Adaptive Gradient Descent Bit-Flipping Diversity Decoding

Srdan Brkic, Predrag Ivanis, Bane Vasic

Research output: Contribution to journalArticlepeer-review


In this letter we propose a novel framework for designing decoders, for Low-Density Parity Check (LDPC) codes, that surpasses the frame error rate performance of Belief-Propagation (BP) decoding on binary symmetric channels. Its key component is the adaptation method, based on the genetic optimization algorithm, that is incorporated into the recently proposed Gradient Descent Bit-Flipping Decoding with Momentum (GDBF-w/M). We show that the resulting decoder outperforms all state-of-the-art probabilistic bit-flipping decoders and, additionally, it can be trained to perform beyond BP decoding, which is verified by numerical examples that include codes used in IEEE 802.3an and 5GNR standards. The proposed framework provides a systematic method for decoder optimization without requiring knowledge of trapping sets. Moreover, it is applicable to both regular and irregular LDPC codes.

Original languageEnglish (US)
Pages (from-to)2257-2261
Number of pages5
JournalIEEE Communications Letters
Issue number10
StatePublished - Oct 1 2022


  • Belief-propagation
  • error-floors
  • genetic algorithm
  • gradient descent bit-flipping
  • low-density parity-check codes

ASJC Scopus subject areas

  • Modeling and Simulation
  • Computer Science Applications
  • Electrical and Electronic Engineering


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