Utilizing Information Assets in RF and Microwave Engineering Workflows

To meet the demands of next generation wireless communication systems, engineering teams must build flexible, reconfigurable design processes, or workflows, which are able to incorporate and leverage existing information in new ways. The challenge: over the past few decades, Electronic Design Automation (EDA) software platforms have focused on building elaborate user interfaces which obscure the lower-level mechanisms now required to build such workflows. Recently, several vendors have provided access to their EDA toolsets through Application Programming Interfaces (APIs), and in doing so have enabled new possibilities for leveraging information in the engineering design process through automation. This paper studies specific areas in high frequency simulation and measurement where automation can dramatically increase productivity and enable novel solutions to difficult problems by allowing engineering teams to use existing data which was previously inaccessible. Four examples are highlighted: netlist data mining, image-based physical modeling, simulation model extraction from measured data, and improved simulation and measurement speed using AI image completion. Theme: utilizing existing data and streamlining design through automation

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Publication Details

Published
2025-04-14
DOI
https://doi.org/10.1109/wamicon64429.2025.11004082
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
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article

Utilizing Information Assets in RF and Microwave Engineering Workflows

Matthew Ozalas, Anil Kumar Pandey, Tom DeMuer
Big Data and Business Intelligence
article

Utilizing Information Assets in RF and Microwave Engineering Workflows

Matthew Ozalas, Anil Kumar Pandey, Tom DeMuer
article en

Abstract

To meet the demands of next generation wireless communication systems, engineering teams must build flexible, reconfigurable design processes, or workflows, which are able to incorporate and leverage existing information in new ways. The challenge: over the past few decades, Electronic Design Automation (EDA) software platforms have focused on building elaborate user interfaces which obscure the lower-level mechanisms now required to build such workflows. Recently, several vendors have provided access to their EDA toolsets through Application Programming Interfaces (APIs), and in doing so have enabled new possibilities for leveraging information in the engineering design process through automation. This paper studies specific areas in high frequency simulation and measurement where automation can dramatically increase productivity and enable novel solutions to difficult problems by allowing engineering teams to use existing data which was previously inaccessible. Four examples are highlighted: netlist data mining, image-based physical modeling, simulation model extraction from measured data, and improved simulation and measurement speed using AI image completion. Theme: utilizing existing data and streamlining design through automation

Keysight Technologies (United States) (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 82%
Big Data and Business Intelligence
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