TF-Capacity-Approaching Coding and Detection for Page-Oriented Digital Recording Channels.

在过去的十年中，廉价、可靠、高容量的小型数据存储设备的出现彻底改变了个人计算和信息管理。最近，随着高密度磁盘驱动器被引入数码相机、音频播放器和机顶盒视频录制系统等产品，存储设备正在改变消费电子产品的世界。这些流行的应用，以及在科学和商业中大规模存储系统的使用，将推动磁记录技术的持续进步。这些进步，如垂直记录，有望产生高达每平方英寸5000亿位信息的面密度。然而，除此之外，磁记录技术可能会在可实现的密度和数据传输速率方面遇到基本的物理限制。因此，追求高容量数字信息存储的新方法至关重要。这些方法中有许多使用面向页面的读写，这与今天的面向跟踪的方法形成了对比。示例包括在纳米尺度图案介质上的记录、多光束二维光学记录和光学全息记录。本项目研究这些面向页面技术的存储容量的理论极限，以及在实践中达到这些极限所需的信号处理和编码算法。具体而言，该项目涉及编码和检测具有符号间干扰信道的噪声二维信道的理论和算法方面。研究人员研究了这些信道的新颖迭代、软输入、软输出检测方法，以及容量逼近代数和基于图的错误控制码及其解码算法。该项目还开发了二维受限调制码的信息理论基础和构建技术。这些信号处理和编码方法结合在新的系统架构中，其性能使用分析和计算方法进行评估。

The availability of inexpensive, reliable, high-capacity data storage devices in compact form factors has revolutionized personal computing and information management during the past decade. More recently, with the introduction of high-density disk drives into such products as digital cameras, audio players, and set-top video recording systems, storage devices are transforming the world of consumer electronics. These popular applications, as well as the use of mass storage systems in science and commerce, will motivate continued advances in magnetic recording technology. These advances, such as perpendicular recording, are expected to yield areal densities as high as 500 billion bits of information per square inch. Beyond that, however, magnetic recording technology will likely encounter fundamental physical limits on achievable density and data transfer rate. Therefore, it is vital to pursue new approaches to high capacity digital information storage. Many of these approaches use page-oriented reading and writing, in contrast to today's track-oriented methods. Examples include recording on nano-scale patterned media, multi-beam two-dimensional optical recording, and optical holographic recording. This project studies theoretical limits on the storage capacity of these page-oriented technologies, as well as the signal processing and coding algorithms needed to achieve those limits in practice. Specifically, the project addresses theoretical and algorithmic aspects of coding and detection for noisy two-dimensional channels with intersymbol interference channels. The investigators study novel iterative, soft-input, soft-output detection methods for these channels, as well as capacity-approaching algebraic and graph-based error-control codes and their decoding algorithms. The project also develops information-theoretic foundations and construction techniques for two-dimensional constrained modulation codes. These signal processing and coding methods are combined in novel system architectures, whose performance is evaluated using analytical and computational methods.