Combined Coding and Detection for High Density Storage Channels

这个项目解决了增加数据存储系统密度和健壮性的方法。具体来说，它将我们在最大过渡运行（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信道，并更有效地处理这些信道中遇到的实际噪声和非线性。特别是，MTR编码和其他距离增强编码约束将被研究用于未来的高密度记录信道。将与距离增强码一起使用的广义信号空间检测方法也将被研究。提出的研究任务是：1)在中等噪声和非线性条件下MTR码的性能分析；2)距离分析和搜索包含过渡噪声和非线性的数据依赖性的其他距离增强代码约束；3)推导出更适合于数据相关噪声和非线性的最优超平面；4)寻找广义的高维信号空间划分方法，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.