Random Matrix Theory and Wireless Communications

IF 2 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
A. Tulino, S. Verdú
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引用次数: 2125

Abstract

Random matrix theory has found many applications in physics, statistics and engineering since its inception. Although early developments were motivated by practical experimental problems, random matrices are now used in fields as diverse as Riemann hypothesis, stochastic differential equations, condensed matter physics, statistical physics, chaotic systems, numerical linear algebra, neural networks, multivariate statistics, information theory, signal processing and small-world networks. This article provides a tutorial on random matrices which provides an overview of the theory and brings together in one source the most significant results recently obtained. Furthermore, the application of random matrix theory to the fundamental limits of wireless communication channels is described in depth.
随机矩阵理论与无线通信
随机矩阵理论自诞生以来,在物理学、统计学和工程学中得到了广泛的应用。尽管早期的发展是由实际的实验问题推动的,但随机矩阵现在被用于各种领域,如黎曼假设、随机微分方程、凝聚态物理、统计物理、混沌系统、数值线性代数、神经网络、多元统计、信息论、信号处理和小世界网络。本文提供了一个关于随机矩阵的教程,它提供了理论的概述,并汇集了最近获得的最重要的结果。此外,还对随机矩阵理论在无线通信信道基本限制中的应用进行了深入的描述。
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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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