用OTFS+语义传输+扩散去噪，提升无人机应急通信稳定性
Emergency Communication: OTFS-Based Semantic Transmission with Diffusion Noise Suppression
- 结合OTFS调制与语义通信，降低冗余并增强抗衰落能力
- 在高速移动场景下实现至少3dB的信噪比增益
- 适合灾害救援等高动态环境下的可靠通信应用
由于具备灵活性和动态覆盖能力，无人机已成为灾后地区应急通信的重要平台。然而，高速移动场景下的复杂信道条件严重影响了传统通信系统的可靠性与效率。本文提出一种智能应急通信框架，融合正交时频空（OTFS）调制、语义通信及基于扩散的去噪模块，以应对这些挑战。OTFS凭借优异的抗衰落特性和对快速变化环境的适应性，确保了信道稳健性；语义通信通过提取关键信息、减少数据冗余，提升了传输效率；此外，提出的扩散去噪模块利用渐进式降噪过程与统计噪声建模，优化了语义信息恢复精度。实验结果表明，所提方案显著提升了高速移动无人机场景下的链路稳定性和传输性能，相比现有方法至少获得3dB信噪比增益。
原文摘要 · Abstract (English)
Due to their flexibility and dynamic coverage capabilities, Unmanned Aerial Vehicles (UAVs) have emerged as vital platforms for emergency communication in disaster-stricken areas. However, the complex channel conditions in high-speed mobile scenarios significantly impact the reliability and efficiency of traditional communication systems. This paper presents an intelligent emergency communication framework that integrates Orthogonal Time Frequency Space (OTFS) modulation, semantic communication, and a diffusion-based denoising module to address these challenges. OTFS ensures robust communication under dynamic channel conditions due to its superior anti-fading characteristics and adaptability to rapidly changing environments. Semantic communication further enhances transmission efficiency by focusing on key information extraction and reducing data redundancy. Moreover, a diffusion-based channel denoising module is proposed to leverage the gradual noise reduction process and statistical noise modeling, optimizing the accuracy of semantic information recovery. Experimental results demonstrate that the proposed solution significantly improves link stability and transmission performance in high-mobility UAV scenarios, achieving at least a 3dB SNR gain over existing methods.
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