CIF: Medium: Collaborative Research: Spatially Coupled Sparse Codes on Graphs - Theory, Practice, and Extensions

CIF：媒介：协作研究：图上的空间耦合稀疏代码 - 理论、实践和扩展

• 批准号: 1161762
• 负责人: Roxana Smarandache
• 金额: $ 15.4万
• 依托单位: San Diego State University Foundation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-05-01 至 2012-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1161762&HistoricalAwards=false
• 关键词: CIF; Medium; Collaborative; Research; Spatially

This research investigates a new approach to protecting the reliability of digital communication and digital storage systems. This approach takes advantage of recent work (by the research team and others) that formulates the "encoding" and "decoding" of data in terms of a novel graphical representation; this formulation has several advantages over existing techniques for insuring data integrity, including better performance at very low power and the absence of an 'error floor', i.e., the ability to consistently (and significantly) lower the decoded error probability with incremental expenditures of power. The ultimate goal of the research is more reliable delivery of digital data, text, computer files, speech and audio signals, video, etc. - using devices that require less power (and thus have longer battery life) and shorter processing delay.More specifically, the research investigates the use of spatially coupled sparse codes - channel (error control) codes with a sparse parity check representation formed by coupling together a chain of small "protographs". This approach, which was pioneered by the research team in the context of terminated low-density parity check convolutional codes, has recently been shown to possess a unique combination of properties - iterative decoding performance that approaches channel capacity and minimum distance that grows linearly with block length - as the code size gets large. The research follows four tracks: (1) the design and analysis of low latency/memory decoding strategies; (2) decoded error probability performance guarantees; (3) the development and analysis of spatially coupled sparse codes with algebraic structure; and (4) the application of spatial coupling outside the immediate domain of channel coding, including cooperative diversity, compressed sensing, and multi-terminal source/channel coding.

这项研究研究了一种保护数字通信和数字存储系统可靠性的新方法。 这种方法利用了最新的工作（研究团队和其他工作），从新的图形表示方面制定了数据的“编码”和“解码”；与现有技术相比，该公式具有多个优势，以确保数据完整性，包括在非常低的功率下的性能以及没有“误差地板”，即具有持续（并显着）降低解码错误概率而使用功率增量支出的能力。 The ultimate goal of the research is more reliable delivery of digital data, text, computer files, speech and audio signals, video, etc. - using devices that require less power (and thus have longer battery life) and shorter processing delay.More specifically, the research investigates the use of spatially coupled sparse codes - channel (error control) codes with a sparse parity check representation formed by coupling together a chain of small "protographs". 这种方法是在终止的低密度平价检查卷积代码的背景下由研究团队开创的，最近已证明具有独特的属性组合 - 迭代解码性能，可接近通道容量和最小距离，并且最小距离随块长度增长 - 代码尺寸很大。 研究遵循四个曲目：（1）低延迟/记忆解码策略的设计和分析； （2）解码错误概率性能保证； （3）具有代数结构的空间耦合稀疏代码的开发和分析； （4）在通道编码的直接域之外的空间耦合，包括合作多样性，压缩感应和多端源/通道编码。