Artifact for MobiCom'24: RF-Diffusion: Radio Signal Generation via Time-Frequency Diffusion
Year: 2024
Type: article
Abstract: We introduce RF-Diffusion, a versatile generative model designed for wireless data. RF-Diffusion is capable of generating various types of signals, including Wi-Fi, FMCW Radar, 5G, and even modalities beyond RF (e.g., EEG signal), showcasing RF-Diffusion's prowess across different signal categories. We extensively evaluate RF-Diffusion's generative capabilities and validate its effectiveness in multiple downstream tasks, including Wi-Fi sensing, 5G channel estimation, and EEG denoising. For more details, please visit our website (https://github.com/mobicom24/RF-Diffusion) or read our paper: [MobiCom'24] RF-Diffusion: Radio Signal Generation via Time-Frequency Diffusion If you use our algorithm in your work, please reference it using: @inproceedings {Chi2024RF, author = {Chi, Guoxuan and Yang, Zheng and Wu, Chenshu and Xu, Jingao and Gao, Yuchong and Liu, Yunhao Han, Tony Xiao}, title = {{RF-Diffusion: Radio Signal Generation via Time-Frequency Diffusion}}, booktitle = {The 30th Annual International Conference on Mobile Computing and Networking (ACM MobiCom'24)}, year = {2024}, publisher = {ACM} }
Author: Chi, Guoxuan
Institution: Tsinghua University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6929924137
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