5G Wireless Jamming Detection Dataset

This dataset is used for evaluating 5G Wireless Jamming Detection setups, and is suitable for binary classification task, i.e., it has got two classes: \Clean\ and \Noisy\/Jamming\. With respect to files in this dataset, there are 7 of them; one file \clean_signal_*.npy\ corresponds to clean signal transmission, and 6 \noisy_signal_*db_*.npy\ files that correspond to jamming signals at various levels of Eb\/N0 noise. Both clean and noisy signal files correspond to a transmitter\/receiver system with 2 antennas. There are 1000 samples in each file, and each signal in a file is 1016 time-steps long. One can use the 7 files to classify them as clean vs noisy\/jamming signals at various levels. That is, there can be 6 classification tasks in total, where e.g., one task could be to classify \clean_signal_*.npy\ and \noisy_signal_3dB_*.npy\. Note that the user has to assign binary classes to the files explicitly.