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Decoding low-density parity-check codes with probabilistic scheduling
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AI
DOI：10.1109/4234.957379.png)
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In this letter, we present a new message-passing schedule for the decoding of low-density parity-check (LDPC) codes. This approach, designated probabilistic schedule, takes into account the structure of the Tanner graph (TG) of the code. We show by simulation that the new schedule offers a much better performance/complexity trade-off. This work also suggests that scheduling plays an important role in iterative decoding and that a schedule that matches the structure of the TG is desirable.
Keyword:
belief propagation algorithm
codes
codes on graphs
decoding
iterative decoding
iterative methods
LDPC codes
message-passing schedule
sum-product algorithm
期刊
IF:
4.4
论文数:
1.3W
被引数:
2.2W
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