DeepSense 6G: A Large-Scale Real-World Multi-Modal Sensing and Communication Dataset

TL;DR

DeepSense 6G is a comprehensive large-scale dataset combining multi-modal sensing and communication data, designed to support advanced deep learning research in 6G wireless systems and related applications.

Contribution

The paper introduces the DeepSense 6G dataset, a large-scale real-world dataset for multi-modal sensing and communication, facilitating research and reproducibility in 6G deep learning applications.

Findings

Dataset covers diverse deployment scenarios

Includes multi-modal sensing and communication data

Supports various deep learning applications

Abstract

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.