Grant: Alliance Grants

The increasing data traffic and number of devices necessitates efficient network access and resource management technologies for Internet of Things (IoT) in 6G wireless networks. In symbiotic radio networks (SRN), secondary IoT users share spectrum resources with the primary system, and hence benefit from multipath diversity and multiplexing gains. As an emerging data-driven AI-based technology, digital twin creates a real-time virtual layer of a physical network and its components, enabling instantaneous simulation, monitoring, and optimization of IoT devices in SRNs. With a properly constructed digital twin, network resources can be allocated more quickly, efficiently and accurately lessening the network capacity crunch and improving quality of service to end users and devices. In this Alliance project, we will (i) investigate the structure of the optimal multiple access and resource management framework, (ii) understand the limits of integrating massive IoT with symbiotic radio in future wireless networks, and (iii) characterize the performance gains due to potential multiplexing and transmission diversity within the digital twin for SRNs. The objective is to develop a scalable and accurate digital twin framework for IoT networks in sensor-based radio network using stochastic optimization techniques and learning technologies in collaboration with the University of London. The proposed research project will provide an environment for training HQP to gain critical engineering skills and solid scientific methodologies in information and communication technology sector. The invention of new techniques and technologies will foster a vital competitive edge for the Canadian telecommunications industry and thus enhance Canada's position as a leader in wireless communication and mobile networking.