{"url":"/dataset/berlin-v2x","name":"Berlin V2X","full_name":null,"description_markdown":"The Berlin V2X dataset offers high-resolution GPS-located wireless measurements across diverse urban environments in the city of Berlin for both cellular and sidelink radio access technologies, acquired with up to 4 cars over 3 days. The data enables thus a variety of different ML studies towards vehicle-to-anything (V2X) communication.\r\n\r\nThe data includes information on\r\n\r\n* physical layer parameters (such as signal strength and signal quality)\r\n* cellular radio resource management like cell identity, carrier aggregation and assigned resource blocks\r\n* wireless Quality of Service (QoS) like delay and throughput (for cellular) or packet error rate (for sidelink)\r\n* positioning information.\r\n\r\nThe datasets are labelled and pre-filtered for a fast on-boarding and applicability. The measurement methodology pursues an application to Machine Learning (ML) for tasks such as QoS prediction, transfer learning, proactive radio resource allocation or link selection, among others.","description_withheld":null,"homepage":"https://ieee-dataport.org/open-access/berlin-v2x","introduced_date":"2022-12-12","introduced_date_note":null,"introduced_by":{"paper":"/paper/berlin-v2x-a-machine-learning-dataset-from","title":"Berlin V2X: A Machine Learning Dataset from Multiple Vehicles and Radio Access Technologies","first_author":"Rodrigo Hernangómez","url":null},"license":{"name":"Creative Commons Attribution","url":"https://creativecommons.org/licenses/by/4.0/"},"modalities":[{"name":"Tabular","url":"/datasets/modality/tabular"},{"name":"Time series","url":"/datasets/modality/time-series"}],"tasks":[{"name":"Intelligent Communication","url":"/task/intelligent-communication","datasets_with_task":"/datasets/task/intelligent-communication"},{"name":"Connectivity Estimation","url":"/task/connectivity-estimation","datasets_with_task":"/datasets/task/connectivity-estimation"}],"languages":[],"variants":["Berlin V2X"],"data_loaders":[],"num_papers_in_archive":2,"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."}