Collaborative Research: New Directions in Graph-Based Code Design

合作研究：基于图的代码设计的新方向摘要这项合作研究的重点是数字通信系统设计的物理层？特别是在分析、设计和实现用于实际通信环境的接近容量的低密度奇偶校验（LDPC）码方面。 在过去的十年中，随着基于图的编码和迭代译码算法的日益普及，信道编码领域发生了革命性的变化。 这些编码方法，包括Turbo码和LDPC码，接近香农在1948年里程碑式的论文中承诺的信道编码性能的极限。目前，这些代码正在许多数字通信和存储标准中取代传统的错误控制技术，包括深空通信，下一代无线传输，最后一英里电缆传输，数字视频广播和高密度数字磁记录。 特别是，它侧重于LDPC卷积码的分析，设计和实现，与LDPC分组码相比，它具有几个优点，但尚未受到研究界的关注。另一方面，传统的卷积码在许多实际通信环境中具有变革性的影响，在接近容量的LDPC码世界中也可能是如此。 该项目强调弥合先进的理论研究和现实的实际执行之间的差距。 特别地，它涉及使LDPC卷积码设计适应需要帧长度和码率两者的灵活性的各种工业标准，并且涉及开发可以在真实的操作条件下测试的硬件解码器的VLSI实现。

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.