Professor Trung Duong, Queen's University Belfast

Consider these startling statistics (from CISCO): global mobile data traffic is increasing exponentially and it is expected that there will be 100 Billion ‘Internet-of-Things’ devices by the year 2025. Thus, the need for improved wireless reliability and latency is greater than ever. However, implementing algorithms to ensure low-latency communication for massive numbers of power-constrained mobile devices conflicts directly with the need for ultra-reliability. The proposed project will address this challenge by developing original signal processing approaches that employ advanced optimisation, machine learning, and signalling in order to generate novel optimisation solvers – the main project aim is to guarantee ultra-reliable real-time communication and simultaneously serve a massive number of users. While it is unknown if wireless systems can deliver high quality-of-service targets to a massive number of IoT devices, our ambitious goal is to overturn an apparent truism in the design of future wireless network, i.e. “the number of users being served cannot exceed the number of transmit antennas at a base station”. This radically different approach to mathematical optimisation breaks entirely new ground in wireless network-enablement. Potentially, the approach will assist in meeting the increasing bandwidth demand and thirst for ever more computing resources required by massive IoT devices. In turn, the approach will enable real-time applications with ultra-reliability such as autonomous vehicles, smart energy, public safety and augmented reality - these applications require response times in the order of few milliseconds to microseconds.