5G wireless system is now available, but the academia needs to start a new research for the next generation of wireless networks. Definitely, AI will play a key role in 6G in PHY, MAC, and network layers. We are excited to start a new journey called AIR (Artificial Intelligence Radio)!
Network delay is one of the concerns in delivering multimedia data to mobile users. One way is to cache popular contents in base stations for better response and minimum delay. Then, the question would be: Which contents to cache and where? How often to refresh the caches? Can we do this in an energy efficient way?
Funded by NRF
Resource Management with Deep Learning
Resource management of 6G wireless will be way more complicated than before because of the increased number of devices, edges and cloud functions. Hence, the traditional approaches based on analytic modeling may no longer be possible. Instead, data-driven and deep learning based mechanism will be essential.
Funded by AIR
Wireless Edge Computing
Unlike traditional cloud-based systems, many functions are placed on the edge side of the networks in order to minimize the latency, to avoid network congestion and to guarantee the QoS. However, there are fundamental tradeoffs among energy-efficiency, latency, computing resource and performance, which leads to new optimization and game theoretic solutions.
Funded by NRF