to mitigate inter-user interference, the framework incorporates orthogonal embedding of semantic features and introduces a multi-user reconstruction loss function to guide joint optimization. Experimental results on open-source datasets demonstrate that S-MDMA consistently outperforms existing methods, achieving robust and high-fidelity reconstruction across diverse signal-to-noise ratio (SNR) conditions and user configurations.

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Hui Cao, Rui Meng, Shujun Han, Song Gao, Xiaodong Xu, Ping Zhang. 2026-01-25. S-MDMA: Sensitivity-Aware Model Division Multiple Access for Satellite-Ground Semantic Communication. https://arxiv.org/abs/2601.17731

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