Grant: Discovery Grants Program - Individual

With the wireless communications heading to the next generation (6G), the emergence of resource-intensive and computing-intensive immersive interactive applications, such as VR and digital twin, demands ultra-high reliability, ultra-low latency, and immersive quality of experience. Although breakthroughs in physical layer technologies, such as massive MIMO, Terahertz communications, and reconfigurable intelligent surface (RIS), keep occurrence to continuously increase the network capacity and transmission rate, these technologies only are far from, or even impossible, satisfying the future application requirements with data transmission rate =100 Gbps, reliability =99.99999%, and latency =1 ms. This asks for novel network management and optimization approaches that will span across all network segments. This research program aims to tackle the aforementioned challenges through studying and developing novel radio resource management techniques. Together with my HQP, we intend to address three critical open issues, including (i) designing nonlinear online incentive mechanisms to promote the active participation of all network entities, while ensuring truthfulness and ethical equity; (ii) designing online and distributive service displacement protocols with focus on fostering network-wide cooperation; and (iii) designing flexible and effective prediction algorithms for achieving ultra-low round-trip latency. Research emphases will be put on addressing challenges raised from practical applications, including hierarchy resource management involving multiple entities, multi-dimensional resource allocation, limited resource budgets, dynamic network environments, and high computational complexity. The key tasks in this research are to 1) develop novel algorithms and protocols for online incentive mechanism design, distributive service displacement, and effective prediction through an in-depth joint investigation from both theory and systems; 2) adopt advanced mathematical models and machine learning techniques in order to facilitate the development of more effective and efficient network management protocols; and 3) use simulation-based approaches to evaluate the performance of the proposed analytical frameworks and management algorithms. The proposed research will achieve breakthroughs in wireless communication network technology, is significant to foster a vital competitive edge for Canadian Information and Communication Technology industry in the international marketplace, and will result in significant benefits to Canadian users, including access to new wireless services and an enhanced quality of experience.