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Welcome to the AntennaCAT wiki!
Current AntennaCAT Version: 2025.0
AntennaCAT v 2025.0 is live!
The Wiki updates are currently in progress, with more guides and tutorials released daily.
Table of Contents
- What is AntennaCAT?
- Code Releases
- System Compatibility
- Getting Started
- Where Can I Find More Information?
- Publications and Related Projects
The Antenna Calculation and Autotuning Tool (AntennaCAT) software suite is a comprehensive implementation of machine learning to automate, evaluate, and optimize the antenna design process using EM simulation software. It utilizes a combined antenna designer pre-loaded with replication studies and internal calculator to accelerate the CAD construction and EM simulation of several common topologies, while eliminating model disparity for automated data collection. In particular, this work includes the capability to create and export structured datasets from the aforementioned EM software for iterative improvement and includes an expandable selection of optimizers. AntennaCAT is designed with three things in mind: accessibility, adaptability, and experimentation.
This documentation includes the basics for downloading and getting started with AntennaCAT, using the advanced features, and how AntennaCAT works on the backend. It has been broken up into multiple Wiki pages, including guides and tutorials, videos, and a series of blog posts. Publication references, including the September 2024 dissertation on AntennaCAT are linked at the bottom of this page
AntennaCAT has appeared in several publications during its development, however it was not publicly available until V2025.0. Some features have been replaced, or removed, during the development process. Information regarding early development publications and code releases are included in the Documentation page Past Releases section
AntennaCAT is currently only compatible with Windows OS. It has been tested with both Windows 10 and Windows 11. Earlier versions of Windows and Linux-based systems are likely incompatible with the current version of AntennaCAT.
AntennaCAT is available as open-source software. In this case, that means:
- The software is provided AS-IS. There's no full-time dedicated team working on the AntennaCAT software, so it will likely have bugs as the features grow and we get through the early releases. However, AntennaCAT has been through enough testing for researchers and those wanting to do some experimenting.
- The documentation is in-progress. AntennaCAT is a living project, so features may be a bit ahead of the documentation.
- It's free. You pay nothing for AntennaCAT. You also do not need an account to download the latest version of AntennaCAT.
- You shouldn't need an account to download ANY version of AntennaCAT, but stable-version hosting may be backed up on a different platform for redundancy.
You can contribute by:
- Reporting bugs in the 'issues' tab at the top of the page.
- Before doing so, see if you are experiencing a known issue by checking the Known Issues section on the Updates & Errata page. We may have a fix in progress!
- Eventually we will be accepting community bug fixes and contributions
And with that, to get started ....
If you're familiar with GitHub, Python, and have a favorite Python-supporting IDE, you can download AntennaCAT from the main page and use the README to get started. It is recommended to check out the Quick StartGuide on the Documentation Page for suggested Python versions and virtual environment settings.
If you're new to GitHub, coding (or just Python), or you just need a refresher, start with the Documentation page, and then check out some of the detailed tutorials linked there. General tutorials and documentation are also linked below. We also have a full Getting Started Guide with a walk through of setting up everything from the IDE to running AntennaCAT.
Full documentation starts on the Documentation page. This is the primary page for any information, guides, tutorials, or other references for the AntennaCAT repository.
Guides and Tutorials have their own page! While mentioned in the documentation, these pages are intended to be supplemental resources for users to explore and experiment with on their own.
Under construction!
As part of the documentation process, informal blog posts will be released on LC-Linkous' project page. These include general use notes, small feature updates, and things not important enough to make it to the main documentation of the Wiki.
Check for the #antennacat tag!
Under construction!
Video tutorials and examples will be released after the first few code release updates. The primary documentation will always be the [Documentation page](Documentation) of the Wiki, but some things are simply easier to explain visually.
This section lists publications and presentations that on materials that have done into the development of AntennaCAT rather than an exhaustive list of all publications that used or mentioned AntennaCAT in early development.
This is the 2024 dissertation with documented work and current progress of AntennaCAT:
[1] L. Linkous, “Machine Learning Assisted Optimization for Calculation and Automated Tuning of Antennas,” VCU Scholars Compass, 2024. https://scholarscompass.vcu.edu/etd/7841/ (accessed Oct. 21, 2024).
AntennaCAT first appeared in these conference papers:
[2] L. Linkous, E. Karincic, J. Lundquist and E. Topsakal, "Automated Antenna Calculation, Design and Tuning Tool for HFSS," 2023 United States National Committee of URSI National Radio Science Meeting (USNC-URSI NRSM), Boulder, CO, USA, 2023, pp. 229-230, doi: 10.23919/USNC-URSINRSM57470.2023.10043119. [Online:] https://ieeexplore.ieee.org/abstract/document/10043119
[3] E. Karincic, L. Linkous, and E. Topsakal , "Generalized Machine-Learning Particle Swarm Optimization Antennas for CBRS," 2023 United States National Committee of URSI National Radio Science Meeting (USNC-URSI NRSM), Boulder, CO, USA, 2023 https://www.usnc-ursi-archive.org/nrsm/2023/papers/1065.pdf. 1-page, non-indexed but presented.
[4] L. Linkous, J. Lundquist and E. Topsakal, "AntennaCAT: Automated Antenna Design and Tuning Tool," 2023 IEEE USNC-URSI Radio Science Meeting (Joint with AP-S Symposium), Portland, OR, USA, 2023, pp. 89-90, doi: 10.23919/USNC-URSI54200.2023.10289238. [Online:] https://ieeexplore.ieee.org/abstract/document/10289238
The following papers were part of the data collection and ML work that went into what would become the Hyperparameter Prediction Network & Dictionary:
[5] L. Linkous and E. Topsakal, "Machine Learning Assisted Optimization Methods for Automated Antenna Design," 2024 United States National Committee of URSI National Radio Science Meeting (USNC-URSI NRSM), Boulder, CO, USA, 2024, pp. 377-378, doi: 10.23919/USNC-URSINRSM60317.2024.10464597. [Online:] https://ieeexplore.ieee.org/abstract/document/10464597
[6] L. Linkous, J. Lundquist, M. Suche and E. Topsakal, "Machine Learning Assisted Hyperparameter Tuning for Optimization," 2024 IEEE INC-USNC-URSI Radio Science Meeting (Joint with AP-S Symposium), Florence, Italy, 2024, pp. 107-108, doi: 10.23919/INC-USNC-URSI61303.2024.10632482. [Online:] https://ieeexplore.ieee.org/abstract/document/10632482
The Antenna Calculator was first debuted at DEF CON 30, and then as an ASEE-presented teaching tool:
[7] "DEF CON 30 RF Village - Erwin Karincic - Have a SDR? - Design and make your own antennas" PDF link, and Dollarhyde's AntennaCalculator
[8] E. Karincic, E. Topsakal, and L. Linkous. "Patch Antenna Calculations and Fabrication Made Simple for Cyber Security Research," 2023 ASEE Annual Conference & Exposition, Baltimore , Maryland, 2023, June. ASEE Conferences, 2023. [Online:] https://peer.asee.org/43974
The stand-alone CLI Antenna Calculator repository by Dollarhyde.
The Objective Function Test Suite is now public. A subset of these functions were used to collect data on optimizer performance.
Stand-Alone Optimizers:
| Base Optimizer | Alternate Version | Quantum-Inspired Optimizer | Surrogate Model Version |
|---|---|---|---|
| pso_python | pso_basic | pso_quantum | all versions are options in surrogate_model_optimization |
| cat_swarm_python | sand_cat_python | cat_swarm_quantum | all versions are options in surrogate_model_optimization |
| chicken_swarm_python |
2015_improved_chicken_swarm 2022 improved chicken swarm |
chicken_swarm_quantum | all versions are options in surrogate_model_optimization |
| sweep_python | *alternates in base repo | - | - |
| bayesian optimization_python | - | - | *interchangeable surrogate models included in base repo |
| multi_glods_python | - | multiGLODS option in surrogate_model_optimization |