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DEMUCS for data-driven RF signal denoising

Citation Author(s):
Cagkan Yapar, Fabian Jaensch, Jan C. Hauffen, Francesco Pezone, Peter Jung, Saeid K. Dehkordi,Giuseppe Caire
Submitted by:
Cagkan Yapar
Last updated:
6 June 2024 - 10:21am
Document Type:
Presentation Slides
Document Year:
Cagkan Yapar
Paper Code:

In this paper, we present our radio frequency signal denoising approach, RFDEMUCS, for the 2024 IEEE ICASSP RF Signal Separation Challenge. Our approach is based on the DEMUCS architecture [1], and has a U-Net structure with a bidirectional LSTM bottleneck. For the task of estimating the underlying bit-sequence message, we also propose an extension of the DEMUCS that directly estimates the bits. Evaluations of the presented methods on the challenge test dataset yield MSE and BER scores of −118.71 and −81, respectively, according to the evaluation metrics defined in the challenge.

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