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Genie-aided adaptive normalized min-sum algorithm for LDPC decoding

Authors: Yue Liu; Kewu Peng; Changyong Pan; Liwen Fan;

Genie-aided adaptive normalized min-sum algorithm for LDPC decoding

Abstract

This paper proposes an algorithm for the decoding of low-density parity check (LDPC) codes, aiming to retrieve the performance degradation of conventional normalized min-sum algorithm, especially for irregular LDPC code. In our proposed algorithm, normalization factors are adjusted dynamically and adaptively during iterative decoding process according to look-up tables obtained by training and simulation in our proposal. The look-up tables construct the relationship between normalization factor a and the failed parity-check equation proportion p, which could be calculated in each decoding process. Simulation results demonstrate that the proposed algorithm can achieve a performance closer to the sum-product algorithm and a coding gain of around 0.2dB compared to the conventional normalized min-sum algorithm for rate 2/3 irregular LDPC codes over the AWGN channel. Our proposal is independent from the channel characteristics and retains low complexity. The implementation facility and the excellent performance make the proposed algorithm expect a wide application.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
8
Top 10%
Top 10%
Average
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