IQ signals captured from multiple Sub-GHz technologies

The dataset was captured using a RTL-SDR at a sampling rate of 2.048 MHz using coaxial cables. Two center frequencies (864.0 MHz and 867.4 MHz) were considered to cover all considered channels of the wireless Sub-GHz technologies. The following settings for the various technologies have been considered: | Technology | Center frequency | Bandwidth | Modulation / setting | | -------- | -------- | -------- | -------- | | LoRa | 868.1 MHz | 125 MHz | Spread spectrum SF 7 | | | 868.1 MHz | 125 MHz | Spread spectrum SF 12 | | Sigfox | 868.2 MHz | 100 Hz | BPSK (400 chan.) | | IEEE 802.11ah | 863.5 MHz | 1 MHz | MCS 0, 10 (BPSK) and 7 (64-QAM) | | | 864.0 MHz | 2 MHz | MCS 0 (BPSK) and 7 (64-QAM) | | | 864.5 MHz | 1 MHz | MCS 0, 10 (BPSK) and 7 (64-QAM) | | | 866.0 MHz | 2 MHz | MCS 0 (BPSK) and 7 (64-QAM) | | IEEE 802.15.4 SUN-FSK | 868.1 MHz | 200 KHz | BFSK | | IEEE 802.15.4 SUN-OFDM | 863.625 MHz | 1.2 MHz | MCS 2 (OQPSK) | | | 863.425 MHz | 800 KHz | MCS 2 (OQPSK) | | | 863.225 MHz | 400 KHz | MCS 2 (OQPSK) | | | 863.125 MHz | 200 KHz | MCS 2 (OQPSK) | | | 863.125 MHz | 200 KHz | MCS 6 (16-QAM) | The dataset consist of multiple .mat files, which can be read with Matlab or with Python using the following code:
import scipy.io mat = scipy.io.loadmat('80211ah_mcs0_chan1_g0.0dB_att10dB_freq864.0MHz_0.mat') IQ_samples = mat["IQ_samples"][0]

IQ_samples will be a numpy array containing IQ data sampled at 2.048 msps.