Semantic Transmission Framework in Direct Satellite Communications

2026-01-01

arXiv.org

AI Summary

This work addresses the severe performance limitations imposed by link budget constraints in direct satellite-to-ground communication. To overcome this challenge, the paper proposes a semantic communication framework tailored for satellite-terrestrial direct links, which jointly integrates communication, computation, and generative quality into a novel semantic efficiency metric. The framework co-optimizes multiple decision variables—including transmission mode selection, satellite–ground association, inter-satellite task migration, denoising steps, and adaptive weighting coefficients. To solve the resulting complex nonlinear integer programming problem, the authors design a decision-aided REINFORCE++ algorithm featuring a feasibility-aware action space and an actor-only policy update mechanism that dispenses with a critic network. Experimental results demonstrate that the proposed method achieves significantly higher semantic efficiency compared to existing baselines.

Technology Category

• Search and Optimization: Sampling/Simulation-based Search
• Planning, Routing, and Scheduling: Planning with Language Models
• Multiagent Systems: Agent Communication

Application Category

• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs
• Search and Retrieval-Augmented AI: Large language models for search
• Economics, Online Markets and Human Computation: Cost models of using LLMs in production systems

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.

Problem

• link budget
• direct satellite communications
• semantic transmission
• bottleneck
• satellite communications

Innovation

• semantic transmission
• satellite communications
• semantic efficiency
• REINFORCE++
• task migration