• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.11C
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• pp.868-873
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• 2008

In this paper, we analyze the burst error performance of LDPC codes on perpendicular magnetic recording(PMR) channel. When burst error is generated on PMR channel, we use channel state information(CSI) to set the LLR information of channel detector zero. We consider the rate 0.94 LDPC codes and use SOVA as channel detector with low complexity.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.4C
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• pp.299-304
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• 2008

For perpendicular magnetic recording channels, it is hard to expect improving the performance by using the PRML or NPML. Hence, we exploit LDPC code to improve the performance. In this paper, we examine a single message-passing detector/decoder matched to the combination of a perpendicular magnetic recording channel detector and an LDPC code decoder. We examine the performance of channel iteration with joint LDPC code on perpendicular magnetic recording channel, and simplify the complexity of the message-passing detector algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.10C
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• pp.758-763
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• 2008

We introduce a noise-predictive turbo equalization using noise filter in perpendicular magnetic recording(PMR) channel. The noise filter mitigates the colored noise in high-density PMR channel. In this paper, the channel detectors used are SOVA (Soft Output Viterbi Algorithm) and BCJR algorithm which proposed by Bahl et al., and the outer decoder used is LDPC (Low Density Parity Check) code that is implemented by sum-product algorithm. Two kinds of LDPC codes are experimented. One is the 0.5Kbyte (4336,4096) LDPC code with the code rate of 0.94, and the other is 1Kbyte (8432,8192) LDPC code with the code rate of 0.97.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.7C
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• pp.611-617
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• 2010

In this paper, we investigate the performances of the serial concatenated convolutional codes (SCCC) and low-density parity-check (LDPC) codes on perpendicular magnetic recording (PMR) channels. We discuss the performance of two systems when user bit-densities are 1.7, 2.0, 2.4 and 2.8, respectively. The SCCC system is less complex than LDPC system. The SCCC system consists of recursive systematic convolutional (RSC) codes encoder/decoder, precoder and random interleaver. The decoding algorithm of the SCCC system is the soft message-passing algorithm and the decoding algorithm of the LDPC system is the log domain sum-product algorithm (SPA). When we apply the iterative decoding between channel detector and the error control codes (ECC) decoder, the SCCC system is compatible with the LDPC system even at the high user bit density.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.1C
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• pp.15-20
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• 2009

For perpendicular magnetic recording (PMR) channels, noise-predictive maximum likelihood (NPML) detection method has been used. But, it is hard to expect improving the performance when the bit density is increased. Hence, we exploit the coding methods which has good performance. In this paper, we show the performance of the recursive systematic convolutional (RSC) codes with turbo-equalization method with different channel bit densities. The noise model is 80% jitter noise and 20% AWGN.