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In this paper we present DISC, a dataset of millimeter-wave channel impulseresponse measurements for integrated human activity sensing and communication.This is the first dataset collected with a software-defined radio testbed thattransmits 60 GHz IEEE 802-11ay-compliant packets and estimates the channelresponse including reflections of the signal on the moving body parts ofsubjects moving in an indoor environment. The provided data contain thecontribution of 7 subjects performing 4 different activities. Differently fromavailable radar-based millimeter-wave sensing datasets, our measurements arecollected using both uniform packet transmission times and sparse trafficpatterns from real Wi-Fi deployments. Thanks to these unique characteristics,DISC serves as a multi-purpose benchmarking tool for machine learning-basedhuman activity recognition, radio frequency gait analysis, and sparse sensingalgorithms for next-generation integrated sensing and communication.

DISC: a Dataset for Integrated Sensing and Communication in mmWave Systems