FURI | Spring 2024

Data Set Design, Generation, and Analysis for Deep MIMO and DeepSense 6G with Machine Learning

Due to recently granted access to broader airwave bands, there has been significant motivation to research more complex digital encoding and novel capabilities for our future 6G wireless communication environment. The transition from 5G to 6G using AI/ML is critical as our future wireless systems will boost the development of emerging technologies like smart cities, driverless cars, augmented reality, and more robust mobile networks. However, prior to making this shift, it is critical to build and test these communication algorithms on robust datasets. This study aims to investigate 3D models/ray-tracing software to more effectively generate real-world based indoor/outdoor models and datasets, compare its accuracy to data generated in the real world, and finally explore how information in these datasets can be leveraged to build secure wireless communication systems for the future.