{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/over-the-air-deep-learning-based-radio-signal","title":"Over the Air Deep Learning Based Radio Signal Classification","arxiv_id":"1712.04578","date":"2017-12-13","proceeding":null,"authors":["Timothy J. O'Shea","Tamoghna Roy","T. Charles Clancy"],"abstract":"We conduct an in depth study on the performance of deep learning based radio\nsignal classification for radio communications signals. We consider a rigorous\nbaseline method using higher order moments and strong boosted gradient tree\nclassification and compare performance between the two approaches across a\nrange of configurations and channel impairments. We consider the effects of\ncarrier frequency offset, symbol rate, and multi-path fading in simulation and\nconduct over-the-air measurement of radio classification performance in the lab\nusing software radios and compare performance and training strategies for both.\nFinally we conclude with a discussion of remaining problems, and design\nconsiderations for using such techniques.","url_abs":"http://arxiv.org/abs/1712.04578v1","url_pdf":"http://arxiv.org/pdf/1712.04578v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"over-the-air-deep-learning-based-radio-signal","repo_url":"https://github.com/ITU-AI-ML-in-5G-Challenge/ITU-ML5G-PS-007-BacalhauNet","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"over-the-air-deep-learning-based-radio-signal","repo_url":"https://github.com/Liu-1994/DL_based_RSC","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null},{"paper_slug":"over-the-air-deep-learning-based-radio-signal","repo_url":"https://github.com/ernestkck/RML2018","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"over-the-air-deep-learning-based-radio-signal","repo_url":"https://github.com/kolbrak/Modulation_Classification","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"over-the-air-deep-learning-based-radio-signal","repo_url":"https://github.com/nikulshr/resnet_fpga","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"deep-learning","task_name":"Deep Learning"},{"task_slug":"classification","task_name":"General Classification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}