CRII: CIF: Towards a Systematic Interference Alignment Approach for Network Information Flow

CRII：CIF：迈向网络信息流的系统干扰对齐方法

• 批准号: 1464336
• 负责人: Viveck Cadambe
• 金额: $ 17.44万
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-08-01 至 2018-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1464336&HistoricalAwards=false
• 关键词: CRII; CIF; Towards; Systematic; Interference

Communication and storage networks play an integral role in various aspects of modern life. The design of an efficient infrastructure of communication and storage relies significantly on algorithms for efficient information flow among its various components. The multiple unicast network capacity characterization problem is an information theoretic abstraction that captures the fundamental challenges in information flow in several communication and storage systems. Despite its importance, development of optimal codes in multiple unicast networks is a challenging unsolved problem in information theory. Recently the idea of interference alignment, which was originally discovered in the context of wireless systems, has been shown to be an important tool in multiple unicast network coding. However, uncovering interference alignment based achievable coding schemes remains an art; alignment-based solutions typically must be carefully handcrafted based on the specific network scenario under consideration. A dearth of systematic alignment based approaches has restricted the impact of this idea to a narrow class of network topologies and configurations. The objective of this project is to fill this gap by developing systematic interference alignment based algorithms for multiple unicast network coding. The project will include the study of several toy models of networks, which are tailor-made to expose the role of alignment. Insights obtained from the toy models will be incorporated into network coding algorithms for general networks over directed acyclic graphs. The performance of the algorithms developed will be studied through analytical and numerical methods.The proposed work involves fundamental contributions to the field of network information theory, specifically to the sub-topic of network coding, through the study of canonical problems in the field. The developments of the project will impact the design of data centers, content distribution networks and wireless communication networks. The research developed will be disseminated through peer-reviewed conferences and journals. The source code for algorithms developed will be made available to the public.

通信和存储网络在现代生活的各个方面发挥着不可或缺的作用。 有效的通信和存储基础设施的设计在很大程度上依赖于在其各个组件之间进行有效信息流的算法。多单播网络容量表征问题是一个信息理论的抽象，捕捉在几个通信和存储系统中的信息流的基本挑战。尽管它的重要性，在多个单播网络中的最佳码的发展是一个具有挑战性的信息论尚未解决的问题。最近，干扰对齐的想法，这最初是在无线系统的上下文中发现的，已被证明是一个重要的工具，在多个单播网络编码。然而，发现基于干扰对齐的可实现编码方案仍然是一种技术;基于干扰对齐的解决方案通常必须基于所考虑的特定网络场景来仔细手工制作。缺乏系统的对齐为基础的方法限制了这一想法的影响，以一个狭窄的网络拓扑结构和配置类。本项目的目标是填补这一空白，开发系统的干扰对齐多个单播网络编码的算法为基础。该项目将包括研究几个玩具模型的网络，这是量身定制的，以揭示对齐的作用。从玩具模型获得的见解将被纳入网络编码算法的一般网络上有向无环图。所开发的算法的性能将通过分析和数值方法进行研究。所提出的工作涉及网络信息理论领域的基本贡献，特别是网络编码的子主题，通过研究该领域的规范问题。该项目的发展将影响数据中心、内容分发网络和无线通信网络的设计。所开展的研究将通过同行审查的会议和期刊传播。开发的算法源代码将向公众提供。