Reconfigurable Intelligent Surface (RIS) Empowered Future Wireless Networks

下一代无线系统的关键驱动因素来自技术驱动的范式转变和现有无线网络的持续发展，以及沉浸式虚拟现实、互联机器人和自主系统等高带宽和超低延迟应用。这些应用对数据速度、计算、连接和能谱效率的要求提出了新的挑战。可重构智能表面(RIS)是一种新的无线通信模式，被认为是支持此类应用的一种很有前途的使能器。当RIS与海量物联网、具有边缘智能和计算的增强型小蜂窝、数据驱动的智能网络控制、综合空中-地面网络和太赫兹回程等关键技术集成时，将具有实现高性能无线信息社会网络的巨大潜力。它为无线系统工程、设计和优化提供了大量的机会。现有的关于RIS技术的研究在许多领域仍然是原始的。当边缘计算、空中通信、物联网与IRS相结合时，我们将利用无线通信、排队模型、优化、决策理论和机器学习等强大工具，解决资源分配、传输和海量接入问题中的许多挑战。因此，拟议的研究计划旨在利用基于优化的传输和多址技术，以及在网络控制和管理中基于学习的数据驱动决策，来设计和开发用于紧密耦合的异质网络中的RIS辅助无线通信的先进和实用技术。具体来说，我们将：(I)开发在密集网络中使用分布式边缘智能的计算框架，并与RIS一起用于低延迟应用；(Ii)设计可扩展的共生无线电网络，以有效利用资源并为物联网设备提供海量接入；(Iii)通过利用先进的传输和接入技术，在RIS集成的空中-地面网络中发展无处不在的大容量通信；以及(Iv)为RIS系统开发主动方案，使其在能量上自我维持，在配置和管理上自组织。这将提高无线网络的容量和覆盖范围，并在下一代无线系统中提供强大的服务质量和可靠的连接。这项研究产生的新的理论贡献和创新技术将对RIS辅助通信的发展产生重大影响。这项研究计划中的新技术和新技术的发明将为加拿大的ICT战略产业培育至关重要的竞争优势，并为加拿大带来重大的科学、经济和社会效益。

The key drivers of next generation wireless system come from the technology-driven paradigm shift and the continuous evolution of the existing wireless networks, along with bandwidth-hungry and ultra-low latency applications such as immersive virtual reality, connected robotics and autonomous systems. These applications pose new challenges to the requirements of data speed, computing, connectivity, and energy-spectral efficiency. Reconfigurable intelligent surfaces (RIS) is a new wireless communication paradigm and is considered a promising enabler to support such applications. RIS when integrated with key technologies such as massive IoT, enhanced small cells with edge intelligence and computing, data-driven intelligent network control, integrated aerial-terrestrial network, and THz backhauling has huge potential to realize high performance wireless information societal networks. It opens up a plethora of opportunities in wireless system engineering, design and optimization. Existing studies on the RIS technology are still primitive in many areas. We will tackle many challenges in resource allocation, transmission and massive access problems when integrating edge computing, aerial communication and IoT with IRS, using powerful tools from wireless communication, queuing models, optimization, decision theory and machine learning. The proposed research program therefore seeks to focus on the design and development of advanced and practical technologies for RIS-aided wireless communication in tightly coupled heterogeneous networks utilising optimization-based transmission and multiple access techniques, and learning-based data-driven decisions in network control and management. In particular, we will: (i) Develop a computing framework using distributed edge intelligence in dense networks with RIS for low-latency applications; (ii) Design scalable symbiotic radio network to efficiently utilize resources and provide massive access for IoT devices; (iii) Develop ubiquitous high-capacity communication in RIS-integrated aerial-terrestrial networks by exploiting advanced transmission and access technologies, and (iv) Develop proactive schemes for RIS systems to be self-sustaining in energy, and self-organizing in configurations and management. This will improve wireless network capacity and coverage, and provide robust quality of service and reliable connectivity in the next generation wireless systems. Novel theoretical contributions and innovative technologies resulting from the proposed research will have significant impact on the evolution of RIS-aided communication. Invention of new techniques and technologies from this research program will foster vital competitive edge to strategic Canadian ICT industry, and bring significant scientific, economic and social benefits to Canada.