Emergency Communication: OTFS-Based Semantic Transmission with Diffusion Noise Suppression
원문 초록
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.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application
Channel-adaptive Cross-modal Generative Semantic Communication for Point Cloud Transmission
ICDM: Interference Cancellation Diffusion Models for Wireless Semantic Communications
PaddleOCR 3.0 Technical Report
ScoreAdv: Score-based Targeted Generation of Natural Adversarial Examples via Diffusion Models
LangMamba: A Language-driven Mamba Framework for Low-dose CT Denoising with Vision-language Models
토론
이 논문과 연결된 포럼 글이 아직 없습니다.