ICASSP 2024 SP Grand Challenge:

Data-Driven Signal Separation in Radio Spectrum

This challenge will require developing an engine for signal separation of radio-frequency (RF) waveforms. At inference time, a superposition of a signal of interest (SOI) and an interfering signal will be fed to the engine, which should recover the SOI by performing a sophisticated interference cancellation. SOI is a digital communication signal whose complete description is available (modulation, pulse-shape, timing, frequency, etc). However, the structure of the interference will need to be learned from data. We expect successful contributions to adapt existing machine learning (ML) methods and/or propose new ones from the areas of generative modeling, variational auto-encoders, U-Nets and others.

Important Dates:

  • Oct. 4, 2023 – Submission 1 deadline: Initial submission containing outcomes on TESTSET1MIXTURE.
  • Nov. 1, 2023 – Submission 2 deadline: Second submission containing the outcomes on TESTSET1MIXTURE.
  • Dec. 1, 2023 – Final submission deadline: Last submission containing the outcomes on TESTSET2MIXTURE. The final ranking will be exclusively determined by the results of this ultimate submission.
  • Jan. 2, 2024 – Submission deadline for 2-page papers of the best Challenge submissions (by invitation only). Accepted papers will be in the ICASSP proceedings.

Further information and details can be found below.

Challenge Details

Click here for details on the challenge setup


Click here to access to access the challenge discord server


Link to dataset

Link to TestSet1Mixture

Starter Code

Click here for the starter code of this challenge

Reference Methods

Click here for the Jupyter notebook of selected reference methods

Link to baseline model weights

* The intellectual property (IP) is not transferred to the challenge organizers; in other words, if code is shared or submitted, the participants retain ownership of their code.