Small CIF: Coding and Detection for Two-dimensional Magnetic Recording Systems

磁记录是应用最广泛的可靠存储数字信息的技术。存储的比特在物理上是被磁化到两个稳定极性之一的微小磁性颗粒的集合。本项目依托二维磁记录的新范式，利用少量颗粒存储1位，结合信号检测对用户数据进行二维编码，确保信息的可靠存储和检索。该项目解决了二维磁记录的主要挑战，这是由于颗粒形状不规则且随机放置在介质表面，因此，由于介质的随机粒度，信号读回受到噪声的支配。该项目开发了新的数据恢复算法，能够补偿如此高的噪声水平。这些算法基于先进的信息论和编码理论概念，即约束码、概率图模型和迭代检测和解码。二维约束被看作是平面的彩色平铺，它提供了丰富的平面气体模型理论和组合学的多米诺骨牌和菱形平铺理论。在检测方面，该项目开发了广义信念传播和线性规划算法，用于处理二维磁记录图形模型中的大量环路。鉴于创建、处理和存储的数字数据量的巨大增长，确保磁硬盘驱动器容量的持续快速增长至关重要。该项目涉及一项新技术，该技术有可能将硬盘容量增加一个数量级。本课题开发的提高存储容量的信号处理方法对未来存储系统的发展具有至关重要的作用。它们不仅在数据存储领域提供了新的性能标准，而且对新一代计算机、数据网络和互联网上提供的服务的性能能力有直接影响。

Magnetic recording is the most widely used technology for reliably storing digital information. A stored bit is physically realized as a collection of tiny magnetic grains magnetized to one of two stable polarities. This project relies on a new paradigm of two-dimensional magnetic recording, which exploits a small number of grains to store one bit as well as two-dimensional coding of user data combined with signal detection to ensure reliable storage and retrieval of information.The project addresses the main challenge in two-dimensional magnetic recording which arises due to the fact that grains are irregularly shaped and randomly positioned on the media surface, and hence, the signal read back is dominated by noise due to this random granularity of the medium. The project develops novel data recovery algorithms capable of compensating such high noise levels. These algorithms are based on advanced information theory and coding theory concepts, namely, constrained codes, probabilistic graphical models, and iterative detection and decoding. A two-dimensional constraint is viewed as a colored tiling of a plane, which affords using the rich theory of planar gas models from statistical mechanics and the theory of domino and lozenge tilings from combinatorics. On the detection front, the project develops generalized belief propagation and linear programming algorithms for dealing with the large number of loops in two-dimensional magnetic recording graphical models.In light of the tremendous growth of the amount of digital data created, processed and stored, it is vitally important to ensure the continued rapid increases in capacity of magnetic hard disk drives. The project is concerned with a new technology that has the potential to increase hard drive capacity by an order of magnitude. Signal processing methods for improving storage capacity developed in this project have a crucial role in providing a foundation for development of future storage systems. They provide not only a new standard of performance in the area of data storage, but have a direct impact on the performance capabilities of a new generation of computers, data networks and services provided on the internet.