{"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/a-hybrid-millimeter-wave-channel-simulator","title":"A Hybrid Millimeter-wave Channel Simulator for Joint Communication and Localization","arxiv_id":"2210.11422","date":"2022-10-04","proceeding":null,"authors":["Junquan Deng"],"abstract":"Joint communication and localization~(JCL) is envisioned to be a key feature in future millimeter-wave~(mmWave) wireless networks for context-aware applications. A map-based channel model considering both site-specific radio environment and statistical channel characteristics is essential to facilitate JCL research and to evaluate the performance of various JCL systems. To this end, this paper presents an open-source hybrid mmWave channel simulator called OmniSIM for site-specific JCL research, which uses digital map, network layout and user trajectories as inputs to predict the channel responses between users and base stations. A fast shooting-bouncing rays~(FSBR) algorithm combined with Computational Electromagnetic, has been developed to generate channel parameters relevant to JCL, considering mmWave reflection, diffusing, diffraction and scattering.","url_abs":"https://arxiv.org/abs/2210.11422v1","url_pdf":"https://arxiv.org/pdf/2210.11422v1.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":"a-hybrid-millimeter-wave-channel-simulator","repo_url":"https://github.com/dengjunquan/omnisim","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[{"method_slug":"base","method_name":"BASE"}],"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}