Enabling Accurate Ray-Tracing Predictions for 5G Communication Channels

实现 5G 通信通道的准确光线追踪预测

• 批准号: 552711-2020
• 负责人: Sarris, Costas
• 金额: $ 4.37万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=704760
• 关键词: Enabling; Accurate; Ray; Tracing; Predictions

Planning and installation of wireless systems in private and public spaces, indoor and outdoor, has primarily relied on measurements and empirical models. However, the emergence of next-generation communication systems and the proliferation of the Internet of Things (IoT), create a wireless ecosystem of unprecedented complexity. Moreover, considering the present challenges that Canadians are facing at the time of a pandemic, it is hard to overstate the importance of intelligent design tools for wireless communication, sensing and monitoring systems in hospitals, schools, retirement homes and other public spaces. Wireless systems offer contact-less monitoring that is compatible with social distancing rules, at the cost of adding interfering signals to other systems and contributing to the radiation exposure of vulnerable groups in confined spaces. This project will produce high-fidelity and computationally efficient simulation techniques for modeling electromagnetic wave propagation in complex environments for existing, emerging and future wireless communication systems, including communication systems of fifth generation (5G) and beyond. Such techniques can predict the signal levels created by a system of transmitters in a given environment. They can be used to optimize the position of network access points, assess interference from and towards neighboring systems, evaluate user exposure to electromagnetic radiation and perform network performance studies. The project is based on a partnership between a University of Toronto research group with a long track record in propagation modeling for wireless communication systems, with iBwave, a Canadian company that is dedicated to improving in-building wireless network design.

在私人和公共空间、室内和室外规划和安装无线系统，主要依靠测量和经验模型。然而，下一代通信系统的出现和物联网(IoT)的激增，创造了一个前所未有的复杂的无线生态系统。此外，考虑到加拿大人在大流行时期面临的当前挑战，很难夸大医院、学校、养老院和其他公共场所无线通信、传感和监控系统的智能设计工具的重要性。无线系统提供符合社交距离规则的非接触式监测，但代价是向其他系统添加干扰信号，并导致受限空间中脆弱群体的辐射暴露。 该项目将产生高保真和计算高效的仿真技术，用于为现有的、新兴的和未来的无线通信系统(包括第五代(5G)及更高级别的通信系统)在复杂环境中建模电磁波传播。这种技术可以预测发射机系统在给定环境中产生的信号电平。它们可用于优化网络接入点的位置、评估来自和指向邻近系统的干扰、评估用户暴露在电磁辐射中以及执行网络性能研究。该项目是基于多伦多大学一个在无线通信系统传播建模方面有着长期记录的研究小组与致力于改进建筑内无线网络设计的加拿大公司iBwave之间的合作关系。