CAREER: Towards a Renassaince in Finite Blocklength Length Information Theory

职业：走向有限块长度信息理论的复兴

• 批准号: 0546618
• 负责人: J Nicholas Laneman
• 金额: $ 40万
• 依托单位: University of Notre Dame
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-03-01 至 2013-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0546618&HistoricalAwards=false
• 关键词: CAREER; Towards; Renassaince; Finite; Blocklength

In the modeling and performance characterization of communication channels, the mathematical framework of information theory has contributed significantly to both conceptual understanding as well as technology development. Despite its magnificent success for certain applications, there are many applications, particularly in delay-constrained and many network scenarios, in which classical information theory has offered fewer insights, or otherwise the available insights have not been fully integrated into existing systems. One of the drawbacks of the classical theory is its reliance on long coding blocklengths. We believe that application of information theory to modern applications can be accelerated by a "finite blocklength" information theory that is general enough to handle a wide class of important channel models but not so complex and subtle so as to be essentially unusable by system designers.This research centers around activities for developing a general framework of finite blocklength information theory for modern communication systems and networks. The guiding objective is to develop suitable abstractions of communication channels and coding strategies in terms of a single random variable called the mutual information density rate, rather than its expectation. The anticipated abstractions will enable characterization of performance and architectural evaluation by network designers as well as facilitate orders of magnitude speedups in network simulation. Thetechnical approach is comprehensive, leveraging theoretical analysis, computer simulation, and testbed experiments. Opportunities for integration of research and education have been identified, and substantial cross-fertilization is expected.

在沟通渠道的建模和性能表征中，信息理论的数学框架对概念理解和技术发展都有很大贡献。 尽管在某些应用程序方面取得了巨大的成功，但仍有许多应用程序，尤其是在延迟限制和许多网络方案中，经典信息理论提供了更少的见解，或者否则可用的见解尚未完全集成到现有系统中。 经典理论的缺点之一是它依赖长期编码区块。 我们认为，将信息理论应用于现代应用程序可以通过“有限的区块长度”信息理论加速，该理论足以处理一类重要的渠道模型，但并非如此复杂和微妙，以至于系统设计师基本上无法使用。该研究中心围绕着开发现代通信系统和网络的有限块信息理论的活动。 指导目标是根据一个称为相互信息密度速率的单个随机变量，而不是其期望来开发合适的通信渠道和编码策略的抽象。预期的抽象将使网络设计人员对性能和架构评估进行表征，并促进网络模拟中的数量级加速顺序。 技术方法是全面的，利用理论分析，计算机模拟和测试床实验。 已经确定了研究和教育整合的机会，并有望进行大量的交叉施肥。