Research on Ultrahigh-Density Perpendicular Magnetic Recording Using Adaptive PRML Systems

自适应PRML系统超高密度垂直磁记录研究

• 批准号: 17360182
• 负责人: OSAWA Hisashi
• 金额: $ 9.47万
• 依托单位: Ehime University
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (B)
• 财政年份: 2005
• 资助国家: 日本
• 起止时间: 2005 至 2006
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-17360182/
• 关键词: perpendicular magnetic recording; thermal decay; PRML system; GPRML system; PRML-AR system; neural network equalization; adaptive PRML system; 信号処理方式; マイクロトラックモデル

A thermal decay model based on the experimental data for three CoPtCr-SiO_2 perpendicular magnetic recording (PMR) media with thermal stability factors K_uV/kT of 94, 60 and 45 is obtained. The long-term BER performance of PRML, GPRML and GPRML-AR systems for the 128/130(0,16/8) RLL code is evaluated by computer simulation using the thermal decay model at a linear recording density of 1000 kBPI, which is difficult to evaluate experimentally.It is clarified that, in all PRML systems at t_E = 10^8 seconds, there is no degradation in BER performance for the medium of K_uV/kT =94, while an order of magnitude or so degradation in BERs is found for the medium of K_uV/kT =60 and three orders of magnitude or so degradation in BERs can be seen for the medium of K_uV/kT =45. Nevertheless, GPR1ML system provides the SNR improvements of 0.4, 0.4 and 4.9 dB at BER=10^<-4> over PR1ML system for the media of K_uV/k_T =94, 60 and 45, respectively, and GPR1ML-AR system offers the improvements of 1.5, 1.8 and 6.6 dB at t_E=10^6 is seconds.When a neural network is employed as a equalizer and the network is simplified and optimized by using a hybrid genetic algorithm which is the combination of a back propagation algorithm and a genetic algorithm, the performance degradation of PRML system is not found for K_uV/kT =60 and till t_E = 10^5. Therefore, this shows that the combination of neural network equalization and PRML system has the good adaptability for the thermal decay. Hereafter, the adaptive GPRML and PRML-AR systems using a neural network equalizer will be studied.

基于实验数据，建立了三种CoPtCr-SiO_2垂直磁记录（PMR）介质的热稳定系数K_uV/kT分别为94、60和45的热衰减模型。采用热衰减模型对128/130(0,16/8)RLL码下的PRML、GPRML和GPRML- ar系统在1000 kBPI线性记录密度下的长期误码率性能进行了计算机模拟评价。结果表明，在t_E = 10^8秒的PRML系统中，K_uV/kT =94介质的BER性能没有下降，而K_uV/kT =60介质的BER性能下降了一个数量级左右，K_uV/kT =45介质的BER性能下降了三个数量级左右。然而，对于K_uV/k_T =94、60和45的介质，GPR1ML系统在BER=10^<-4>时的信噪比分别比PR1ML系统提高了0.4、0.4和4.9 dB，而GPR1ML- ar系统在t_E=10^6 s时的信噪比分别提高了1.5、1.8和6.6 dB。采用神经网络作为均衡器，采用反向传播算法和遗传算法相结合的混合遗传算法对网络进行简化和优化，在K_uV/kT =60时，直到t_E = 10^5时，PRML系统的性能没有下降。因此，这表明神经网络均衡与PRML系统相结合对热衰减具有良好的适应性。接下来，研究了基于神经网络均衡器的自适应GPRML和PRML-AR系统。

项目成果

An application of neural network equalization to polytopic multipexing holography and reduction of interpixel interference

神经网络均衡在多面复用全息术和减少像素间干扰中的应用

• 发表时间: 2007
• 期刊: IEICE Transaction on Electronics 90-C・8(to be appeared)
• 作者: H.Osawa;N.Kawaue;Y.Okamoto;Y.Nakamura;H.Ochi;S.Marukawa
• 通讯作者: S.Marukawa

PRML方式を適用した長手及び垂直磁気記録の性能比較

PRML方法纵向和垂直磁记录的性能比较

• 发表时间: 2005
• 期刊: 日本応用磁気学会誌 (印刷中)
• 作者: H.Isozaki;Y.Nakamura;大沢 寿;岡本好弘
• 通讯作者: 岡本好弘

BER performance of PRML system in perpendicular magnetic recording channel with thermal decay

PRML系统在热衰减垂直磁记录通道中的BER性能

• 发表时间: 2007
• 期刊: IEEE Transactions on Magnetics 43・6
• 作者: N.Shinohara;H.Osawa;Y.Okamoto;Y.Nakamura;A.Nakamoto;K.Miura;H.Muraoka;Y.Nakamura
• 通讯作者: Y.Nakamura

Performance evaluation of PRML system based on thermal decay model

基于热衰减模型的PRML系统性能评估

• 发表时间: 2007
• 期刊: IEICE Transaction on Electronics 90-C・8(to be appeared)
• 作者: N.Shinohara;K.Takeuchi;H.Osawa;Y.Okamoto;Y.Nakamura;A.Nakamoto;K.Miura;H.Muraoka;Y.Nakamura
• 通讯作者: Y.Nakamura

Iterative decoding using attenuated extrinsic information from sum-product decoder for PMR channel with patterned medium

使用来自和积解码器的衰减外在信息对具有图案介质的 PMR 通道进行迭代解码

• 发表时间: 2007
• 期刊: IEEE Transactions on Magnetics 43・6
• 作者: Y.Nakamura;M.Nishimura;Y.Okamoto;H.Osawa;H.Aoi;H.Muraoka;Y.Nakamura
• 通讯作者: Y.Nakamura