Guoda Tian defends his thesis: Navigating the future — Machine learning for wireless sensing and localization.

Cellular-based localization and sensing pave the way for a variety of applications across various domains, ranging from autonomous driving to emergency care and intelligent traffic management. Although traditional methods have been effective, they still face challenges such as the requirement for highly accurate models and the inherent complexity of the algorithms. This thesis explores the potential of integrating machine learning (ML) techniques to augment the performance of sensing and localization systems. Three main topics are covered by this thesis, namely, ML-aided channel estimation, sensing, and localization.

 

Link to thesis i LU Research Portal:

https://portal.research.lu.se/sv/publications/navigating-the-future-machine-learning-for-wireless-sensing-and-l

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