PI: Oleg Sysoev, Linköping University
co-PI: Ove Edfors, Lund University
Wireless sensing in distributed multiple-input multiple-output (D-MIMO) systems is an emerging research direction which opens new opportunities for sensing tasks such as localization or intrusion detection. Compared to existing sensing methods based on wireless sensor networks, D-MIMO offers much greater computational opportunities without the need for any additional equipment. This project aims to improve the state-of-the-art sensing by combining realistic data from a unique D-MIMO testbed at Lund University with advanced analytical frameworks. We will focus on anomaly/outlier detection by D-MIMO sensing – a task that has a clear connection to national security aspects. Our project will be based on machine learning (ML) and statistical modeling, theoretical analysis, development of distributed implementation strategies and evaluation in realistic propagation environments.
Project number: G9