During the first half of 2020, the COVID-19 pandemic changed the social gathering lifestyle to online business and social interaction. The worldwide imposed travel bans and national lockdown prevented social gatherings, making learning institutions and businesses to adopt an online platform for learning and business transactions. This development led to the incorporation of video conferencing into daily activities. This data article presents broadband data usage measurement collected using Glasswire software on various conference calls made between July and August.

The dataset contains:
1. We conducted a A 24-hour recording of ADS-B signals at DAB on 1090 MHz with USRP B210 (8 MHz sample rate). In total, we got the signals from more than 130 aircraft.
2. An enhanced gr-adsb, in which each message's digital baseband (I/Q) signals and metadata (flight information) are recorded simultaneously. The output file path can be specified in the property panel of the ADS-B decoder submodule.
3. Our GnuRadio flow for signal reception.
4. Matlab code of the paper, wireless device identification using the zero-bias neural network.

Measurement method and Built-In Self-Test (BIST) circuit architecture exploiting Compressive Sampling for frequency response characterization of Digital-to-Analog Converters

There has been extensive modelling of the optical wireless channel, and the optimum modulation scheme for a particular channel is well-understood. However, this modelling has not taken into account the trade-offs that transmitter and receiver selection usually involve. For a particular type of transmitter, the modulation bandwidth and available power are closely related, as are receiver bandwidth, active area and sensitivity. In this paper, we present a design approach that takes this device selection into account.