2D-Pdnp多道检测的最小误码率调整

Shanwei Shi, J. Barry
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引用次数: 0

摘要

磁记录的主要障碍是模式相关的介质噪声,其影响只会随着面密度的增加而变得更加严重。模式相关噪声预测(PDNP)算法[1][2]被广泛用作减轻单轨检测中模式相关媒体噪声的有效策略,最近已扩展到多轨场景[3];基于图1所示的架构,它使用2D模式(跨越多个轨道)来减轻下行轨道和交叉轨道模式相关的噪声。采样后的回读波形由一个系数为$\mathbf{C}$的$2 \times 2$ MIMO均衡器滤波,其输出$\mathbf{y}_{k}=\left[y_{k}^{(1)}, y_{k}^{(2)}\right]^{T}$被传递给2D -PDNP多道检测器。与每个2D位模式相关联的是信号电平向量$\mathbf{s}$,标准差对角矩阵$\Lambda$和一组矩阵值预测系数$\mathbf{P}_{0}, \mathbf{P}_{1}, \ldots, \mathbf{P}_{N_{p}-1} $。2D -PDNP Viterbi检测器边缘e的分支度量为[3]:
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Minimum-Bit-Error Rate Tuning for 2D-Pdnp Multitrack Detection
A dominant impediment in magnetic recording is pattern-dependent media noise, and its impact will only grow more severe as areal densities increase. The pattern-dependent noise prediction (PDNP) algorithm [1] [2], widely used as an effective strategy for mitigating pattern-dependent media noise in single-track detection, has recently been extended to the multitrack scenario [3]; it uses 2D patterns (spanning multiple tracks) to mitigate both downtrack and crosstrack pattern-dependent noise, based on the architecture shown in Fig. 1. The sampled readback waveforms are filtered by a $2 \times 2$ MIMO equalizer with coefficients $\mathbf{C}$, whose output $\mathbf{y}_{k}=\left[y_{k}^{(1)}, y_{k}^{(2)}\right]^{T}$ is passed to a 2D -PDNP multitrack detector. Associated with each 2D bit pattern is a signal level vector $\mathbf{s}$, a standard deviation diagonal matrix $\Lambda$, and a set of matrix-valued predictor coefficients $\mathbf{P}_{0}, \mathbf{P}_{1}, \ldots, \mathbf{P}_{N_{p}-1} $. The branch metric of edge e for the 2D -PDNP Viterbi detector is [3]:
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