Resource allocation for emerging applications of wireless communication networks

无线通信网络新兴应用的资源分配

• 批准号: RGPIN-2020-06832
• 负责人: Davidson, Timothy
• 金额: $ 3.35万
• 依托单位: McMaster University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=741462
• 关键词: Resource; allocation; emerging; applications; wireless

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.

前几代移动的网络对地球仪人们的生活方式产生了变革性的影响。虽然即将到来的第五代和未来几代将继续丰富熟悉应用程序的用户体验，但可以预见，这几代真正的变革性影响将出现在其他新兴应用程序中。这些“用例”将包括为“物联网”设想的大规模机器类型通信，以及延迟受限的“关键任务”通信，这些通信将实现对自动驾驶车辆、机器人、无人机和远程手术系统的无线控制，并将促进移动的增强和虚拟现实系统。为了实现这样的应用，正在重新审视无线通信系统设计的长期传统。拟议研究计划的目标是开发设计见解和实用算法，使未来的无线网络能够动态分配资源，以便满足这些新兴应用的需求。 从根本上说，无线通信网络的设计涉及在其性能的不同方面之间做出明智的权衡，包括数据速率（频谱效率）、可靠性、能耗、复杂性和延迟。在前几代移动的网络中，通常从运营商的角度进行设计权衡，关键指标捕获所有用户的平均长期性能。虽然这一策略是针对我们现在熟悉的“人类规模”的移动的应用程序量身定制的，但为了融入新兴的“机器规模”应用程序，必须重新想象这些权衡的方式。特别是，关键指标必须捕获网络中各个设备的短期性能的完整分布，而不仅仅是长期平均值。 拟议的研究计划将结合联合收割机的见解，从信息理论，通信理论和信号处理，设想网络拓扑结构，信令框架和接收器结构，将提供通信资源，有可能支持设想的机器规模的应用。它还将把来自这些领域的联合收割机见解与来自数学优化的见解结合起来，以开发有效的算法，有效地分配真实的时间的通信资源，从而使愿景得以实现。拟议的研究计划的主要成果将是广泛适用的设计准则和资源分配算法的发展，沿着高素质的人员谁将能够利用这些想法，和其他人，因为他们采取了新兴的机器提供的机会规模的应用程序，导致在加拿大无线通信行业的复苏。