Intelligent Modeling and Design of Medium to Large Scale Microwave and Millimeter-Wave Circuits for Communication Systems

通信系统中大规模微波和毫米波电路的智能建模和设计

• 批准号: RGPIN-2017-05872
• 负责人: Wang, Ying
• 金额: $ 2.04万
• 依托单位: University of Ontario Institute of Technology
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 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=711443
• 关键词: Intelligent; Modeling; Design; Medium; Large

Demands, such as extremely high data rates, are driving new technology development toward the higher end of microwave spectrum and the millimeter-wave spectrum, resulting in new challenges. At the same time, design and optimization at such high frequency rely on efficient computer aided design (CAD) techniques, which is especially true for medium and large scale design problems. The objectives of the proposed research program are to develop intelligent modeling techniques and optimization methods for medium to large scale microwave and millimeter-wave circuits and systems, and to apply these CAD techniques to the development of innovative and high performance circuits for next generation satellite and wireless communication systems. The research program will focus on the following areas. (1) Effective synthesis method and efficient and accurate wideband models will be developed for new multiplexing network configurations for applications in satellite communications. The developed CAD methods will be applied to medium to large-scale designs, including the development of new tunable multiplexers. (2) Intelligent modeling techniques will be developed for antenna arrays, allowing iterative design optimizations. The models will be applied to the development of highly efficient medium to large-scale millimeter-wave antenna arrays, and to the investigations of reconfigurability of the arrays, exploring microelectromechanical systems (MEMS) technology and advanced material, such as carbon-nanotube (CNT). In this research program, the modeling techniques build on efficient integrations of full wave simulations, distributed circuit models and/or neural networks, to accurately and quickly model the circuit behavior over a wide frequency range, and to further enable optimization with high efficiency. Each circuit/system has its own characteristics and design challenge. Different methods, such as artificial neural network, machine learning, and surrogate-based optimization techniques, will be effectively combined taking into account the specific characteristics of the circuits and design goals. The microwave and mm-wave circuits and systems focused on in this research program find important applications in space and ground based communications systems, as well as in imaging systems, sensors and automotive radar. The proposed research program is expected to make significant contributions in the field of CAD, and to the development of advanced and innovative circuits and systems, in both theoretical research and practical applications. The outcomes of the research can enhance competitiveness of the Canada's high-tech industry in the global market through development of new technologies and improvement of design capabilities. Furthermore, the expertise gained by HQP is valuable to Canadian industries, especially the information and communication technology sector.

极高数据速率等需求正在推动新技术向微波频谱和毫米波频谱的高端发展，从而带来新的挑战。同时，在如此高的频率下的设计和优化依赖于高效的计算机辅助设计（CAD）技术，这对于中型和大型设计问题尤其如此。 拟议的研究计划的目标是开发智能建模技术和优化方法，用于中到大规模的微波和毫米波电路和系统，并将这些CAD技术应用于下一代卫星和无线通信系统的创新和高性能电路的开发。研究计划将集中在以下几个方面。(1)有效的综合方法和有效的和准确的宽带模型将被开发用于卫星通信中的新的复用网络配置。所开发的CAD方法将被应用于中到大规模的设计，包括新的可调多路复用器的开发。(2)将为天线阵列开发智能建模技术，允许迭代设计优化。这些模型将被应用于开发高效的中到大规模毫米波天线阵列，并研究阵列的可重构性，探索微机电系统（MEMS）技术和先进材料，如碳纳米管（CNT）。在这项研究计划中，建模技术建立在全波仿真，分布式电路模型和/或神经网络的有效集成之上，以准确，快速地在宽频率范围内对电路行为进行建模，并进一步实现高效优化。每个电路/系统都有自己的特点和设计挑战。不同的方法，如人工神经网络，机器学习和基于代理的优化技术，将有效地结合考虑到电路和设计目标的具体特点。 该研究计划重点关注的微波和毫米波电路和系统在空间和地面通信系统以及成像系统，传感器和汽车雷达中具有重要应用。该研究计划预计将在CAD领域做出重大贡献，并在理论研究和实际应用中开发先进和创新的电路和系统。研究结果可以通过开发新技术和提高设计能力来提高加拿大高科技产业在全球市场上的竞争力。此外，HQP获得的专业知识对加拿大工业，特别是信息和通信技术部门很有价值。