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Application-Driven Coding Techniques: From Cloud Storage to Quantum Communications

Abstract

Data-driven applications are becoming ubiquitous. This dissertation is focused on developing advanced channel coding techniques for improved reliability and latency in a variety of data-hungry applications, from cloud storage, to memory devices, and quantum communications.

The first line of our work focused on cloud storage. In order to accommodate the ever-growing data from various, possibly independent, sources and the dynamic nature of data usage rates in practical applications, modern cloud data storage systems are required to be scalable, flexible, and heterogeneous. The recent rise of the blockchain technology is also moving various information systems towards decentralization to achieve high privacy at low costs. We proposed channel codes with hierarchical locality that were the first to simultaneously achieve scalability and flexibility for both centralized cloud storage and decentralized storage networks (DSN). In particular, we proposed a joint coding scheme where each node receives extra protection through the cooperation with nodes in its neighborhood in a heterogeneous DSN with any given topology. Our proposed construction not only preserves desirable properties such as scalability and flexibility, which are critical in dynamic networks, but also adapts to arbitrary topologies, a property that is essential in DSNs but has been overlooked in existing works.

The second line of our work focused on spatially-coupled (SC) codes design for advanced memory devices and quantum communications. SC codes have demonstrated potential in a variety of applications thanks to their excellent error-correcting performance and desirable structures that enable low latency decoding. While high memory SC codes are known to have superior performance, no prior work was able to produce practical codes due to computational complexity of the high-memory regime. We overcome this computational bottleneck in the finite-length construction of high-performance SC codes with high memory, with a novel coding framework that unifies seemingly disparate probabilistic and combinatorial approaches, and benefits from both. Simulation results show that codes obtained through our proposed method notably outperform state-of-the-art codes in a variety of practical settings, including flash memories and hard disk drives. Building on this new framework, we then developed a new class of channel codes for quantum communications. Combined with irregular-repeat-accumulate (IRA) codes that are known for excellent performance on low rate region, we constructed state-of-the-art SC-IRA codes for multidimensional quantum key distribution to efficiently generate private keys for one-time pad encrypted communications.

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