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Semantic Transmission Framework in Direct Satellite Communications

Chong Huang, Xuyang Chen, Jingjing Cui, Jingfu Li, Pei Xiao, Gaojie Chen, Rahim Tafazolli

TL;DR

A decision-assisted REINFORCE++ algorithm is proposed that utilizes feasibility-aware action space and a critic-free stabilized policy update to maximize the average semantic efficiency metric and achieves higher semantic efficiency than baselines.

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.

Semantic Transmission Framework in Direct Satellite Communications

TL;DR

A decision-assisted REINFORCE++ algorithm is proposed that utilizes feasibility-aware action space and a critic-free stabilized policy update to maximize the average semantic efficiency metric and achieves higher semantic efficiency than baselines.

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.
Paper Structure (8 sections, 13 equations, 3 figures, 1 algorithm)

This paper contains 8 sections, 13 equations, 3 figures, 1 algorithm.

Table of Contents

  1. Introduction
  2. System Model and Problem Formulation
  3. System Model
  4. Semantic Transmission Framework
  5. Problem Formulation
  6. Decision-Assisted DRL-Based Optimization
  7. NUMERICAL RESULTS
  8. Conclusion

Figures (3)

  • Figure 1: Direct satellite communication networks.
  • Figure 2: Average semantic efficiency versus transmit power at satellites.
  • Figure 3: Average semantic efficiency versus number of satellites.