Resource allocation for emerging applications of wireless communication networks

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The previous generations of mobile networks have had a transformative impact on the way that people across the globe live their lives. While the imminent fifth generation, and future generations, will continue to enrich the user experience of familiar applications, it is envisioned that the truly transformative impacts of those generations will appear in other, emerging, applications. Those "use cases" will include the massive machine-type communications that are envisioned for the "Internet of Things", and the latency-constrained "mission-critical" communications that will enable wireless control of autonomous vehicles, robots, drones, and remote surgical systems, and will facilitate mobile augmented and virtual reality systems. To enable such applications, the long-standing traditions of wireless communication system design are being revisited. The goal of the proposed research program is to develop design insights and practical algorithms that will enable the wireless networks of the future to dynamically allocate their resources so that they can meet the demands of these emerging applications. Fundamentally, the design of wireless communication networks involves making judicious trade-offs between different aspects of their performance, including data rate (spectral efficiency), reliability, energy consumption, complexity and latency. In previous generations of mobile networks, the design trade-offs have typically been made from the operator's perspective, with the key metrics capturing the long-term performance, averaged over all users. While that strategy was well tailored to the "human-scale" mobile applications that we now find familiar, in order to incorporate the emerging "machine-scale" applications, the way that these trade-offs are made must be re-imagined. In particular, the key metrics must capture the full distribution of the short-term performance of the individual devices in the network, and not just the long-term average. The proposed research program will combine insights from information theory, communication theory and signal processing to conceive of network topologies, signaling frameworks, and receiver structures that will provide communication resources that have the potential to support the envisioned machine-scale applications. It will also combine insights from those fields with insights from mathematical optimization to develop efficient algorithms that effectively allocate, those communication resources in real time, and hence enable the vision to be realized. The main outcomes of the proposed research program will be the development of broadly applicable design guidelines and resource allocation algorithms, along with highly-qualified personnel who will be able to leverage these ideas, and those of others, as they take the opportunity provided by the emerging machine-scale applications to lead a resurgence in the Canadian wireless communications industry.