This project studies and develops new techniques to support the emerging time-critical communications for the future Internet of things (IoT) in 5G and 6G wireless generations. Timely delivery of information (i.e., status updates) from low-power sensors to a destination is needed for, e.g., industrial control, surveillance in smart homes, and drone control. The timeliness can be measured by age of information (AoI). The project develops different sampling, quantization, coding, transmission, and estimation techniques that improve the information freshness (i.e., minimize the AoI) while advocating low-energy communications in time-critical IoT systems. The analytical tools used in the project are optimization, quantization, compressed sensing, machine learning, and queueing theory. The project is expected to influence the development and implementation of novel AoI-aware low-energy IoT solutions to enable various real-time control applications in 5G and 6G networks.

2021

2023