DeepTurbo: Deep Turbo Decoder

Understand

Present-day communication systems routinely use codes that approach the channel capacity when coupled with a computationally efficient decoder.

• However, the decoder is typically designed for the Gaussian noise channel and is known to be sub-optimal for non-Gaussian noise distribution.
• Deep learning methods offer a new approach for designing decoders that can be trained and tailored for arbitrary channel statistics.
• We focus on Turbo codes and propose DeepTurbo, a novel deep learning based architecture for Turbo decoding.