  RF fingerprinting is emerging as a physical layer security scheme to identify
illegitimate and/or unauthorized emitters sharing the RF spectrum. However, due
to the lack of publicly accessible real-world datasets, most research focuses
on generating synthetic waveforms with software-defined radios (SDRs) which are
not suited for practical deployment settings. On other hand, the limited
datasets that are available focus only on chipsets that generate only one kind
of waveform. Commercial off-the-shelf (COTS) combo chipsets that support two
wireless standards (for example WiFi and Bluetooth) over a shared dual-band
antenna such as those found in laptops, adapters, wireless chargers, Raspberry
Pis, among others are becoming ubiquitous in the IoT realm. Hence, to keep up
with the modern IoT environment, there is a pressing need for real-world open
datasets capturing emissions from these combo chipsets transmitting
heterogeneous communication protocols. To this end, we capture the first known
emissions from the COTS IoT chipsets transmitting WiFi and Bluetooth under two
different time frames. The different time frames are essential to rigorously
evaluate the generalization capability of the models. To ensure widespread use,
each capture within the comprehensive 72 GB dataset is long enough (40
MSamples) to support diverse input tensor lengths and formats. Finally, the
dataset also comprises emissions at varying signal powers to account for the
feeble to high signal strength emissions as encountered in a real-world
setting.
