December 01, 2017

Scaling Deep Learning-based Decoding of Polar Codes via Partitioning

  • Cammerer S.
  • Gruber T.
  • Hoydis J.
  • Ten Brink S.

The training complexity of deep learning-based channel decoders scales exponentially with the codebook size and therefore with the number of information bits. Thus, neural network decoding (NND) is currently only feasible for very short block lengths. In this work, we show that the conventional iterative decoding algorithm for polar codes can be enhanced when sub-blocks of the decoder are replaced by neural network (NN) based components. Thus, we partition the encoding graph into smaller sub-blocks and train them individually, closely approaching maximum a posteriori (MAP) performance per sub-block. These blocks are then connected via the remaining conventional belief propagation decoding stage(s). The resulting decoding algorithm is non-iterative and inherently enables a high-level of parallelization, while showing a competitive biterror- rate performance. We examine the degradation through partitioning and compare the resulting decoder to state-of-theart polar decoders such as successive cancellation list and belief propagation decoding.

Recent Publications

January 01, 2019

Friendly, appealing or both? Characterising user experience in sponsored search landing pages

  • Bron M.
  • Chute M.
  • Evans H.
  • Lalmas M.
  • Redi M.
  • Silvestri F.

© 2017 International World Wide Web Conference Committee (IW3C2), published under Creative Commons CC BY 4.0 License. Many of today's websites have recognised the importance of mobile friendly pages to keep users engaged and to provide a satisfying user experience. However, next to the experience provided by the sites themselves, ...

January 01, 2019

Analyzing uber's ride-sharing economy

  • Aiello L.
  • Djuric N.
  • Grbovic M.
  • Kooti F.
  • Lerman K.
  • Radosavljevic V.

© 2017 International World Wide Web Conference Committee (IW3C2), published under Creative Commons CC BY 4.0 License. Uber is a popular ride-sharing application that matches people who need a ride (or riders) with drivers who are willing to provide it using their personal vehicles. Despite its growing popularity, there exist ...

January 01, 2019

The paradigm-shift of social spambots: Evidence, theories, and tools for the arms race

  • Cresci S.
  • Petrocchi M.
  • Pietro R.
  • Spognardi A.
  • Tesconi M.

© 2017 International World Wide Web Conference Committee (IW3C2), published under Creative Commons CC BY 4.0 License. Recent studies in social media spam and automation provide anecdotal argumentation of the rise of a new generation of spambots, so-called social spambots. Here, for the first time, we extensively study this novel ...