Powder Data Sets

This dataset contains channel measurements from a measurement campaign conducted on the University of Utah campus for determining the placement of three massive MIMO base stations. The exercise also shows the viability of over a dozen candidate endpoint sites. This dataset is comprised of LTS frames sent by a transmitter that was moved from position to position (endpoint locations). These frames were measured at radio receivers on five candidate rooftop locations. Candidate rooftop sites (receivers) and potential endpoints locations (transmitter) are shown on the following map:

Date Collected09/23/2020
Date Released10/26/2020
File Size5.3 GiB
File DownloadDOI

We frequently perform spectrum scans from all available POWDER nodes. The scans cover all sub-6GHz frequencies. The resulting data is archived and can be downloaded for analysis. The data is also useful to look at activity within the bands POWDER can operate in.

Date CollectedSince August 2020
View/DownloadScanning data

This dataset was collected on the POWDER platform by the GENESYS Lab at Northeastern University.

This dataset is supplementary to the article 'G. Reus-Muns, D. Jaisinghani, K. Sankhe and K. R. Chowdhury, "Trust in 5G Open RANs through Machine Learning: RF Fingerprinting on the POWDER PAWR Platform," IEEE Globecom, 7-11 December 2020, Taipei, Taiwan.'

Date Created09/10/2020
File DownloadPOWDER-4BS-IQsample

This massive MIMO dataset was collected by the RENEW team from Rice University using a mMIMO array set up in an anechoic chamber at the POWDER platform. In Full-Duplex systems, one of the main challenges is self-interference where outgoing transmissions essentially "drown" the incoming signals. This dataset measured the self-interference across all radios on a massive MIMO base station comprised of 48 radios. The RENEW Sounder tool was used to continuously send pilots from each antenna, in round robin fashion, while all other antennas listened to those transmissions.

Date Created17/11/2021
File DownloadFull-Duplex Massive MIMO dataset
Salt Lake City skyline