Intelligent wireless edge networks: Theories and applications

(Note: Dr. Tse-Tin Chan was the Principal Investigator of this project. After Dr. Chan moved from HSUHK to EdUHK on August 1, 2022, the Principal Investigator was transferred to Dr. Kin-Hon Ho to meet the funding eligibility. Currently, Dr. Chan is the Co-Investigator of this project.) This project is supported by the Research Matching Grant Scheme of the Research Grants Council of Hong Kong and in-kind donations from industrial partners with a total amount of HKD 13,338,000. (HKD 6,669,000 from the Research Grants Council of Hong Kong and HKD 6,669,000 in-kind donations from industrial partners.) With the rapid growth of smart Internet of Things (IoT) devices, intelligent wireless edge networks have been receiving significant attention. Intelligent wireless edge networks enable distributed edge learning to support artificial intelligence (AI) applications on various end devices. Distributed edge learning overcomes the limited computing power, energy resources, and data on end devices. It also significantly reduces latency compared to conventional machine learning approaches that require training data and inference processes to be centralized in a data center or on a cloud. With the advanced development of wireless networks, we expect more powerful network intelligence to emerge in the future. However, there are many challenges with intelligent wireless edge networks. In this project, we focus on the following objectives. (1) To establish theoretical frameworks for low-latency wireless edge networks; (2) To develop new communication schemes and networking solutions for the intelligent Internet of Things (IoT); (3) To build prototypes and applications for wireless edge intelligence. If the research project yields favorable outcomes, it will be a great advance in the theory and practice of supporting next-generation intelligent wireless edge networks.

Funding Source: UGC - Other Specific Funds/Earmarked Grants^