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CIF: Small: Fundamental Limits of Robust Interference Management -- Between the Extremes

CIF：小：稳健干扰管理的基本限制——极端之间

基本信息

批准号：
1617504
负责人：
Syed Jafar
金额：
$ 49.98万
依托单位：
University of California-Irvine
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2016
资助国家：
美国
起止时间：
2016-06-15 至 2020-12-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1617504&HistoricalAwards=false
关键词：
CIF Small Fundamental Limits Robust

项目摘要

The capacity of wireless interference networks is one of the most important open problems of network information theory. Much progress has been made on this problem within the past decade. However, the initial focus has been on divergent extremes: where channel knowledge is available either with infinite precision or entirely absent; where the interference is either too strong or too weak; where channels are either perfectly constant or independently varying. Where previous studies have focused on extreme scenarios to arrive at radically divergent conclusions, this research reconciles the divergent extremes by resolving incompatibilities wherever they exist and exploiting synergies everywhere possible.The research is comprised of three main components ? exploring progressively, the full range of partial channel knowledge, channel strengths, and channel coherence patterns. The stepping stones for the three thrusts include recent advances in topological interference management, the optimality of treating interference as noise, and blind interference alignment. The final critical ingredient of this research is a breakthrough in robust outer bounds, called the Aligned Image Sets (AIS) approach ? a novel combinatorial argument that bounds the relative size of the images cast by a set of codewords at different receivers based on the amount of channel knowledge available to the transmitters. The research combines the theoretical pursuit of capacity limits with the practical concern for robustness. Understanding the capabilities of wireless communication networks in robust settings is essential for the industry, the academia, the government agencies and the society in general to have realistic expectations from the networks of the future.

无线干扰网络容量是网络信息论中最重要的公开问题之一。在过去的十年里，在这个问题上取得了很大的进展。然而，最初的重点一直放在不同的极端情况上：在这种情况下，可以无限精确地获得信道知识，或者完全不存在；在干扰太强或太弱的情况下；在信道完全恒定或独立变化的情况下。以前的研究侧重于极端情景以得出截然不同的结论，而这项研究通过解决存在的不兼容性并尽可能地利用协同效应来调和分歧的极端。该研究由三个主要部分组成？循序渐进地探索全方位的部分渠道知识、渠道优势和渠道连贯性模式。三次推进的垫脚石包括拓扑干扰管理的最新进展，将干扰视为噪声的最佳性，以及盲干扰对齐。这项研究的最后一个关键因素是在稳健外部边界方面的突破，称为对齐图像集(AIS)方法？一种新的组合论点，基于发射机可用的信道知识的量，限定由一组码字在不同接收器投射的图像的相对大小。这项研究将对容量极限的理论追求与对稳健性的实际关注结合在一起。了解无线通信网络在强健环境下的能力对于业界、学术界、政府机构和整个社会对未来网络有现实的期望是至关重要的。