Combined Coding and Detection for High Density Storage Channels

该项目介绍了提高数据存储系统的密度和健壮性的方法。具体地说，它将我们在组合最大转移游程(MTR)编码和信号空间检测方面的工作扩展到非常高密度的记录通道，并更有效地应对此类通道中遇到的真实噪声和非线性。特别是，将研究MTR编码和其他距离增强码约束，以便在未来的高密度记录通道中使用。还将研究与距离增强码结合使用的广义信号空间检测方法。提出的研究任务是：1)分析MTR码在中等噪声和非线性情况下的性能；2)结合转移噪声和非线性的数据依赖特性，分析和寻找其他距离增强码约束；3)推导出更适合于数据相关噪声和非线性的最优超平面；以及4)寻找更高维的广义信号空间划分方法，以开发高效的约束延迟检测器。

This project addresses methods for increasing the density and robustness of data storage systems. Specifically, it extends our work on combined maximum transition run (MTR) coding and signal space detection to recording channels at very high densities and to cope more efficiently with realistic noise and nonlinearity encountered in such channels. In particular, MTR coding and other distance-enhancing code constraints will be investigated for use in future high density recording channels. Generalized signal space detection methods which will be used in conjunction with the distance-enhancing codes will also be studied. The proposed research tasks are: 1) performance analysis of MTR codes in the presence of medium noise and nonlinearity; 2) distance analysis and search for other distance-enhancing code constraints incorporating the data-dependent nature of transition noise and nonlinearity; 3) derivation of optimal hyperplanes better suited to data-dependent noise and nonlinearity; and 4) finding generalized signal space partitioning methods in higher dimensions to develop efficient constrained-delay detectors.