Towards Fountain Codes. Part II: Belief Propagation Decoding

Error-prone patterns have been extensively studied for low-density parity-check codes, yet they have never been fully explored for generator-based Fountain codes. In the previous work, the structures and analysis of Fountain codes were discussed. In what follows, we will focus on different substructures in the $$G$$G-based Tanner graph under the belief propagation algorithm. We will then proceed to provide further insights on the most pertinent issues related to Fountain codes, such as their code constructions, encoding and decoding techniques, performance metrics, the convergence of their decoding as well as the associated design techniques. Most of the work carried out during the previous years has been presented.

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