LDPC BP Decoder as RNN? #8
Inv4lidn4m3
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It is great to hear about your work. We are currently thinking about various ways to promote Sionna-based research. Could you develop and share a Sionna-based Jupyter notebook that contains your RNN decoder and reproduces some results from your paper for this purpose? |
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Hello everyone,
First of all I would like to thank you for this initiative. This is a great idea!
With my coworkers we are studying the usage of neural networks and machine learning for digital signal processing, and more specifically in the context of linear block coding/decoding. We have a BP algorithm implemented as a RNN, see the corresponding implementation in this paper (I am one of the author, Louis-Adrien Dufrène).
This implementation is fully differentiable and generic in the sens that you can described any factor graph in the RNN cell. Moreover, the BP algorithm is implemented with matrix manipulations, hence more complient with the "Tensorflow spirit".
Some modifications of our code are needed to support all the features already proposed by the Sionna's LDPC Decoder, but since the main basis is there, it should be managable.
Would you be interested in this architecture?
Edit (01/10/23) : We have published a paper in IEEE Transactions on Communications (https://ieeexplore.ieee.org/document/9896912) on automatic code discovery using our decoder architecture. The code to replicate the paper results is available in open source here https://github.com/Orange-OpenSource/GNBP. The code do not use Sionna at the moment because of legacy development, and we are wondering how we could actually add some Sionna's feature within the notebook to apply for the "Made with Sionna" section. Could you tell us how much of Sionna's features would we need to add? Does a simple Sionna's AWGN layer be enough?
LA
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