Collaborative Research: New Directions in Graph-Based Code Design

协作研究：基于图的代码设计的新方向

• 批准号: 0830650
• 负责人: Daniel Costello
• 金额: $ 27万
• 依托单位: University of Notre Dame
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-15 至 2012-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0830650&HistoricalAwards=false
• 关键词: Collaborative; Research; New; Directions; Graph

Collaborative Research:New Directions in Graph-Based Code DesignAbstractThis collaborative research focuses on the physical layer of digital communication system design ? in particular on the analysis, design, and implementation of capacity-approaching low-density parity-check (LDPC) codes for practical communication environments. In the last ten years, the area of channel coding has undergone a revolutionary change with the growing popularity of graph-based codes and iterative decoding algorithms. These coding methods, which include both turbo codes and LDPC codes, approach the limits of channel coding performance promised by Shannon in his landmark 1948 paper. Currently, these codes are in the process of replacing conventional error control techniques in numerous digital communication and storage standards, including, among others, deep-space communication, next-generation wireless transmission, last-mile cable transmission, digital video broadcasting, and high-density digital magnetic recording.The research addresses several issues related to graph-based codes. In particular, it focuses on the analysis, design, and implementation of LDPC convolutional codes, which have several advantages compared to LDPC block codes, but have not received much attention from the research community. Conventional convolutional codes, on the other hand, have had a transformative effect in numerous practical communication environments, and the same is likely to be true in the capacity-approaching world of LDPC codes. The project emphasizes bridging the gap between advanced theoretical research and realistic practical implementations. In particular, it is concerned with adapting LDPC convolutional code designs to various industry standards that require flexibility in both frame length and code rate and with developing VLSI implementations of hardware decoders that can be tested under real operating conditions.

协作研究：基于图形的代码DesignAbstractthis协作研究的新方向的重点是数字通信系统设计的物理层？尤其是在实用通信环境的低密度奇偶校验检查（LDPC）代码的分析，设计和实施中。 在过去的十年中，随着基于图的代码和迭代解码算法的日益普及，渠道编码领域经历了革命性的变化。 这些编码方法（包括涡轮代码和LDPC代码）都接近Shannon在其具有里程碑意义的1948年论文中承诺的通道编码性能的限制。目前，这些代码正在替换许多数字通信和存储标准中的常规错误控制技术，包括深空通信，下一代无线传输，上一英里电缆传输，数字视频广播以及高密度的数字磁性记录。该研究解决了与图基代码相关的几个问题。 特别是，它着重于LDPC卷积代码的分析，设计和实施，与LDPC块代码相比，该代码具有多个优势，但并未受到研究界的关注。另一方面，传统的卷积代码在众多实用的通信环境中具有变革性的效果，而在LDPC代码的能力世界中，情况也可能是正确的。 该项目强调弥合高级理论研究与现实实践实现之间的差距。 特别是，它与将LDPC卷积代码设计适应各种行业标准有关，这些标准需要在框架长度和代码速率上灵活性以及开发可以在实际操作条件下进行测试的硬件解码器的VLSI实现。