Grant: Discovery Grants Program - Individual
Carleton University
$59,200.00
Advanced modeling and optimization methodologies for design of high-frequency electronic components and subsystems
FY 2015-16
Summary
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.
Program
Discovery Grants Program - Individual
Recipient
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
122049-2009
Name nom
Zhang, QiJun
Department département
Electronics
Organization id
23
Institution établissement
Carleton University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2015
Competition year année de concours
2009
Award amount
59200
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
Discovery grants programs
Group fr
Programmes de subventions à la découverte
Committee code
1079
Committee name en
Electrical and Computer Engineering
Committee name fr
Génie électrique et de l'informatique
Area of application code
1207
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Information, computer and communication technologies
Area of application fr
Technologie de l'information, des ordinateurs et des réseaux de communications
Research subject code
2520
Research subject group en
Electrical and electronic engineering
Research subject group fr
Génie électrique et électronique
Research subject en
Microwave and millimeterwave devices, circuits and technologies
Research subject fr
Dispositifs, circuits et technologie hyperfréquences et d'ondes millimétriques
Partie
5
Nb partie
5
Application title
Advanced modeling and optimization methodologies for design of high-frequency electronic components and subsystems
Keyword
NSERC
Application summary
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.