{"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/beamformed-fingerprint-learning-for-accurate","title":"Beamformed Fingerprint Learning for Accurate Millimeter Wave Positioning","arxiv_id":"1804.04112","date":"2018-04-11","proceeding":null,"authors":["João Gante","Gabriel Falcão","Leonel Sousa"],"abstract":"With millimeter wave wireless communications, the resulting radiation\nreflects on most visible objects, creating rich multipath environments, namely\nin urban scenarios. The radiation captured by a listening device is thus shaped\nby the obstacles encountered, which carry latent information regarding their\nrelative positions. In this paper, a system to convert the received millimeter\nwave radiation into the device's position is proposed, making use of the\naforementioned hidden information. Using deep learning techniques and a\npre-established codebook of beamforming patterns transmitted by a base station,\nthe simulations show that average estimation errors below 10 meters are\nachievable in realistic outdoors scenarios that contain mostly\nnon-line-of-sight positions, paving the way for new positioning systems.","url_abs":"http://arxiv.org/abs/1804.04112v1","url_pdf":"http://arxiv.org/pdf/1804.04112v1.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":"beamformed-fingerprint-learning-for-accurate","repo_url":"https://github.com/gante/mmWave-localization-learning","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[{"task_slug":"outdoor-positioning","task_name":"Outdoor Positioning"},{"task_slug":null,"task_name":"Position"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}