Direct Satellite-to-Device Communications: From Cooperative Task Offloading to Non-Cooperative Access Monitoring

2026-09-01

AI Summary

该文针对直接卫星到设备通信中的动态信道条件、计算资源限制及未授权访问问题，提出了一种支持合作任务卸载与非合作接入监控的系统，通过D3QN优化任务卸载策略，并使用基于Transformer的模型实现信号检测和自动调制分类。

Abstract

Direct satellite-to-device (DS2D) communication is emerging as a transformative paradigm for extending ubiquitous connectivity and edge computing capabilities to remote and underserved regions within 6G non-terrestrial networks. However, practical deployment faces dual critical challenges: i) dynamic satellite channel conditions (e.g., severe Doppler shifts, fast fading) and constrained satellite computing resources in cooperative scenarios; and ii) unauthorized satellite access introduces significant spectrum security threats in non-cooperative scenarios. To address these challenges, we propose a versatile DS2D system that supports cooperative task offloading and non-cooperative access monitoring. For cooperative DS2D communications, we integrate a channel estimation module with a dueling double deep Q-network (D3QN) to dynamically optimize task offloading strategy. For non-cooperative DS2D communications, we propose Transformer-based models to enable blind signal detection and automatic modulation classification (AMC). Simulation results show that: 1) The D3QN algorithm reduces average latency by up to 225\% compared to static association policies. 2) Our signal detection model achieves an average presence detection probability of 90.5\% for DS2D signals. 3) The proposed AMC algorithm achieves superior performance across different signal-to-noise ratios (SNRs), with a 9.4\% accuracy gain in low-SNR regimes compared to existing methods.

Problem

• Direct Satellite-to-Device Communications
• Dynamic Channel Conditions
• Spectrum Security Threats
• Satellite Computing Resources

Innovation

• Direct Satellite-to-Device (DS2D) Communication
• Dueling Double Deep Q-Network (D3QN)
• Transformer-based Models
• Automatic Modulation Classification (AMC)