  This article presents the DeepSense 6G dataset, which is a large-scale
dataset based on real-world measurements of co-existing multi-modal sensing and
communication data. The DeepSense 6G dataset is built to advance deep learning
research in a wide range of applications in the intersection of multi-modal
sensing, communication, and positioning. This article provides a detailed
overview of the DeepSense dataset structure, adopted testbeds, data collection
and processing methodology, deployment scenarios, and example applications,
with the objective of facilitating the adoption and reproducibility of
multi-modal sensing and communication datasets.
