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

TL;DR

This paper introduces S-MDMA, a novel sensitivity-aware multiple access framework for satellite-ground semantic communication, enhancing robustness and efficiency in multi-user data transmission under bandwidth constraints.

Contribution

The paper proposes a new S-MDMA framework with semantic extraction, sensitivity sorting, and orthogonal embedding to improve multi-user satellite-ground semantic communication.

Findings

Outperforms existing methods in reconstruction quality

Maintains robustness across various SNR conditions

Effectively reduces inter-user interference

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.