End-to-End Autoencoder Communications with Optimized Interference Suppression. (arXiv:2201.01388v1 [cs.IT])

An end-to-end communications system based on Orthogonal Frequency Division
Multiplexing (OFDM) is modeled as an autoencoder (AE) for which the transmitter
(coding and modulation) and receiver (demodulation and decoding) are
represented as deep neural networks (DNNs) of the encoder and decoder,
respectively. This AE communications approach is shown to outperform
conventional communications in terms of bit error rate (BER) under practical
scenarios regarding channel and interference effects as well as training data
and embedded implementation constraints. A generative adversarial network …

arxiv autoencoder communications