随机集理论与无线通信

IF 2 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
E. Biglieri, E. Grossi, M. Lops
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引用次数: 24

摘要

这本专著致力于随机集理论,它允许从任意空间绘制的随机元素的无序集合进行处理。在说明了它的基础之后,我们将重点放在随机有限集上,即来自任意空间的点的随机基数的无序集合,并展示如何将该理论应用于无线通信系统中出现的一些问题。其中三个问题是:(1)无线网络中的邻居发现;(2)活动用户数量未知且时变的多用户检测;(3)路径数量未知且可能时变的多径信道估计。这些问题的标准解决方案本质上是次优的,因为它们要么是假设一个固定数量的矢量组件,要么是先估计这个数量,然后再计算组件的值。本文展示了随机集理论如何为所有这些问题提供最优解。复杂性问题也进行了研究,并提出和讨论了次优解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Random-Set Theory and Wireless Communications
This monograph is devoted to random-set theory, which allows unordered collections of random elements, drawn from an arbitrary space, to be handled. After illustrating its foundations, we focus on Random Finite Sets, i.e., unordered collections of random cardinality of points from an arbitrary space, and show how this theory can be applied to a number of problems arising in wireless communication systems. Three of these problems are: (1) neighbor discovery in wireless networks, (2) multiuser detection in which the number of active users is unknown and time-varying, and (3) estimation of multipath channels where the number of paths is not known a priori and which are possibly time-varying. Standard solutions to these problems are intrinsically suboptimum as they proceed either by assuming a fixed number of vector components, or by first estimating this number and then the values taken on by the components. It is shown how random-set theory provides optimum solutions to all these problems. The complexity issue is also examined, and suboptimum solutions are presented and discussed.
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来源期刊
Foundations and Trends in Communications and Information Theory
Foundations and Trends in Communications and Information Theory COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-
CiteScore
7.90
自引率
0.00%
发文量
6
期刊介绍: Foundations and Trends® in Communications and Information Theory publishes survey and tutorial articles in the following topics: - Coded modulation - Coding theory and practice - Communication complexity - Communication system design - Cryptology and data security - Data compression - Data networks - Demodulation and Equalization - Denoising - Detection and estimation - Information theory and statistics - Information theory and computer science - Joint source/channel coding - Modulation and signal design - Multiuser detection - Multiuser information theory
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