mattiafabiani/One-Shot-Near-Field-Localization-with-AI-Optimized-Hybrid-Beamformer-Design
A CNN-based method efficiently locates near-field users in large-scale hybrid beamforming antenna array systems with low beam training overhead.
This project offers a method to quickly and accurately pinpoint the location of a single user device in the near-field of very large antenna systems, often found in advanced wireless communication. It takes in raw signal data from the antenna array and outputs the user's precise position, even in complex environments. It is designed for researchers and engineers working on next-generation wireless communication systems.
Use this if you need a highly efficient and robust way to locate single user devices in the near-field of extremely large MIMO (XL-MIMO) systems, especially when aiming for low training overhead and fewer radio frequency chains.
Not ideal if you are working with far-field localization, multi-user scenarios, or smaller antenna array systems where the near-field effect is not dominant.
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10
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3
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Jupyter Notebook
License
MIT
Category
Last pushed
Oct 15, 2025
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