Automation of Antenna Isolation Modeling

Abstract

This thesis enhances an existing Python-based automation framework for antenna isolation modeling in large-scale antenna arrays, developed by Ericsson Research. The framework utilizes ANSYS HFSS via the PyAEDT API for automating electromagnetic workflows, enabling systematic variation of antenna array parameters including geometry, element spacing, polarization configurations, etc. which are loaded for model creation. This builds a complete 3D antenna array model in HFSS with proper excitation and boundary conditions, which then extracts comprehensive S-parameter data from simulation results and provides visualization capabilities with mathematical error metrics for evaluating mesh convergence and simulation reliability. This work extends the framework with advanced performance evaluation and additional comparative analysis capabilities. Key contributions include the development of simulation performance evaluation tools that systematically analyze HFSS log files to extract information as resource utilization and convergence behavior, estimating error-free dynamic range and computational efficiency enabling quantitative comparison of simulation performance across different array configurations and computational runs. This is critical for optimizing simulation workflow and validating result accuracy in large-scale antenna modeling. Additionally, the extended framework provides comprehensive S-parameter comparison tools that perform quantitative analysis between different antenna simulations facilitating systematic evaluation of design variation and isolation performance characteristics.