Advanced modeling and optimization methodologies for design of high-frequency electronic components and subsystems

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The objective of this research is to develop new methodologies for modeling/optimization of high-frequency electronic components and packages in wireless and wireline communication systems. At high signal frequency, modeling and optimization of the electromagnetic behavior in devices /systems are vital. This task becomes computationally prohibitive as the complexity of the electromagnetic structure increase and optimization is applied. For yield-driven design with random variations in physical/geometrical parameters in the system, the computational difficulty is further compounded. The proposed research will address these challenges. Built on top of our advances in neural network technologies for microwave design, this research will open several new frontiers in the area: a new category of training algorithms using both electromagnetic response and electromagnetic sensitivity, a new category of behavioral modeling of nonlinear devices using state-space estimation and state-space training of dynamic neural models, fundamentally new formulations of neural based parametric electromagnetic modeling exploiting spatial relationship of components. The work will be further elevated by neural based multidisciplinary electrical/electromagnetic/thermal modeling and design. The long term direction is towards a unified methodology for developing neural based models that are fast and accurate for design of next generation high-frequency components and systems. The long-term impact will be faster design cycle, lower design cost, and better design quality. It contributes to creating new knowledge and training of highly qualified technical personnel in areas of high-frequency electronic design. Applications in designing RF/microwave/millimeterwave circuits, and high-speed circuits and packages also contribute to strengthening the competitiveness our high-tech economy.