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Author: search.filters.author.Supnithi, PornchaiSubject: search.filters.subject.low-density parity-check (LDPC) codes

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    Reliability Ratio-Based Serial Algorithm of LDPC Decoder for Turbo Equalization Schemes
    (2022-02-01)
    Khittiwitchayakul, Sirawit
    ;
    Phakphisut, Watid
    ;
    Supnithi, Pornchai
    Serial decoding algorithms of low-density parity-check (LDPC) code converge efficiently with low errors. Previously, a serial decoding algorithm, named a shuffled belief-propagation (SBP), was applied in turbo equalization of bit-patterned magnetic recording (BPMR) systems. With the SBP algorithm, an LDPC decoder converged twice as fast as one using conventional BP algorithms. We further improved the convergence speed of SBP by updating the messages in an adaptive order, which played a flexible role throughout decoding. We proposed two adaptive-serial algorithms for LDPC codes in turbo equalization. One updated the messages using the extrinsic loglikelihood ratio (LLR) and the result of the parity-check equation checking. The second contained an additional rule that tracked the LLR sign changes in each iteration. Both algorithms converged faster and with lower bit error rates (BERs) than the SBP and previous adaptive-serial algorithms in a BPMR system with media noise.
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    EXIT chart analysis of nonbinary protograph LDPC codes for partial response channels
    (2014-11-01)
    Phakphisut, Watid
    ;
    Supnithi, Pornchai
    ;
    Puttarak, Nattakan
    Low-density parity-check (LDPC) codes over finite fields GF(q) provide an error correction in the noisy partial response (PR) channels. The extrinsic information transfer (EXIT) chart can be used to predict the threshold decoding of protograph LDPC codes, however, previous works only consider the binary protograph LDPC codes in the PR channels. In this paper, we propose to perform the EXIT chart analysis on the nonbinary protograph LDPC codes for the PR channels. Unlike prior works, the actual extrinsic information of the channel detector is measured, then the extrinsic information to the variable nodes is generated with the measured statistics. Moreover, since the mutual information of the variable nodes depends on GF(q), we use the Monte Carlo method to approximate the mutual information. The analysis on the regular (2,4) code, regular (3,6) code, RA code, and AR3A code on the PR channels reveal that, for the PR1 channel, the RA code outperforms the others for q = 2, 4, and 8, but the regular (2,4) code is the best for q = 16 and 32. For the PR2 channel, the RA code is the best code for q = 2 and 4, but the regular (2,4) code is the best code for q > 4. The simulation of the codes for q = 4 and 16 are then used to confirm the theoretical results.