Synthetic Data for Data-Driven Wireless
Published in Proceedings of the 30th Annual International Conference on Mobile Computing and Networking, 2024
Abstract
The fundamental bottleneck in adapting data-driven wireless solutions to real world is the lack of tools for augmenting good quality data which is environment-specific. Indeed, much of the data required for popular data-driven wireless communication and sensing systems requires domain expertise beyond the reach of an average consumer. This demo presents a radical new vision for generating synthetic data in consumer-specific environments by leveraging the power of modern compute.
This demo presents a vision for consumer-facing wireless tools that can augment synthetic data for development and adaptation of data-driven wireless systems. Our solution leverages existing ray-tracing based wireless simulators in a new way to map and visualize the coverage in three key use-cases for this technology. Further, we motivate the need for development of such tools for generating synthetic data is vital towards a broader vision of foundational wireless models for data-driven wireless communication and sensing systems.
Recommended citation: Qiancheng Li, Xinghua Sun, and Akshay Gadre. 2024. Demo : Synthetic Data for Data-Driven Wireless. In Proceedings of the 30th Annual International Conference on Mobile Computing and Networking (ACM MobiCom ‘24). Association for Computing Machinery, New York, NY, USA, 2303–2305. https://doi.org/10.1145/3636534.3701545
Recommended citation: Qiancheng Li, Xinghua Sun, and Akshay Gadre. 2024. Demo : Synthetic Data for Data-Driven Wireless. In Proceedings of the 30th Annual International Conference on Mobile Computing and Networking (ACM MobiCom '24). Association for Computing Machinery, New York, NY, USA, 2303–2305. https://doi.org/10.1145/3636534.3701545
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