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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.

无线干扰网络的容量问题是网络信息论的一个重要的开放性问题。在过去十年中，在这个问题上取得了很大进展。然而，最初的重点一直在分歧的极端：在信道知识是可用的无限精确或完全没有;干扰是太强或太弱;在信道是完全恒定或独立变化。以前的研究都集中在极端的情况下，从根本上得出不同的结论，这项研究通过解决不兼容的地方，他们存在和利用协同效应无处不在的调和分歧的极端。逐步探索全方位的部分渠道知识、渠道优势和渠道一致性模式。这三个目标的基石包括拓扑干扰管理的最新进展、将干扰视为噪声的最优性以及盲干扰对齐。这项研究的最后一个关键因素是鲁棒外边界的突破，称为对齐图像集（AIS）方法？一种新颖的组合参数，其基于发射机可用的信道知识的量来限定由一组码字在不同接收机处投射的图像的相对大小。该研究将容量限制的理论追求与对鲁棒性的实际关注相结合。了解无线通信网络在稳健环境中的能力对于工业界、学术界、政府机构和整个社会来说是至关重要的，以便对未来的网络有现实的期望。