The data was measured in the Communications Laboratory in the Department of Electrical and Computer Engineering at University of Minnesota - Twin Cities.
Scenario Description: We have used the data to test spectra separation algorithms in cognitive radio networks. The scenario is as follows: there are multiple licensed and unlicensed transmitters transmitting simultaneously and some cognitive radio receivers try to determine what are the spectral occupancy situation of each transmitter. At the same time, the receivers also try to localize the transmitters. Detailed description of the acquisition process and environment of the data can be found in [1] below.
The data and a demo script can be downloaded from this link (311 MB). The data was measured and collected by Dr. John H. Tranter and the script was programmed by and John and Xiao. Please contact xfu@umn.edu if any bug is identified.
References:
[1] X. Fu, N. D. Sidiropoulos, J. H. Tranter, and W.-K. Ma, “A factor analysis framework for power spectra separation and multiple emitter localization,” IEEE Transactions on Signal Processing, vol. 63, no. 24, Dec. 2015
[2] X. Fu, N. D. Sidiropoulos, W.-K. Ma, and J. Tranter, “Blind spectra separation and direction finding for cognitive radio using temporal correlation-domain ESPRIT,” in Proc. ICASSP 2014, Florence, Italy, May 2014
[3] X. Fu, N. D. Sidiropoulos, and W.-K. Ma, “Power spectra separation via structured matrix factorization,” IEEE Transactions on Signal Processing, vol. 64, no. 17, pp. 4592-4605, Sept., 2016.