本项目主要面向流媒体、存储系统或光纤通信等低时延高可靠、高谱效、以及海量接入的应用场景，深入研究空间耦合多元Turbo-like码（或称为多元编织卷积码）的构造、优化、性能分析和在译码延迟受限的条件下的译码性能，借助于最大似然性能分析与密度进化分析工具，探索空间耦合码在滑窗译码机制下的性能界。通过结合空间耦合思想，借助于EXIT Chart等性能分析工具对其渐进性能分析和优化设计，提出空间耦合码的高谱效传输方案和空间耦合稀疏码多址接入技术（SCMA）方案，为未来的移动互联网和高速光纤通信等应用提供技术支撑。主要研究内容包括：空间耦合多元Turbo-like码的设计、构造以及性能分析；空间耦合多元Turbo-like码的低延迟和低复杂度译码算法研究；噪声信道上空间耦合码的高谱效传输方案的设计和性能分析；以及空间耦合非正交多址接入技术研究。

This project is oriented towards the application scenarios with high reliability, low latency, high spectral efficiency, and massive access, such as the streaming data, the memory system, fiber-optical communications, and so on. The construction, optimization, performance analysis, and the decoding with the limited decoding latency of spatially coupled nonbinary turbo-like codes (or termed as nonbinary braided convolutional codes) are studied. By means of the maximum likelihood (ML) decoding performance analysis and the density evolution analysis, we calculate the performance bound of the spatially coupled nonbinary turbo-like code with window decoding. With the idea of spatial coupling, we propose the high spectral-efficiency transmission scheme with the spatially coupled nonbinary turbo-like codes and the spatially coupled SCMA system. We analyze their asymptotic performance and optimize them using EXIT (Extrinsic Information Transfer) Chart. It can provide the technical support to the future mobile internet, high-speed fiber-optical communications, and so on. The research topics include: design，optimization, and performance analysis of spatially coupled nonbinary turbo-like codes; the low-latency and low-complexity decoding algorithms; design and performance analysis of the high spectral-efficiency transmission scheme with the spatially coupled nonbinary turbo-like code over noisy channels; research on the spatially coupled SCMA system.