DeepSense 6G: A Large-Scale Real-World Multi-Modal Sensing and Communication Dataset
This dataset addresses the need for reproducible and adoptable resources in the intersection of multi-modal sensing, communication, and positioning, primarily for researchers in deep learning and 6G technologies, but it is incremental as it builds on existing data collection efforts.
The authors tackled the lack of large-scale real-world datasets for multi-modal sensing and communication by introducing the DeepSense 6G dataset, which includes detailed measurements and methodologies to support deep learning research in this area.
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.