The autoencoder concept has fostered the reinterpretation and the design of modern
communication systems. It consists of an encoder, a channel and a decoder block that …

Designing codes that combat the noise in a communication medium has remained a
significant area of research in information theory as well as wireless communications …

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 …

End-to-end learning of communication systems enables joint optimization of transmitter and
receiver, implemented as deep neural network (NN)-based autoencoders, over any type of …

There have been significant research activities in recent years to automate the design of
channel encoders and decoders via deep learning. Due the dimensionality challenge in …

The idea of end-to-end learning of communications systems through neural network (NN)-
based autoencoders has the shortcoming that it requires a differentiable channel model. We …

A rekindled the interest in auto-encoder algorithms has been spurred by recent work on
deep learning. Current efforts have been directed towards effective training of auto-encoder …

Attracted by its scalability towards practical code-word lengths, we revisit the idea of Turbo-
autoencoders for end-to-end learning of PHY-Layer communications. For this, we study the …

End-to-end learning of a communications system using the deep learning-based
autoencoder concept has drawn interest in recent research due to its simplicity, flexibility …

For reliable transmission across a noisy communication channel, classical results from
information theory show that it is asymptotically optimal to separate out the source and …