purus15987/CSI-Prediction
A comparative study of deep learning models for predicting Channel State Information (CSI) in massive MIMO systems. Integrates COST2100 dataset with STNet compression and evaluates models based on NMSE, RMSE, and spectral efficiency.
This project helps wireless communication engineers predict future Channel State Information (CSI) in massive MIMO systems. It takes raw or compressed channel measurement data and outputs predictions of future CSI, allowing engineers to evaluate and compare different deep learning models like STEMGNN, Transformer, BiLSTM, and STNet for improved spectral and temporal prediction performance. This is for researchers or practitioners optimizing wireless network performance.
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Use this if you need to accurately forecast wireless channel conditions to improve the efficiency and reliability of massive MIMO communication systems.
Not ideal if you are looking for a pre-packaged, production-ready solution without diving into model training and comparison.
Stars
30
Forks
5
Language
Python
License
Apache-2.0
Category
Last pushed
May 14, 2025
Commits (30d)
0
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