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.

在通信信道的建模和性能表征中，信息论的数学框架对概念理解和技术发展都做出了重大贡献。 尽管它在某些应用中取得了巨大的成功，但在许多应用中，特别是在延迟受限和许多网络场景中，经典信息理论提供的见解较少，或者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于长编码块长度。 我们认为，信息理论的应用到现代应用可以加速由“有限块长度”的信息理论，一般足以处理广泛的一类重要的信道模型，但不那么复杂和微妙，以便基本上是不可用的系统designers.This研究中心围绕活动的发展有限块长度信息理论的一般框架，为现代通信系统和网络。 的指导目标是开发一个单一的随机变量称为互信息密度率，而不是它的期望方面的通信信道和编码策略的适当的抽象。预期的抽象将使网络设计师的性能和架构评估的表征，以及促进数量级的网络仿真加速。 该技术方法是全面的，利用理论分析，计算机模拟和试验台实验。 已经确定了研究与教育相结合的机会，预计将有大量的相互促进。