Intelligent Reflecting Surface-enabled High-speed 6G Wireless Networks. Intelligent reflecting surface (IRS) is a ground-breaking wireless technology essential for the development of future sixth-generation (6G) wireless communication networks. This project aims to develop fundamental communication theories and practical solutions to characterise and optimise IRS-based communication. The project expects to design novel channel estimation, robust beamforming, resource allocation and analytical fr ....Intelligent Reflecting Surface-enabled High-speed 6G Wireless Networks. Intelligent reflecting surface (IRS) is a ground-breaking wireless technology essential for the development of future sixth-generation (6G) wireless communication networks. This project aims to develop fundamental communication theories and practical solutions to characterise and optimise IRS-based communication. The project expects to design novel channel estimation, robust beamforming, resource allocation and analytical framework to address the significant scientific challenges for the development of IRS for enabling high-speed 6G networks. These outcomes are expected to contribute to a new type of wireless infrastructure which paves the way for building and transforming the Australian information and communications technology industries.Read moreRead less
Multi-Modal Dictionary Learning for Smart City Operation and Management. This Project aims to provide new digital asset management tools for city councils to improve city services by utilising new sensing and automated learning technologies for recognising, tracking and auditing of assets. Currently, there are no digital tools available to handle these services. This project proposes new multi-modal sensing and mapping of city asset techniques by building new multi-modal dictionary learning proc ....Multi-Modal Dictionary Learning for Smart City Operation and Management. This Project aims to provide new digital asset management tools for city councils to improve city services by utilising new sensing and automated learning technologies for recognising, tracking and auditing of assets. Currently, there are no digital tools available to handle these services. This project proposes new multi-modal sensing and mapping of city asset techniques by building new multi-modal dictionary learning procedures. The new framework will recognise different conditions of city assets in real-time to make decisions. Expected outcomes of this Project include integration and easy access of assets with unique digital identities to help city councils, governments, and navigation services for real-time asset monitoring.Read moreRead less