Semantic Transmission Framework in Direct Satellite Communications

TL;DR

This paper proposes a semantic transmission framework for direct satellite communications to address link budget limitations, introducing a semantic efficiency metric and an optimized algorithm to improve communication effectiveness.

Contribution

It introduces a novel semantic transmission framework with a new efficiency metric and a decision-assisted REINFORCE++ algorithm for optimized satellite communication.

Findings

The proposed algorithm outperforms baseline methods in semantic efficiency.

Optimization of transmission mode and resource allocation enhances communication quality.

Numerical results validate the effectiveness of the proposed framework.

Abstract

Insufficient link budget has become a bottleneck problem for direct access in current satellite communications. In this paper, we develop a semantic transmission framework for direct satellite communications as an effective and viable solution to tackle this problem. To measure the tradeoffs between communication, computation, and generation quality, we introduce a semantic efficiency metric with optimized weights. The optimization aims to maximize the average semantic efficiency metric by jointly optimizing transmission mode selection, satellite-user association, ISL task migration, denoising steps, and adaptive weights, which is a complex nonlinear integer programming problem. To maximize the average semantic efficiency metric, we propose a decision-assisted REINFORCE++ algorithm that utilizes feasibility-aware action space and a critic-free stabilized policy update. Numerical results show that the proposed algorithm achieves higher semantic efficiency than baselines.