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。 高效通信和存储基础设施的设计在很大程度上依赖于其各个组件之间高效信息流的算法。多单播网络容量表征问题是一种信息理论抽象，它捕获了多种通信和存储系统中信息流的基本挑战。尽管它很重要，但在多个单播网络中开发最优代码是信息论中一个具有挑战性的未解决问题。最近，干扰对齐的想法最初是在无线系统的背景下发现的，已被证明是多单播网络编码中的重要工具。然而，揭示基于干扰对齐的可实现编码方案仍然是一门技术。基于对齐的解决方案通常必须根据所考虑的特定网络场景精心设计。由于缺乏基于系统对齐的方法，这一想法的影响仅限于一小类网络拓扑和配置。该项目的目标是通过开发基于系统干扰对齐的多单播网络编码算法来填补这一空白。该项目将包括对几个网络玩具模型的研究，这些模型是为揭示对齐的作用而量身定制的。从玩具模型中获得的见解将被纳入有向无环图上通用网络的网络编码算法中。所开发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础性贡献，特别是通过研究该领域的典型问题，特别是网络编码的子主题。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。所开发的研究将通过同行评审的会议和期刊进行传播。所开发算法的源代码将向公众开放。