A multi-level convolutional autoencoder for finite-blocklength AWGN channels claims comparable or better bit error rates than TurboAE-MOD and polar codes, with per-level exhaustive codebook tests and SNR-adaptive rate by layer removal.
Channel polarization: A method for constructing capacity- achieving codes for symmetric binary-input memoryless channels,
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Mutli-Level Autoencoder: Deep Learning Based Channel Coding and Modulation
A multi-level convolutional autoencoder for finite-blocklength AWGN channels claims comparable or better bit error rates than TurboAE-MOD and polar codes, with per-level exhaustive codebook tests and SNR-adaptive rate by layer removal.