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- W1956376585 abstract "The best known practical algorithm for the decoding of low-density parity-check (LDPC) codes is the iterative sum-product or belief propagation algorithm, operating on a Tanner graph (TG) of the code. Conventionally, in each iteration, all the symbol nodes and subsequently all the check nodes in the TG pass new messages to their neighbors (the so-called flooding schedule). We propose a new message-passing schedule, called schedule. Unlike flooding, the probabilistic schedule operates based on the structure of the TG, and probabilistically balances the frequency at which different symbol nodes update their outgoing messages in accordance with their girths. Our results show that, particularly for short block lengths, the new schedule offers a much better performance/complexity trade-off. For a particular example of a (1268,456) code, at no cost in complexity, the probabilistic schedule not only decreases both the bit and message error rates by an order of magnitude, but also reduces the number of undetected errors considerably. This work shows the importance of scheduling in the performance of iterative decoding algorithms and suggests that a schedule which matches the structure of the TG can substantially improve the performance/complexity trade-off in the decoding of short LDPC codes." @default.
- W1956376585 created "2016-06-24" @default.
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- W1956376585 date "2002-11-13" @default.
- W1956376585 modified "2023-09-26" @default.
- W1956376585 title "Decoding low-density parity-check codes with probabilistic schedule" @default.
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- W1956376585 doi "https://doi.org/10.1109/pacrim.2001.953537" @default.
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