{"url":"/dataset/deepbeam","name":"DeepBeam","full_name":null,"description_markdown":"It contains 19 HDF5 files that represent a data collection campaign run on the NI mmWave Transceiver System with four SiBeam 60 GHz radio heads and on two Pi-Radio digital 60 GHz radios.\r\n\r\nPlease refer to the website deepbeam.net\r\n\r\nSource: [https://github.com/wineslab/deepbeam](https://github.com/wineslab/deepbeam)","description_withheld":null,"homepage":"https://deepbeam.net","introduced_date":"2020-12-28","introduced_date_note":null,"introduced_by":{"paper":"/paper/deepbeam-deep-waveform-learning-for","title":"DeepBeam: Deep Waveform Learning for Coordination-Free Beam Management in mmWave Networks","first_author":null,"url":null},"license":null,"modalities":[],"tasks":[],"languages":[],"variants":["DeepBeam"],"data_loaders":[],"num_papers_in_archive":5,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}