SAIC-MONTREAL/CeBed
Data-Driven Channel Estimation Test Bed
This project helps wireless communication researchers and engineers design and evaluate deep learning models for estimating communication channels in OFDM systems. It takes simulated or custom generated channel and signal data as input and produces trained models and benchmark comparisons against existing channel estimation algorithms. Wireless system designers and researchers in signal processing would use this tool.
No commits in the last 6 months.
Use this if you need a standardized way to develop, test, and compare new deep channel estimation algorithms for OFDM systems.
Not ideal if you are looking for a plug-and-play solution for real-time channel estimation in a deployed wireless system.
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Last pushed
Dec 11, 2023
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