On the Design of Channel Coding Autoencoders With Arbitrary Rates for ISI Channels

Yitian Zhang, Huihui Wu, Mark Coates

Abstract: This letter presents an autoencoder-based channel coding scheme in the presence of inter-symbol interference (ISI) and additive white Gaussian noise (AWGN), supporting arbitrary coding rates. Both the transmitter and receiver of the proposed autoencoder employ bi-directional gated recurrent unit (Bi-GRU) layers. Additional extra dense layers are applied at the end of the transmitter and at the beginning of the receiver, serving as learnable puncture and depuncture modules, respectively. Different code rates can be achieved by adjusting the output dimension of the extra dense layers. Experimental results demonstrate that the proposed autoencoder significantly outperforms conventional convolutional codes over ISI channels, for multiple code rates. The proposed autoencoder also outperforms LDPC codes in the low signal-to-noise ratio (SNR) regime. The neural codes still require improvement to be competitive in the high SNR regime.