DEEPTURBO: Deep Turbo Decoder

Yihan Jiang, Sreeram Kannan, Hyeji Kim, Sewoong Oh, Himanshu Asnani, Pramod Viswanath

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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. The standard Turbo decoder (TURBO) iteratively applies the Bahl-Cocke-Jelinek-Raviv (BCJR) algorithm with an interleaver in the middle. A neural architecture for TURBO decoding, termed (NEURALBCJR), was proposed recently to create a module that imitates the BCJR algorithm using supervised learning, and to use the interleaver architecture along with this module, which is then fine-tuned using end-to-end training. However, knowledge of the BCJR algorithm is required to design such an architecture, which also constrains the resulting learnt decoder. Here we remedy this requirement and propose a fully end-to-end trained neural decoder-Deep Turbo Decoder (DEEPTURBO). With novel learnable decoder structure and training methodology, DEEPTURBO reveals superior performance under both AWGN and non-AWGN settings as compared to the other two decoders-TURBOand NEURALBCJR.

Original languageEnglish (US)
Title of host publication2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538665282
DOIs
StatePublished - Jul 2019
Externally publishedYes
Event20th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2019 - Cannes, France
Duration: Jul 2 2019Jul 5 2019

Publication series

NameIEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC
Volume2019-July

Conference

Conference20th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2019
CountryFrance
CityCannes
Period7/2/197/5/19

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Science Applications
  • Information Systems

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  • Cite this

    Jiang, Y., Kannan, S., Kim, H., Oh, S., Asnani, H., & Viswanath, P. (2019). DEEPTURBO: Deep Turbo Decoder. In 2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2019 [8815400] (IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC; Vol. 2019-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SPAWC.2019.8815400