Ultra-wide Band mm-Wave Components Design Based on Machine Learning Techniques

点击翻译按钮获取中文摘要

Future communication systems are heading toward the utilization of the mm-wave bands to provide a large**bandwidth for short distance communication. This type of networks is an essential part of the backbone that**supports both 5G standard and IOT applications. Such applications will result in a significant increase in the**number of access points. The current design methodologies cannot provide a large number of designs as fast as**required for such applications. At Scientific Microware Corporation (SMC), which is a worldwide known**Canadian corporation in the field of design and manufacturing of microwave and mm-wave components, the**design procedure of mm-wave components is time consuming in a way that it is not suitable for expected high**demand. Thus, the objective of this research is to address this problem and to propose some solutions that are**based on the latest advancement in the field of machine learning.**In this research, we are targeting to study machine learning techniques, and the mm-wave component design**process, in order to propose solutions that will speed up the design phase, and specifically, solutions that will**automate the design process by saving the historical data of previous designs that were accomplished at SMC**in order to exploit them in the future. This will automate the design process, and will shorten the time between**the reception of a demand and the production of a custom-made product.