Machine Learning Aided Self-Estimation of Device Position in Cellular IoT Networks

The research program in this project aims at advancing the use of cellular communications for Internet-of-Things applications. The academic researchers and the partner organization have identified three work items that revolve around the self-estimation of cellular IoT devices (1) to improve energy and spectrum efficient transmission of short and intermittent data packets, (2) to enable cellular non-terrestrial communication with low-cost devices, and (3) to help realize tracking applications that can benefit from device-to-device communication. The research is closely aligned with IoT use cases supported through IoT connectivity solutions and cloud-based services by the partner organization and with ongoing standardization efforts for 5G cellular communication technology.

Intern: 
Gautham Prasad;Vishnu Rajendran Chandrika
Faculty Supervisor: 
Lutz Lampe
Province: 
British Columbia
Partner: 
Partner University: 
Program: