ipc-lab/deepjscc-noma
Implementation of "Distributed Deep Joint Source-Channel Coding over a Multiple Access Channel" paper (ICC 2023)
This project helps researchers transmit images more effectively over noisy communication channels, especially when bandwidth is limited. It takes raw image data from multiple sources and processes it using advanced deep learning techniques to produce higher-quality reconstructed images at the receiver end. This tool is designed for telecommunications researchers and engineers exploring next-generation wireless communication systems.
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Use this if you are a telecommunications researcher working on optimizing image transmission over shared, noisy wireless channels with limited bandwidth, and you want to explore non-orthogonal joint source-channel coding methods.
Not ideal if you are looking for a plug-and-play image compression tool for general consumer use or a solution for orthogonal image transmission methods.
Stars
33
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6
Language
Python
License
—
Category
Last pushed
Oct 12, 2023
Commits (30d)
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