CIF:Small: The Design and Analysis of Spatially-Coupled Coding Systems
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The storage and transmission of digital information is now ubiquitous in our society and plays a valuable role in the modern information-technology infrastructure. Error-correcting codes are a key part of infrastructure components that efficiently and reliably store and transmit digital information. Spatial coupling is a new technique for designing error-correcting codes that has been shown in some cases to achieve near-optimal performance with low-complexity decoding. This research focuses on the design and analysis of innovative techniques for the storage and transmission of digital information based on spatially-coupled codes. The research is broken into three broad thrusts. The first thrust focuses on generalizing recent proof techniques for spatially-coupled codes to include a wide class of inference problems on spatially-coupled graphical models. The second thrust considers the design of universal spatially-coupled codes for multiuser communication problems including the noisy Slepian-Wolf problem and multiple-access communication. The third thrust targets source and channel coding problems with side information and focuses on nested spatially-coupled codes with enhanced message-passing decoding. Spatial coupling also appears to be a general principle that is broadly applicable to problems involving message passing and inference on factor graphs. Therefore, this research is expected to have an impact on science and engineering disciplines beyond communications such as signal processing and machine learning.