Abstract

This article presents the DeepSense 6G data-set, which is a large-scale dataset based on real-world measurements of co-existing multi-modal sensing and communication data. The Deep-Sense 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.

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            @ARTICLE{10144504,
    author={Alkhateeb, Ahmed and Charan, Gouranga and Osman, Tawfik and Hredzak, Andrew and Morais, Joao and Demirhan, Umut and Srinivas, Nikhil},
    journal={IEEE Communications Magazine}, 
    title={DeepSense 6G: A Large-Scale Real-World Multi-Modal Sensing and Communication Dataset}, 
    year={2023},
    volume={61},
    number={9},
    pages={122-128},
    keywords={Sensors;6G mobile communication;Data collection;Millimeter wave communication;Laser radar;Wireless communication;Global Positioning System},
    doi={10.1109/MCOM.006.2200730}}