Turbo autoencoder: Deep learning based channel codes for point-to-point communication channels
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 …
significant area of research in information theory as well as wireless communications …
Learn codes: Inventing low-latency codes via recurrent neural networks
Designing channel codes under low-latency constraints is one of the most demanding
requirements in 5G standards. However, a sharp characterization of the performance of …
requirements in 5G standards. However, a sharp characterization of the performance of …
Deepcode: Feedback codes via deep learning
The design of codes for communicating reliably over a statistically well defined channel is an
important endeavor involving deep mathematical research and wide-ranging practical …
important endeavor involving deep mathematical research and wide-ranging practical …
Deepcode: Feedback codes via deep learning
The design of codes for communicating reliably over a statistically well defined channel is an
important endeavor involving deep mathematical research and wide-ranging practical …
important endeavor involving deep mathematical research and wide-ranging practical …
Communication algorithms via deep learning
Coding theory is a central discipline underpinning wireline and wireless modems that are
the workhorses of the information age. Progress in coding theory is largely driven by …
the workhorses of the information age. Progress in coding theory is largely driven by …
Physical layer communication via deep learning
Reliable digital communication is a primary workhorse of the modern information age. The
disciplines of communication, coding, and information theories drive the innovation by …
disciplines of communication, coding, and information theories drive the innovation by …
Ko codes: inventing nonlinear encoding and decoding for reliable wireless communication via deep-learning
Landmark codes underpin reliable physical layer communication, eg, Reed-Muller, BCH,
Convolution, Turbo, LDPC, and Polar codes: each is a linear code and represents a …
Convolution, Turbo, LDPC, and Polar codes: each is a linear code and represents a …
A CNN-based end-to-end learning framework toward intelligent communication systems
Deep learning has been applied in physical-layer communications systems in recent years
and has demonstrated fascinating results that were comparable or even better than human …
and has demonstrated fascinating results that were comparable or even better than human …
Deep learning for decoding of linear codes-a syndrome-based approach
A Bennatan, Y Choukroun… - 2018 IEEE International …, 2018 - ieeexplore.ieee.org
We present a novel framework for applying deep neural networks (DNN) to soft decoding of
linear codes at arbitrary block lengths. Unlike other approaches, our framework allows …
linear codes at arbitrary block lengths. Unlike other approaches, our framework allows …