Berlin V2X

Citation Author(s):
Rodrigo
Hernangomez
Fraunhofer Heinrich Hertz Institute
Philipp
Geuer
Ericsson Research
Alexandros
Palaios
Ericsson Research
Daniel
Schäufele
Fraunhofer Heinrich Hertz Institute
Cara
Watermann
Ericsson Research
Khawla
Taleb-Bouhemadi
Fraunhofer Heinrich Hertz Institute
Mohammad
Parvini
Vodafone Chair, Technische Universität Dresden
Anton
Krause
Vodafone Chair, Technische Universität Dresden
Sanket
Partani
Technische Universität Kaiserslautern
Christian
Vielhaus
Deutsche Telekom Chair, Technische Universität Dresden
Martin
Kasparick
Fraunhofer Heinrich Hertz Institute
Daniel F.
Külzer
BMW Group
Friedrich
Burmeister
Vodafone Chair, Technische Universität Dresden
Frank H. P.
Fitzek
Deutsche Telekom Chair, Technische Universität Dresden
Hans D.
Schotten
Technische Universität Kaiserslautern
Gerhard
Fettweis
Vodafone Chair, Technische Universität Dresden
Slawomir
Stanczak
Fraunhofer Heinrich Hertz Institute
Submitted by:
Rodrigo Hernangomez
Last updated:
Fri, 05/26/2023 - 07:48
DOI:
10.21227/8cj7-q373
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Abstract 

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.

The data includes information on:

  • Physical layer parameters (such as signal strength and signal quality).
  • Cellular radio resource management like cell identity, carrier aggregation and assigned resource blocks.
  • Wireless Quality of Service (QoS) like delay and throughput (for cellular) or packet error rate (for sidelink).
  • GPS-positioning information.
  • Side information (traffic and weather).

The 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.

Instructions: 

The cellular and sidelink parquet files can be directly downloaded and read with Python using Pandas and parquet support via PyArrow or Fastparquet.

For detailed instructions, please refer to the BerlinV2X-README.pdf or the available documentation on GitHub.

Funding Agency: 
German Federal Ministry of Education and Research
Grant Number: 
16KIS1170K

Dataset Files

Documentation

AttachmentSize
File BerlinV2X-README.pdf761.94 KB